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- Edited on - - @@ -412,7 +406,7 @@
-
  1. 1. 在工作中碰到的一点C++指针上的一点小问题
+
  1. 1. 在工作中碰到的一点C++指针上的一点小问题
diff --git a/2014/12/24/MFC 模态对话框/index.html b/2014/12/24/MFC 模态对话框/index.html index c05de651a0..822108dfac 100644 --- a/2014/12/24/MFC 模态对话框/index.html +++ b/2014/12/24/MFC 模态对话框/index.html @@ -4,7 +4,7 @@ - + @@ -26,14 +26,15 @@ var CONFIG = {"hostname":"nicksxs.me","root":"/","scheme":"Pisces","version":"7.8.0","exturl":false,"sidebar":{"position":"left","display":"post","padding":18,"offset":12,"onmobile":false},"copycode":{"enable":true,"show_result":false,"style":null},"back2top":{"enable":true,"sidebar":false,"scrollpercent":false},"bookmark":{"enable":false,"color":"#222","save":"auto"},"fancybox":true,"mediumzoom":false,"lazyload":true,"pangu":false,"comments":{"style":"tabs","active":null,"storage":true,"lazyload":false,"nav":null},"algolia":{"hits":{"per_page":10},"labels":{"input_placeholder":"Search for Posts","hits_empty":"We didn't find any results for the search: ${query}","hits_stats":"${hits} results found in ${time} ms"}},"localsearch":{"enable":false,"trigger":"auto","top_n_per_article":1,"unescape":false,"preload":false},"motion":{"enable":true,"async":false,"transition":{"post_block":"fadeIn","post_header":"slideDownIn","post_body":"slideDownIn","coll_header":"slideLeftIn","sidebar":"slideUpIn"}}}; - + - + + - + @@ -229,13 +230,6 @@ - - - - - Edited on - - @@ -285,7 +279,13 @@
- 
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void CTestDialog::OnBnClickedOk() 
{
	CString m_SrcTest;
	int nIndex = m_CbTest.GetCurSel(); 
	m_CbTest.GetLBText(nIndex, m_SrcTest);  
	OnOK();
}
+ 
void CTestDialog::OnBnClickedOk() 
+{
+	CString m_SrcTest;
+	int nIndex = m_CbTest.GetCurSel(); 
+	m_CbTest.GetLBText(nIndex, m_SrcTest);  
+	OnOK();
+}

模态对话框弹出确定后，在弹出对话框时新建的类及其变量会存在，但是对于其中的控件
对象无法调用函数，即如果要在主对话框中获得弹出对话框的Combo box选中值的话，需
要在弹出 对话框的确定函数内将其值取出，赋值给弹出对话框的公有变量，这样就可以
在主对话框类得到值。

diff --git a/2014/12/30/Clone-Graph-Part-I/index.html b/2014/12/30/Clone-Graph-Part-I/index.html index dcc633253c..68cb9d5e4d 100644 --- a/2014/12/30/Clone-Graph-Part-I/index.html +++ b/2014/12/30/Clone-Graph-Part-I/index.html @@ -4,7 +4,7 @@ - + @@ -26,17 +26,18 @@ var CONFIG = {"hostname":"nicksxs.me","root":"/","scheme":"Pisces","version":"7.8.0","exturl":false,"sidebar":{"position":"left","display":"post","padding":18,"offset":12,"onmobile":false},"copycode":{"enable":true,"show_result":false,"style":null},"back2top":{"enable":true,"sidebar":false,"scrollpercent":false},"bookmark":{"enable":false,"color":"#222","save":"auto"},"fancybox":true,"mediumzoom":false,"lazyload":true,"pangu":false,"comments":{"style":"tabs","active":null,"storage":true,"lazyload":false,"nav":null},"algolia":{"hits":{"per_page":10},"labels":{"input_placeholder":"Search for Posts","hits_empty":"We didn't find any results for the search: ${query}","hits_stats":"${hits} results found in ${time} ms"}},"localsearch":{"enable":false,"trigger":"auto","top_n_per_article":1,"unescape":false,"preload":false},"motion":{"enable":true,"async":false,"transition":{"post_block":"fadeIn","post_header":"slideDownIn","post_body":"slideDownIn","coll_header":"slideLeftIn","sidebar":"slideUpIn"}}}; - + - + + - + - + @@ -229,13 +230,6 @@ - - - - - Edited on - - @@ -285,10 +279,46 @@
-

problem

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Clone a graph. Input is a Node pointer. Return the Node pointer of the cloned graph.

A graph is defined below:
struct Node {
vector neighbors;
}
- - -

code

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typedef unordered_map<Node *, Node *> Map;
 
Node *clone(Node *graph) {
    if (!graph) return NULL;
 
    Map map;
    queue<Node *> q;
    q.push(graph);
 
    Node *graphCopy = new Node();
    map[graph] = graphCopy;
 
    while (!q.empty()) {
        Node *node = q.front();
        q.pop();
        int n = node->neighbors.size();
        for (int i = 0; i < n; i++) {
            Node *neighbor = node->neighbors[i];
            // no copy exists
            if (map.find(neighbor) == map.end()) {
                Node *p = new Node();
                map[node]->neighbors.push_back(p);
                map[neighbor] = p;
                q.push(neighbor);
            } else {     // a copy already exists
                map[node]->neighbors.push_back(map[neighbor]);
            }
        }
    }
 
    return graphCopy;
}
+

problem

Clone a graph. Input is a Node pointer. Return the Node pointer of the cloned graph.
+
+A graph is defined below:
+struct Node {
+vector neighbors;
+}
+ + +

code

typedef unordered_map<Node *, Node *> Map;
+ 
+Node *clone(Node *graph) {
+    if (!graph) return NULL;
+ 
+    Map map;
+    queue<Node *> q;
+    q.push(graph);
+ 
+    Node *graphCopy = new Node();
+    map[graph] = graphCopy;
+ 
+    while (!q.empty()) {
+        Node *node = q.front();
+        q.pop();
+        int n = node->neighbors.size();
+        for (int i = 0; i < n; i++) {
+            Node *neighbor = node->neighbors[i];
+            // no copy exists
+            if (map.find(neighbor) == map.end()) {
+                Node *p = new Node();
+                map[node]->neighbors.push_back(p);
+                map[neighbor] = p;
+                q.push(neighbor);
+            } else {     // a copy already exists
+                map[node]->neighbors.push_back(map[neighbor]);
+            }
+        }
+    }
+ 
+    return graphCopy;
+}

anlysis

using the Breadth-first traversal
and use a map to save the neighbors not to be duplicated.

@@ -303,16 +333,16 @@
Number of 1 Bits
  • -
    34_Search_for_a_Range
    +
    G1收集器概述
  • -
    Leetcode 104 二叉树的最大深度(Maximum Depth of Binary Tree) 题解分析
    +
    34_Search_for_a_Range
  • -
    Leetcode 124 二叉树中的最大路径和(Binary Tree Maximum Path Sum) 题解分析
    +
    add-two-number
  • -
    Leetcode 160 相交链表(intersection-of-two-linked-lists) 题解分析
    +
    Leetcode 104 二叉树的最大深度(Maximum Depth of Binary Tree) 题解分析
    • @@ -356,8 +386,8 @@
    - +
    diff --git a/2015/01/04/Path-Sum/index.html b/2015/01/04/Path-Sum/index.html index df7c3940d7..6833c38287 100644 --- a/2015/01/04/Path-Sum/index.html +++ b/2015/01/04/Path-Sum/index.html @@ -4,7 +4,7 @@ - + @@ -32,8 +32,9 @@ + - + @@ -229,13 +230,6 @@ - - - - - Edited on - - @@ -286,12 +280,45 @@

    problem

    Given a binary tree and a sum, determine if the tree has a root-to-leaf path such that adding up all the values along the path equals the given sum.

    - +

    For example:
    Given the below binary tree and sum = 22,

    -
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    7
          5
         / \
        4   8
       /   / \
      11  13  4
     /  \      \
    7    2      1
    +
          5
+     / \
+    4   8
+   /   / \
+  11  13  4
+ /  \      \
+7    2      1

    return true, as there exist a root-to-leaf path 5->4->11->2 which sum is 22.

    Analysis

    using simple deep first search

    -

    code

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    /*
      Definition for binary tree
      struct TreeNode {
          int val;
          TreeNode *left;
          TreeNode *right;
          TreeNode(int x) : val(x), left(NULL), right(NULL)}
      };
     */
    class Solution {
    public:
        bool deep_first_search(TreeNode *node, int sum, int curSum)
        {
            if (node == NULL)
                return false;
            
            if (node->left == NULL && node->right == NULL)
                return curSum + node->val == sum;
                   
            return deep_first_search(node->left, sum, curSum + node->val) || deep_first_search(node->right, sum, curSum + node->val);
        }
        
        bool hasPathSum(TreeNode *root, int sum) {
            // Start typing your C/C++ solution below
            // DO NOT write int main() function
            return deep_first_search(root, sum, 0);
        }
    };
    +

    code

    /*
+  Definition for binary tree
+  struct TreeNode {
+      int val;
+      TreeNode *left;
+      TreeNode *right;
+      TreeNode(int x) : val(x), left(NULL), right(NULL)}
+  };
+ */
+class Solution {
+public:
+    bool deep_first_search(TreeNode *node, int sum, int curSum)
+    {
+        if (node == NULL)
+            return false;
+        
+        if (node->left == NULL && node->right == NULL)
+            return curSum + node->val == sum;
+               
+        return deep_first_search(node->left, sum, curSum + node->val) || deep_first_search(node->right, sum, curSum + node->val);
+    }
+    
+    bool hasPathSum(TreeNode *root, int sum) {
+        // Start typing your C/C++ solution below
+        // DO NOT write int main() function
+        return deep_first_search(root, sum, 0);
+    }
+};
    @@ -308,10 +335,10 @@
    34_Search_for_a_Range
  • -
    add-two-number
    +
    Number of 1 Bits
  • -
    Number of 1 Bits
    +
    add-two-number
  • Reverse Bits
    diff --git a/2015/01/14/Two-Sum/index.html b/2015/01/14/Two-Sum/index.html index 50c8897371..ce7ed160fe 100644 --- a/2015/01/14/Two-Sum/index.html +++ b/2015/01/14/Two-Sum/index.html @@ -4,7 +4,7 @@ - + @@ -32,8 +32,9 @@ + - + @@ -229,13 +230,6 @@ - - - - - Edited on - - @@ -287,10 +281,59 @@

    problem

    Given an array of integers, find two numbers such that they add up to a specific target number.

    The function twoSum should return indices of the two numbers such that they add up to the target, where index1 must be less than index2. Please note that your returned answers (both index1 and index2) are not zero-based.

    - +

    You may assume that each input would have exactly one solution.

    Input: numbers={2, 7, 11, 15}, target=9
    Output: index1=1, index2=2

    -

    code

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    struct Node
    {
        int num, pos;
    };
    bool cmp(Node a, Node b)
    {
        return a.num < b.num;
    }
    class Solution {
    public:
        vector<int> twoSum(vector<int> &numbers, int target) {
            // Start typing your C/C++ solution below
            // DO NOT write int main() function
            vector<int> result;
            vector<Node> array;
            for (int i = 0; i < numbers.size(); i++)
            {
                Node temp;
                temp.num = numbers[i];
                temp.pos = i;
                array.push_back(temp);
            }

            sort(array.begin(), array.end(), cmp);
            for (int i = 0, j = array.size() - 1; i != j;)
            {
                int sum = array[i].num + array[j].num;
                if (sum == target)
                {
                    if (array[i].pos < array[j].pos)
                    {
                        result.push_back(array[i].pos + 1);
                        result.push_back(array[j].pos + 1);
                    } else
                    {
                        result.push_back(array[j].pos + 1);
                        result.push_back(array[i].pos + 1);
                    }
                    break;
                } else if (sum < target)
                {
                    i++;
                } else if (sum > target)
                {
                    j--;
                }
            }
            return result;
        }
    };
    +

    code

    struct Node
+{
+    int num, pos;
+};
+bool cmp(Node a, Node b)
+{
+    return a.num < b.num;
+}
+class Solution {
+public:
+    vector<int> twoSum(vector<int> &numbers, int target) {
+        // Start typing your C/C++ solution below
+        // DO NOT write int main() function
+        vector<int> result;
+        vector<Node> array;
+        for (int i = 0; i < numbers.size(); i++)
+        {
+            Node temp;
+            temp.num = numbers[i];
+            temp.pos = i;
+            array.push_back(temp);
+        }
+
+        sort(array.begin(), array.end(), cmp);
+        for (int i = 0, j = array.size() - 1; i != j;)
+        {
+            int sum = array[i].num + array[j].num;
+            if (sum == target)
+            {
+                if (array[i].pos < array[j].pos)
+                {
+                    result.push_back(array[i].pos + 1);
+                    result.push_back(array[j].pos + 1);
+                } else
+                {
+                    result.push_back(array[j].pos + 1);
+                    result.push_back(array[i].pos + 1);
+                }
+                break;
+            } else if (sum < target)
+            {
+                i++;
+            } else if (sum > target)
+            {
+                j--;
+            }
+        }
+        return result;
+    }
+};

    Analysis

    sort the array, then test from head and end, until catch the right answer

    @@ -309,10 +352,10 @@
    34_Search_for_a_Range
  • -
    add-two-number
    +
    Number of 1 Bits
  • -
    Number of 1 Bits
    +
    add-two-number
  • Path Sum
    diff --git a/2015/01/16/pcre-intro-and-a-simple-package/index.html b/2015/01/16/pcre-intro-and-a-simple-package/index.html index 7e1a8cacc8..2487cf5c1c 100644 --- a/2015/01/16/pcre-intro-and-a-simple-package/index.html +++ b/2015/01/16/pcre-intro-and-a-simple-package/index.html @@ -4,7 +4,7 @@ - + @@ -32,8 +32,9 @@ + - + @@ -229,13 +230,6 @@ - - - - - Edited on - - @@ -285,25 +279,42 @@
    -

    Pcre

    +

    Pcre

    Perl Compatible Regular Expressions (PCRE) is a regular
    expression C library inspired by the regular expression
    capabilities in the Perl programming language, written
    by Philip Hazel, starting in summer 1997.

    -

    因为最近工作内容的一部分需要做字符串的识别处理，所以就顺便用上了之前在PHP中用过的正则，在C/C++中本身不包含正则库，这里使用的pcre，对MFC开发，在这里提供了静态链接库，在引入lib跟.h文件后即可使用。

    - +

    因为最近工作内容的一部分需要做字符串的识别处理，所以就顺便用上了之前在PHP中用过的正则，在C/C++中本身不包含正则库，这里使用的pcre，对MFC开发，在这里提供了静态链接库，在引入lib跟.h文件后即可使用。

    + -

    Regular Expression Syntax

    然后是一些正则语法，官方的语法文档比较科学严谨，特别是对类似于贪婪匹配等细节的说明，当然一般的使用可以在网上找到很多匹配语法，例如这个。

    +

    Regular Expression Syntax

    然后是一些正则语法，官方的语法文档比较科学严谨，特别是对类似于贪婪匹配等细节的说明，当然一般的使用可以在网上找到很多匹配语法，例如这个。

    PCRE函数介绍

    pcre_compile
    原型：

    -
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    #include <pcre.h>
    pcre *pcre_compile(const char *pattern, int options, const char **errptr, int *erroffset, const unsigned char *tableptr);
    +
    #include <pcre.h>
+pcre *pcre_compile(const char *pattern, int options, const char **errptr, int *erroffset, const unsigned char *tableptr);

    功能：将一个正则表达式编译成一个内部表示，在匹配多个字符串时，可以加速匹配。其同pcre_compile2功能一样只是缺少一个参数errorcodeptr。
    参数：
    pattern 正则表达式
    options 为0，或者其他参数选项
    errptr 出错消息
    erroffset 出错位置
    tableptr 指向一个字符数组的指针，可以设置为空NULL

    pcre_exec
    原型：

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    #include <pcre.h>
    int pcre_exec(const pcre *code, const pcre_extra *extra, const char *subject, int length, int startoffset, int options, int *ovector, int ovecsize)
    +
    #include <pcre.h>
+int pcre_exec(const pcre *code, const pcre_extra *extra, const char *subject, int length, int startoffset, int options, int *ovector, int ovecsize)

    功能：使用编译好的模式进行匹配，采用与Perl相似的算法，返回匹配串的偏移位置。
    参数：
    code 编译好的模式
    extra 指向一个pcre_extra结构体，可以为NULL
    subject 需要匹配的字符串
    length 匹配的字符串长度（Byte）
    startoffset 匹配的开始位置
    options 选项位
    ovector 指向一个结果的整型数组
    ovecsize 数组大小。

    -

    这里是两个最常用的函数的简单说明，pcre的静态库提供了一系列的函数以供使用，可以参考这个博客说明，另外对于以上函数的具体参数详细说明可以参考官网此处

    -

    一个丑陋的封装

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    void COcxDemoDlg::pcre_exec_all(const pcre * re, PCRE_SPTR src, vector<pair<int, int>> &vc)
    {
    	int rc;
    	int ovector[30];
    	int i = 0;
    	pair<int, int> pr;
    	rc = pcre_exec(re, NULL, src, strlen(src), i, 0, ovector, 30);
    	for (; rc > 0;)
    	{
    		i = ovector[1];
    		pr.first = ovector[2];
    		pr.second = ovector[3];
    		vc.push_back(pr);
    		rc = pcre_exec(re, NULL, src, strlen(src), i, 0, ovector, 30);
    	}
    }
    +

    这里是两个最常用的函数的简单说明，pcre的静态库提供了一系列的函数以供使用，可以参考这个博客说明，另外对于以上函数的具体参数详细说明可以参考官网此处

    +

    一个丑陋的封装

    void COcxDemoDlg::pcre_exec_all(const pcre * re, PCRE_SPTR src, vector<pair<int, int>> &vc)
+{
+	int rc;
+	int ovector[30];
+	int i = 0;
+	pair<int, int> pr;
+	rc = pcre_exec(re, NULL, src, strlen(src), i, 0, ovector, 30);
+	for (; rc > 0;)
+	{
+		i = ovector[1];
+		pr.first = ovector[2];
+		pr.second = ovector[3];
+		vc.push_back(pr);
+		rc = pcre_exec(re, NULL, src, strlen(src), i, 0, ovector, 30);
+	}
+}

    vector中是全文匹配后的索引对，只是简单地用下。

    @@ -453,7 +464,7 @@
    -
    1. 1. Pcre
    2. 2. Regular Expression Syntax
    3. 3. PCRE函数介绍
    4. 4. 一个丑陋的封装
    +
    1. 1. Pcre
    2. 2. Regular Expression Syntax
    3. 3. PCRE函数介绍
    4. 4. 一个丑陋的封装
    diff --git a/2015/03/11/Number-Of-1-Bits/index.html b/2015/03/11/Number-Of-1-Bits/index.html index 8cee4002e5..4c502c7fa4 100644 --- a/2015/03/11/Number-Of-1-Bits/index.html +++ b/2015/03/11/Number-Of-1-Bits/index.html @@ -4,7 +4,7 @@ - + @@ -32,8 +32,9 @@ + - + @@ -229,13 +230,6 @@     - - - - - Edited on - - @@ -285,11 +279,25 @@
    -

    Number of 1 Bits

    Write a function that takes an unsigned integer and returns the number of ’1’ bits it has (also known as the Hamming weight). For example, the 32-bit integer ‘11’ has binary representation 00000000000000000000000000001011, so the function should return 3.

    +

    Number of 1 Bits

    Write a function that takes an unsigned integer and returns the number of ’1’ bits it has (also known as the Hamming weight). For example, the 32-bit integer ‘11’ has binary representation 00000000000000000000000000001011, so the function should return 3.

    分析

    从1位到2位到4位逐步的交换

    -

    code

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    int hammingWeight(uint32_t n) {
            const uint32_t m1  = 0x55555555; //binary: 0101...  
            const uint32_t m2  = 0x33333333; //binary: 00110011..  
            const uint32_t m4  = 0x0f0f0f0f; //binary:  4 zeros,  4 ones ...  
            const uint32_t m8  = 0x00ff00ff; //binary:  8 zeros,  8 ones ...  
            const uint32_t m16 = 0x0000ffff; //binary: 16 zeros, 16 ones ...  
            
            n = (n & m1 ) + ((n >>  1) & m1 ); //put count of each  2 bits into those  2 bits   
            n = (n & m2 ) + ((n >>  2) & m2 ); //put count of each  4 bits into those  4 bits   
            n = (n & m4 ) + ((n >>  4) & m4 ); //put count of each  8 bits into those  8 bits   
            n = (n & m8 ) + ((n >>  8) & m8 ); //put count of each 16 bits into those 16 bits   
            n = (n & m16) + ((n >> 16) & m16); //put count of each 32 bits into those 32 bits   
            return n; 

    }
    +

    code

    int hammingWeight(uint32_t n) {
+        const uint32_t m1  = 0x55555555; //binary: 0101...  
+        const uint32_t m2  = 0x33333333; //binary: 00110011..  
+        const uint32_t m4  = 0x0f0f0f0f; //binary:  4 zeros,  4 ones ...  
+        const uint32_t m8  = 0x00ff00ff; //binary:  8 zeros,  8 ones ...  
+        const uint32_t m16 = 0x0000ffff; //binary: 16 zeros, 16 ones ...  
+        
+        n = (n & m1 ) + ((n >>  1) & m1 ); //put count of each  2 bits into those  2 bits   
+        n = (n & m2 ) + ((n >>  2) & m2 ); //put count of each  4 bits into those  4 bits   
+        n = (n & m4 ) + ((n >>  4) & m4 ); //put count of each  8 bits into those  8 bits   
+        n = (n & m8 ) + ((n >>  8) & m8 ); //put count of each 16 bits into those 16 bits   
+        n = (n & m16) + ((n >> 16) & m16); //put count of each 32 bits into those 32 bits   
+        return n; 
+
+}
    @@ -299,19 +307,19 @@
    Related Posts
    @@ -437,7 +445,7 @@
    -
    1. 1. Number of 1 Bits
      1. 1.1. Write a function that takes an unsigned integer and returns the number of ’1’ bits it has (also known as the Hamming weight). For example, the 32-bit integer ‘11’ has binary representation 00000000000000000000000000001011, so the function should return 3.
    2. 2. 分析
    3. 3. code
    +
    1. 1. Number of 1 Bits
      1. 1.1. Write a function that takes an unsigned integer and returns the number of ’1’ bits it has (also known as the Hamming weight). For example, the 32-bit integer ‘11’ has binary representation 00000000000000000000000000001011, so the function should return 3.
    2. 2. 分析
    3. 3. code
    diff --git a/2015/03/11/Reverse-Bits/index.html b/2015/03/11/Reverse-Bits/index.html index 42f5123dca..0bd33d953d 100644 --- a/2015/03/11/Reverse-Bits/index.html +++ b/2015/03/11/Reverse-Bits/index.html @@ -4,7 +4,7 @@ - + @@ -32,8 +32,9 @@ + - + @@ -229,13 +230,6 @@     - - - - - Edited on - - @@ -285,11 +279,21 @@
    -

    Reverse Bits

    Reverse bits of a given 32 bits unsigned integer.

    For example, given input 43261596 (represented in binary as 00000010100101000001111010011100), return 964176192 (represented in binary as 00111001011110000010100101000000).

    - +

    Reverse Bits

    Reverse bits of a given 32 bits unsigned integer.

    For example, given input 43261596 (represented in binary as 00000010100101000001111010011100), return 964176192 (represented in binary as 00111001011110000010100101000000).

    +

    Follow up:
    If this function is called many times, how would you optimize it?

    -

    code

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    class Solution {
    public:
        uint32_t reverseBits(uint32_t n) {
            n = ((n >> 1) & 0x55555555) | ((n & 0x55555555) << 1);
            n = ((n >> 2) & 0x33333333) | ((n & 0x33333333) << 2);
            n = ((n >> 4) & 0x0f0f0f0f) | ((n & 0x0f0f0f0f) << 4);
            n = ((n >> 8) & 0x00ff00ff) | ((n & 0x00ff00ff) << 8);
            n = ((n >> 16) & 0x0000ffff) | ((n & 0x0000ffff) << 16);
            return n;
        }
    };
    +

    code

    class Solution {
+public:
+    uint32_t reverseBits(uint32_t n) {
+        n = ((n >> 1) & 0x55555555) | ((n & 0x55555555) << 1);
+        n = ((n >> 2) & 0x33333333) | ((n & 0x33333333) << 2);
+        n = ((n >> 4) & 0x0f0f0f0f) | ((n & 0x0f0f0f0f) << 4);
+        n = ((n >> 8) & 0x00ff00ff) | ((n & 0x00ff00ff) << 8);
+        n = ((n >> 16) & 0x0000ffff) | ((n & 0x0000ffff) << 16);
+        return n;
+    }
+};
    @@ -306,10 +310,10 @@
    34_Search_for_a_Range
  • -
    add-two-number
    +
    Number of 1 Bits
  • -
    Number of 1 Bits
    +
    add-two-number
  • Path Sum
    diff --git a/2015/03/13/Reverse-Integer/index.html b/2015/03/13/Reverse-Integer/index.html index 71f1990105..10ebaf3802 100644 --- a/2015/03/13/Reverse-Integer/index.html +++ b/2015/03/13/Reverse-Integer/index.html @@ -4,7 +4,7 @@ - + @@ -32,8 +32,9 @@ + - + @@ -229,13 +230,6 @@ - - - - - Edited on - - @@ -285,14 +279,38 @@
    -

    Reverse Integer

    Reverse digits of an integer.

    Example1: x = 123, return 321
    Example2: x = -123, return -321

    - +

    Reverse Integer

    Reverse digits of an integer.

    Example1: x = 123, return 321
    Example2: x = -123, return -321

    +

    spoilers

    Have you thought about this?
    Here are some good questions to ask before coding. Bonus points for you if you have already thought through this!

    If the integer’s last digit is 0, what should the output be? ie, cases such as 10, 100.

    Did you notice that the reversed integer might overflow? Assume the input is a 32-bit integer, then the reverse of 1000000003 overflows. How should you handle such cases?

    For the purpose of this problem, assume that your function returns 0 when the reversed integer overflows.

    -

    code

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    class Solution {
    public:
        int reverse(int x) {

            int max = 1 << 31 - 1;
            int ret = 0;
            max = (max - 1) * 2 + 1;
            int min = 1 << 31;
            if(x < 0)
                while(x != 0){
                    if(ret < (min - x % 10) / 10)
                        return 0;
                    ret = ret * 10 + x % 10;
                    x = x / 10;
                }
            else
                while(x != 0){
                   if(ret > (max -x % 10) / 10)
                        return 0;
                    ret = ret * 10 + x % 10;
                    x = x / 10;
                }
            return ret;
        }
    };
    +

    code

    class Solution {
+public:
+    int reverse(int x) {
+
+        int max = 1 << 31 - 1;
+        int ret = 0;
+        max = (max - 1) * 2 + 1;
+        int min = 1 << 31;
+        if(x < 0)
+            while(x != 0){
+                if(ret < (min - x % 10) / 10)
+                    return 0;
+                ret = ret * 10 + x % 10;
+                x = x / 10;
+            }
+        else
+            while(x != 0){
+               if(ret > (max -x % 10) / 10)
+                    return 0;
+                ret = ret * 10 + x % 10;
+                x = x / 10;
+            }
+        return ret;
+    }
+};
    @@ -309,10 +327,10 @@
    34_Search_for_a_Range
  • -
    add-two-number
    +
    Number of 1 Bits
  • -
    Number of 1 Bits
    +
    add-two-number
  • Path Sum
    diff --git a/2015/04/14/Add-Two-Number/index.html b/2015/04/14/Add-Two-Number/index.html index 3fcf1fcd9b..17a327ba62 100644 --- a/2015/04/14/Add-Two-Number/index.html +++ b/2015/04/14/Add-Two-Number/index.html @@ -4,7 +4,7 @@ - + @@ -32,8 +32,9 @@ + - + @@ -229,13 +230,6 @@ - - - - - Edited on - - @@ -287,12 +281,95 @@

    problem

    You are given two linked lists representing two non-negative numbers. The digits are stored in reverse order and each of their nodes contain a single digit. Add the two numbers and return it as a linked list.

    Input:(2 -> 4 -> 3) + (5 -> 6 -> 4)
    Output: 7 -> 0 -> 8

    -

    分析（不用英文装逼了）
    这个代码是抄来的，链接原作是这位大大。

    - +

    分析（不用英文装逼了）
    这个代码是抄来的，链接原作是这位大大。

    +

    一开始没看懂题，后来发现是要进位的，自己写的时候想把长短不同时长的串接到结果
    串的后面，试了下因为进位会有些问题比较难搞定，这样的话就是在其中一个为空的
    时候还是会循环操作，在链表太大的时候可能会有问题，就这样（逃
    原来是有个小错误没发现，改进后的代码也AC了，棒棒哒！

    -

    正确代码

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    /**
     * Definition for singly-linked list.
     * struct ListNode {
     *     int val;
     *     ListNode *next;
     *     ListNode(int x) : val(x), next(NULL) {}
     * };
     */
    class Solution {
    public:
        ListNode *addTwoNumbers(ListNode *l1, ListNode *l2) {
            ListNode dummy(0);
            ListNode* p = &dummy;

            int cn = 0;
            while(l1 || l2){
                int val = cn + (l1 ? l1->val : 0) + (l2 ? l2->val : 0);
                cn = val / 10;
                val = val % 10;
                p->next = new ListNode(val);
                p = p->next;
                if(l1){
                    l1 = l1->next;
                }
                if(l2){
                    l2 = l2->next;
                }
            }
            if(cn != 0){
                p->next = new ListNode(cn);
                p = p->next;
            }
            return dummy.next;
        }
    };
    - -

    失败的代码

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    /**
     * Definition for singly-linked list.
     * struct ListNode {
     *     int val;
     *     ListNode *next;
     *     ListNode(int x) : val(x), next(NULL) {}
     * };
     */
    class Solution {
    public:
        ListNode *addTwoNumbers(ListNode *l1, ListNode *l2) {
            ListNode dummy(0);
            ListNode* p = &dummy;

            int cn = 0;
            int flag = 0;
            while(l1 || l2){
                int val = cn + (l1 ? l1->val : 0) + (l2 ? l2->val : 0);
                cn = val / 10;
                val = val % 10;
                p->next = new ListNode(val);
                p = p->next;
                if(!l1 && cn == 0){
                    flag = 1;
                    break;
                }
                if(!l2 && cn == 0){
                    flag = 1;
                    break;
                }
                if(l1){
                    l1 = l1->next;
                }
                if(l2){
                    l2 = l2->next;
                }
            }
            if(!l1 && cn == 0 && flag == 1){
                p->next = l2->next;
            }
            if(!l2 && cn == 0 && flag == 1){
                p->next = l1->next;
            }
            if(cn != 0){
                p->next = new ListNode(cn);
                p = p->next;
            }
            return dummy.next;
        }
    };
    +

    正确代码

    /**
+ * Definition for singly-linked list.
+ * struct ListNode {
+ *     int val;
+ *     ListNode *next;
+ *     ListNode(int x) : val(x), next(NULL) {}
+ * };
+ */
+class Solution {
+public:
+    ListNode *addTwoNumbers(ListNode *l1, ListNode *l2) {
+        ListNode dummy(0);
+        ListNode* p = &dummy;
+
+        int cn = 0;
+        while(l1 || l2){
+            int val = cn + (l1 ? l1->val : 0) + (l2 ? l2->val : 0);
+            cn = val / 10;
+            val = val % 10;
+            p->next = new ListNode(val);
+            p = p->next;
+            if(l1){
+                l1 = l1->next;
+            }
+            if(l2){
+                l2 = l2->next;
+            }
+        }
+        if(cn != 0){
+            p->next = new ListNode(cn);
+            p = p->next;
+        }
+        return dummy.next;
+    }
+};
    + +

    失败的代码

    /**
+ * Definition for singly-linked list.
+ * struct ListNode {
+ *     int val;
+ *     ListNode *next;
+ *     ListNode(int x) : val(x), next(NULL) {}
+ * };
+ */
+class Solution {
+public:
+    ListNode *addTwoNumbers(ListNode *l1, ListNode *l2) {
+        ListNode dummy(0);
+        ListNode* p = &dummy;
+
+        int cn = 0;
+        int flag = 0;
+        while(l1 || l2){
+            int val = cn + (l1 ? l1->val : 0) + (l2 ? l2->val : 0);
+            cn = val / 10;
+            val = val % 10;
+            p->next = new ListNode(val);
+            p = p->next;
+            if(!l1 && cn == 0){
+                flag = 1;
+                break;
+            }
+            if(!l2 && cn == 0){
+                flag = 1;
+                break;
+            }
+            if(l1){
+                l1 = l1->next;
+            }
+            if(l2){
+                l2 = l2->next;
+            }
+        }
+        if(!l1 && cn == 0 && flag == 1){
+            p->next = l2->next;
+        }
+        if(!l2 && cn == 0 && flag == 1){
+            p->next = l1->next;
+        }
+        if(cn != 0){
+            p->next = new ListNode(cn);
+            p = p->next;
+        }
+        return dummy.next;
+    }
+};
    @@ -303,7 +380,7 @@
    Related Posts
    • -
      Number of 1 Bits
      +
      Path Sum
    • 34_Search_for_a_Range
      @@ -441,7 +518,7 @@
      -
      1. 1. problem
      2. 2. 正确代码
      3. 3. 失败的代码
      +
      1. 1. problem
      2. 2. 正确代码
      3. 3. 失败的代码
      diff --git a/2015/04/15/Leetcode-No-3/index.html b/2015/04/15/Leetcode-No-3/index.html index 65b512008e..bfaa575b1e 100644 --- a/2015/04/15/Leetcode-No-3/index.html +++ b/2015/04/15/Leetcode-No-3/index.html @@ -4,7 +4,7 @@ - + @@ -26,14 +26,15 @@ var CONFIG = {"hostname":"nicksxs.me","root":"/","scheme":"Pisces","version":"7.8.0","exturl":false,"sidebar":{"position":"left","display":"post","padding":18,"offset":12,"onmobile":false},"copycode":{"enable":true,"show_result":false,"style":null},"back2top":{"enable":true,"sidebar":false,"scrollpercent":false},"bookmark":{"enable":false,"color":"#222","save":"auto"},"fancybox":true,"mediumzoom":false,"lazyload":true,"pangu":false,"comments":{"style":"tabs","active":null,"storage":true,"lazyload":false,"nav":null},"algolia":{"hits":{"per_page":10},"labels":{"input_placeholder":"Search for Posts","hits_empty":"We didn't find any results for the search: ${query}","hits_stats":"${hits} results found in ${time} ms"}},"localsearch":{"enable":false,"trigger":"auto","top_n_per_article":1,"unescape":false,"preload":false},"motion":{"enable":true,"async":false,"transition":{"post_block":"fadeIn","post_header":"slideDownIn","post_body":"slideDownIn","coll_header":"slideLeftIn","sidebar":"slideUpIn"}}}; - + - + + - + @@ -229,13 +230,6 @@ - - - - - Edited on - - @@ -285,11 +279,22 @@
      -

      *Longest Substring Without Repeating Characters *

      - +

      **Longest Substring Without Repeating Characters **

      +

      description

      Given a string, find the length of the longest substring without repeating characters.
      For example, the longest substring without repeating letters for “abcabcbb” is “abc”,
      which the length is 3. For “bbbbb” the longest substring is “b”, with the length of 1.

      -

      分析

      源码这次是参考了这个代码，
      tail 表示的当前子串的起始点位置，tail从-1开始就包括的串的长度是1的边界。其实我
      也是猜的（逃

      -
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      int ct[256];
          memset(ct, -1, sizeof(ct));
      	int tail = -1;
      	int max = 0;
      	for (int i = 0; i < s.size(); i++){
      		if (ct[s[i]] > tail)
      			tail = ct[s[i]];
      		if (i - tail > max)
      			max = i - tail;
      		ct[s[i]] = i;
      	}
      	return max;
      +

      分析

      源码这次是参考了这个代码，
      tail 表示的当前子串的起始点位置，tail从-1开始就包括的串的长度是1的边界。其实我
      也是猜的（逃

      +
      int ct[256];
+    memset(ct, -1, sizeof(ct));
+	int tail = -1;
+	int max = 0;
+	for (int i = 0; i < s.size(); i++){
+		if (ct[s[i]] > tail)
+			tail = ct[s[i]];
+		if (i - tail > max)
+			max = i - tail;
+		ct[s[i]] = i;
+	}
+	return max;
      @@ -300,7 +305,7 @@
      Related Posts
      • -
        Number of 1 Bits
        +
        Path Sum
      • 34_Search_for_a_Range
        @@ -438,7 +443,7 @@
        -
        1. 1. description
        2. 2. 分析
        +
        1. 1. description
        2. 2. 分析
        diff --git a/2015/06/22/invert-binary-tree/index.html b/2015/06/22/invert-binary-tree/index.html index 85a37a57f2..5349291562 100644 --- a/2015/06/22/invert-binary-tree/index.html +++ b/2015/06/22/invert-binary-tree/index.html @@ -4,7 +4,7 @@ - + @@ -26,14 +26,15 @@ var CONFIG = {"hostname":"nicksxs.me","root":"/","scheme":"Pisces","version":"7.8.0","exturl":false,"sidebar":{"position":"left","display":"post","padding":18,"offset":12,"onmobile":false},"copycode":{"enable":true,"show_result":false,"style":null},"back2top":{"enable":true,"sidebar":false,"scrollpercent":false},"bookmark":{"enable":false,"color":"#222","save":"auto"},"fancybox":true,"mediumzoom":false,"lazyload":true,"pangu":false,"comments":{"style":"tabs","active":null,"storage":true,"lazyload":false,"nav":null},"algolia":{"hits":{"per_page":10},"labels":{"input_placeholder":"Search for Posts","hits_empty":"We didn't find any results for the search: ${query}","hits_stats":"${hits} results found in ${time} ms"}},"localsearch":{"enable":false,"trigger":"auto","top_n_per_article":1,"unescape":false,"preload":false},"motion":{"enable":true,"async":false,"transition":{"post_block":"fadeIn","post_header":"slideDownIn","post_body":"slideDownIn","coll_header":"slideLeftIn","sidebar":"slideUpIn"}}}; - + - + + - + @@ -229,13 +230,6 @@ - - - - - Edited on - - @@ -290,16 +284,39 @@ / \ 2 7 / \ / \ -1 3 6 9

        to

        +1 3 6 9 + +

        to

             4
    /   \
   7     2
  / \   / \
-9   6 3   1

        Trivia:
        This problem was inspired by this original tweet by Max Howell:

        +9 6 3 1 + +

        Trivia:
        This problem was inspired by this original tweet by Max Howell:

        Google: 90% of our engineers use the software you wrote (Homebrew),
        but you can’t invert a binary tree on a whiteboard so fuck off.

        -
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        /**
         * Definition for a binary tree node.
         * struct TreeNode {
         *     int val;
         *     TreeNode *left;
         *     TreeNode *right;
         *     TreeNode(int x) : val(x), left(NULL), right(NULL) {}
         * };
         */
        class Solution {
        public:
            TreeNode* invertTree(TreeNode* root) {
                if(root == NULL) return root;
                TreeNode* temp;
                temp = invertTree(root->left);
                root->left = invertTree(root->right);
                root->right = temp;
                return root;
            }
        };
        +
        /**
+ * Definition for a binary tree node.
+ * struct TreeNode {
+ *     int val;
+ *     TreeNode *left;
+ *     TreeNode *right;
+ *     TreeNode(int x) : val(x), left(NULL), right(NULL) {}
+ * };
+ */
+class Solution {
+public:
+    TreeNode* invertTree(TreeNode* root) {
+        if(root == NULL) return root;
+        TreeNode* temp;
+        temp = invertTree(root->left);
+        root->left = invertTree(root->right);
+        root->right = temp;
+        return root;
+    }
+};
        @@ -315,10 +332,10 @@
        34_Search_for_a_Range
      • -
        add-two-number
        +
        Number of 1 Bits
      • -
        Number of 1 Bits
        +
        add-two-number
      • Path Sum
        diff --git a/2016/07/13/swoole-websocket-test/index.html b/2016/07/13/swoole-websocket-test/index.html index eaa9c8f0df..443c561b69 100644 --- a/2016/07/13/swoole-websocket-test/index.html +++ b/2016/07/13/swoole-websocket-test/index.html @@ -4,7 +4,7 @@ - + @@ -32,9 +32,10 @@ + - + @@ -231,13 +232,6 @@ - - - - - Edited on - - @@ -287,28 +281,113 @@
        -

        玩一下swoole的websocket

        WebSocket是HTML5开始提供的一种在单个TCP连接上进行全双工通讯的协议。WebSocket通信协议于2011年被IETF定为标准RFC 6455，WebSocketAPI被W3C定为标准。
        ,在web私信，im等应用较多。背景和优缺点可以参看wiki。

        -

        环境准备

        因为swoole官方还不支持windows，所以需要装下linux,之前都是用ubuntu，
        这次就试一下centos7，还是满好看的，虽然虚拟机会默认最小安装，需要在安装
        时自己选择带gnome的，当然最小安装也是可以的，只是最后需要改下防火墙。
        然后是装下PHP，Nginx什么的，我是用Oneinstack，可以按需安装
        给做这个的大大点个赞。

        - +

        玩一下swoole的websocket

        WebSocket是HTML5开始提供的一种在单个TCP连接上进行全双工通讯的协议。WebSocket通信协议于2011年被IETF定为标准RFC 6455，WebSocketAPI被W3C定为标准。
        ,在web私信，im等应用较多。背景和优缺点可以参看wiki。

        +

        环境准备

        因为swoole官方还不支持windows，所以需要装下linux,之前都是用ubuntu，
        这次就试一下centos7，还是满好看的，虽然虚拟机会默认最小安装，需要在安装
        时自己选择带gnome的，当然最小安装也是可以的，只是最后需要改下防火墙。
        然后是装下PHP，Nginx什么的，我是用Oneinstack，可以按需安装
        给做这个的大大点个赞。

        +

        swoole

        1.install via pecl

        -
        1
        pecl install swoole
        +
        pecl install swoole

        2.install from source

        -
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        sudo apt-get install php5-dev
        git clone https://github.com/swoole/swoole-src.git
        cd swoole-src
        phpize
        ./configure
        make && make install
        - +
        sudo apt-get install php5-dev
+git clone https://github.com/swoole/swoole-src.git
+cd swoole-src
+phpize
+./configure
+make && make install

        3.add extension

        -
        1
        extension = swoole.so
        +
        extension = swoole.so

        4.test extension

        -
        1
        php -m | grep swoole
        +
        php -m | grep swoole

        如果存在就代表安装成功啦

        -

        Exec

        实现代码看了这位仁兄的代码

        +

        Exec

        实现代码看了这位仁兄的代码

        还是贴一下代码
        服务端：

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        //创建websocket服务器对象，监听0.0.0.0:9502端口
        $ws = new swoole_websocket_server("0.0.0.0", 9502);

        //监听WebSocket连接打开事件
        $ws->on('open', function ($ws, $request) {
            $fd[] = $request->fd;
            $GLOBALS['fd'][] = $fd;
            //区别下当前用户
            $ws->push($request->fd, "hello user{$request->fd}, welcome\n"); 
        });

        //监听WebSocket消息事件
        $ws->on('message', function ($ws, $frame) {
            $msg =  'from'.$frame->fd.":{$frame->data}\n";

            foreach($GLOBALS['fd'] as $aa){
                foreach($aa as $i){
                    if($i != $frame->fd) {
                        # code...
                        $ws->push($i,$msg);
                    }
                }
            }
        });

        //监听WebSocket连接关闭事件
        $ws->on('close', function ($ws, $fd) {
            echo "client-{$fd} is closed\n";
        });

        $ws->start();
        +
        //创建websocket服务器对象，监听0.0.0.0:9502端口
+$ws = new swoole_websocket_server("0.0.0.0", 9502);
+
+//监听WebSocket连接打开事件
+$ws->on('open', function ($ws, $request) {
+    $fd[] = $request->fd;
+    $GLOBALS['fd'][] = $fd;
+    //区别下当前用户
+    $ws->push($request->fd, "hello user{$request->fd}, welcome\n"); 
+});
+
+//监听WebSocket消息事件
+$ws->on('message', function ($ws, $frame) {
+    $msg =  'from'.$frame->fd.":{$frame->data}\n";
+
+    foreach($GLOBALS['fd'] as $aa){
+        foreach($aa as $i){
+            if($i != $frame->fd) {
+                # code...
+                $ws->push($i,$msg);
+            }
+        }
+    }
+});
+
+//监听WebSocket连接关闭事件
+$ws->on('close', function ($ws, $fd) {
+    echo "client-{$fd} is closed\n";
+});
+
+$ws->start();

        客户端：

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        <!DOCTYPE html>
        <html lang="en">
        <head>
            <meta charset="UTF-8">
            <title>Title</title>
        </head>
        <body>
        <div id="msg"></div>
        <input type="text" id="text">
        <input type="submit" value="发送数据" onclick="song()">
        </body>
        <script>
            var msg = document.getElementById("msg");
            var wsServer = 'ws://0.0.0.0:9502';
            //调用websocket对象建立连接：
            //参数：ws/wss(加密)：//ip:port （字符串）
            var websocket = new WebSocket(wsServer);
            //onopen监听连接打开
            websocket.onopen = function (evt) {
                //websocket.readyState 属性：
                /*
                CONNECTING    0    The connection is not yet open.
                OPEN    1    The connection is open and ready to communicate.
                CLOSING    2    The connection is in the process of closing.
                CLOSED    3    The connection is closed or couldn't be opened.
                */
                msg.innerHTML = websocket.readyState;
            };

            function song(){
                var text = document.getElementById('text').value;
                document.getElementById('text').value = '';
                //向服务器发送数据
                websocket.send(text);
            }
              //监听连接关闭
        //    websocket.onclose = function (evt) {
        //        console.log("Disconnected");
        //    };

            //onmessage 监听服务器数据推送
            websocket.onmessage = function (evt) {
                msg.innerHTML += evt.data +'<br>';
        //        console.log('Retrieved data from server: ' + evt.data);
            };
        //监听连接错误信息
        //    websocket.onerror = function (evt, e) {
        //        console.log('Error occured: ' + evt.data);
        //    };

        </script>
        </html>
        +
        <!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <title>Title</title>
+</head>
+<body>
+<div id="msg"></div>
+<input type="text" id="text">
+<input type="submit" value="发送数据" onclick="song()">
+</body>
+<script>
+    var msg = document.getElementById("msg");
+    var wsServer = 'ws://0.0.0.0:9502';
+    //调用websocket对象建立连接：
+    //参数：ws/wss(加密)：//ip:port （字符串）
+    var websocket = new WebSocket(wsServer);
+    //onopen监听连接打开
+    websocket.onopen = function (evt) {
+        //websocket.readyState 属性：
+        /*
+        CONNECTING    0    The connection is not yet open.
+        OPEN    1    The connection is open and ready to communicate.
+        CLOSING    2    The connection is in the process of closing.
+        CLOSED    3    The connection is closed or couldn't be opened.
+        */
+        msg.innerHTML = websocket.readyState;
+    };
+
+    function song(){
+        var text = document.getElementById('text').value;
+        document.getElementById('text').value = '';
+        //向服务器发送数据
+        websocket.send(text);
+    }
+      //监听连接关闭
+//    websocket.onclose = function (evt) {
+//        console.log("Disconnected");
+//    };
+
+    //onmessage 监听服务器数据推送
+    websocket.onmessage = function (evt) {
+        msg.innerHTML += evt.data +'<br>';
+//        console.log('Retrieved data from server: ' + evt.data);
+    };
+//监听连接错误信息
+//    websocket.onerror = function (evt, e) {
+//        console.log('Error occured: ' + evt.data);
+//    };
+
+</script>
+</html>

        做了个循环，将当前用户的消息发送给同时在线的其他用户，比较简陋，如下图
        user1:
        NH}()5}1DTLTKZ%HUQ`4L(V.png](https://ooo.0o0.ooo/2016/07/13/578665c07d94c.png) user2: @@ -445,7 +524,7 @@ user3: <!--noindex--> <div class= -

        1. 1. 玩一下swoole的websocket
        2. 2. 环境准备
      • swoole
      • Exec +
        1. 1. 玩一下swoole的websocket
        2. 2. 环境准备
      • swoole
      • Exec diff --git a/2016/08/14/34-Search-for-a-Range/index.html b/2016/08/14/34-Search-for-a-Range/index.html index 3652f3088a..17cf5fc697 100644 --- a/2016/08/14/34-Search-for-a-Range/index.html +++ b/2016/08/14/34-Search-for-a-Range/index.html @@ -4,7 +4,7 @@ - + @@ -32,8 +32,9 @@ + - + @@ -229,13 +230,6 @@ - - - - - Edited on - - @@ -285,13 +279,41 @@
        -

        question

        34. Search for a Range

        Original Page

        +

        question

        34. Search for a Range

        Original Page

        Given a sorted array of integers, find the starting and ending position of a given target value.

        Your algorithm’s runtime complexity must be in the order of O(log n).

        If the target is not found in the array, return [-1, -1].

        For example,
        Given [5, 7, 7, 8, 8, 10] and target value 8,
        return [3, 4].

        -

        analysis

        一开始就想到了二分查找，但是原来做二分查找的时候一般都是找到确定的那个数就完成了，
        这里的情况比较特殊，需要找到整个区间，所以需要两遍查找，并且一个是找到小于target
        的最大索引，一个是找到大于target的最大索引，代码参考leetcode discuss,这位仁
        兄也做了详细的分析解释。

        -

        code

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        class Solution {
        public:
            vector<int> searchRange(vector<int>& nums, int target) {
                vector<int> ret(2, -1);
                int i = 0, j = nums.size() - 1;
                int mid;
                while(i < j){
                    mid = (i + j) / 2;
                    if(nums[mid] < target) i = mid + 1;
                    else j = mid;
                }
                if(nums[i] != target) return ret;
                else {
                    ret[0] = i;
                    if((i+1) < (nums.size() - 1) && nums[i+1] > target){
                        ret[1] = i;
                        return ret;
                    }
                }   //一点小优化
                j = nums.size() - 1;
                while(i < j){
                    mid = (i + j) / 2 + 1;
                    if(nums[mid] > target) j = mid - 1;
                    else i = mid;
                }
                ret[1] = j;
                return ret;
            }
        };
        +

        analysis

        一开始就想到了二分查找，但是原来做二分查找的时候一般都是找到确定的那个数就完成了，
        这里的情况比较特殊，需要找到整个区间，所以需要两遍查找，并且一个是找到小于target
        的最大索引，一个是找到大于target的最大索引，代码参考leetcode discuss,这位仁
        兄也做了详细的分析解释。

        +

        code

        class Solution {
+public:
+    vector<int> searchRange(vector<int>& nums, int target) {
+        vector<int> ret(2, -1);
+        int i = 0, j = nums.size() - 1;
+        int mid;
+        while(i < j){
+            mid = (i + j) / 2;
+            if(nums[mid] < target) i = mid + 1;
+            else j = mid;
+        }
+        if(nums[i] != target) return ret;
+        else {
+            ret[0] = i;
+            if((i+1) < (nums.size() - 1) && nums[i+1] > target){
+                ret[1] = i;
+                return ret;
+            }
+        }   //一点小优化
+        j = nums.size() - 1;
+        while(i < j){
+            mid = (i + j) / 2 + 1;
+            if(nums[mid] > target) j = mid - 1;
+            else i = mid;
+        }
+        ret[1] = j;
+        return ret;
+    }
+};
        @@ -301,7 +323,7 @@
        Related Posts
        • -
          Number of 1 Bits
          +
          Path Sum
        • add-two-number
          diff --git a/2016/08/14/docker-mysql-cluster/index.html b/2016/08/14/docker-mysql-cluster/index.html index 9c309a11f1..1f8fbd1c86 100644 --- a/2016/08/14/docker-mysql-cluster/index.html +++ b/2016/08/14/docker-mysql-cluster/index.html @@ -4,7 +4,7 @@ - + @@ -32,10 +32,11 @@ + - + @@ -232,13 +233,6 @@ - - - - - Edited on - - @@ -288,13 +282,21 @@
          -

          docker-mysql-cluster

          基于docker搭了个mysql集群，稍微记一下，
          首先是新建mysql主库容

          docker run -d -e MYSQL_ROOT_PASSWORD=admin --name mysql-master -p 3307:3306 mysql:latest
          -d表示容器运行在后台，-e表示设置环境变量，即MYSQL_ROOT_PASSWORD=admin,设置了mysql的root密码，
          --name表示容器名，-p表示端口映射，将内部mysql:3306映射为外部的3307，最后的mysql:latest表示镜像名
          此外还可以用-v /local_path/my-master.cnf:/etc/mysql/my.cnf来映射配置文件
          然后同理启动从库
          docker run -d -e MYSQL_ROOT_PASSWORD=admin --name mysql-slave -p 3308:3306 mysql:latest
          然后进入主库改下配置文件
          docker-enter mysql-master如果无法进入就用docker ps -a看下容器是否在正常运行，如果status显示
          未正常运行，则用docker logs mysql-master看下日志哪里出错了。
          进入容器后，我这边使用的镜像的mysqld配置文件是在/etc/mysql下面，这个最新版本的mysql的配置文件包含
          三部分，/etc/mysql/my.cnf和/etc/mysql/conf.d/mysql.cnf，还有/etc/mysql/mysql.conf.d/mysqld.cnf
          这里需要改的是最后一个，加上

          -
          1
          2
          log-bin = mysql-bin
          server_id = 1
          +

          docker-mysql-cluster

          基于docker搭了个mysql集群，稍微记一下，
          首先是新建mysql主库容

          docker run -d -e MYSQL_ROOT_PASSWORD=admin --name mysql-master -p 3307:3306 mysql:latest
          -d表示容器运行在后台，-e表示设置环境变量，即MYSQL_ROOT_PASSWORD=admin,设置了mysql的root密码，
          --name表示容器名，-p表示端口映射，将内部mysql:3306映射为外部的3307，最后的mysql:latest表示镜像名
          此外还可以用-v /local_path/my-master.cnf:/etc/mysql/my.cnf来映射配置文件
          然后同理启动从库
          docker run -d -e MYSQL_ROOT_PASSWORD=admin --name mysql-slave -p 3308:3306 mysql:latest
          然后进入主库改下配置文件
          docker-enter mysql-master如果无法进入就用docker ps -a看下容器是否在正常运行，如果status显示
          未正常运行，则用docker logs mysql-master看下日志哪里出错了。
          进入容器后，我这边使用的镜像的mysqld配置文件是在/etc/mysql下面，这个最新版本的mysql的配置文件包含
          三部分，/etc/mysql/my.cnf和/etc/mysql/conf.d/mysql.cnf，还有/etc/mysql/mysql.conf.d/mysqld.cnf
          这里需要改的是最后一个，加上

          +
          log-bin = mysql-bin
+server_id = 1

          保存后退出容器重启主库容器，然后进入从库更改相同文件，

          -
          1
          2
          log-bin = mysql-bin
          server_id = 2
          -

          主从配置

          同样退出重启容器，然后是配置主从，首先进入主库，用命令mysql -u root -pxxxx进入mysql，然后赋予一个同步
          权限GRANT REPLICATION SLAVE ON *.* to 'backup'@'%' identified by '123456';还是同样说明下，ON .表示了数
          据库全部的权限，如果要指定数据库/表的话可以使用类似testDb/testTable，然后是'backup'@'%'表示给予同步
          权限的用户名及其主机ip，%表示不限制ip，当然如果有防火墙的话还是会有限制的，最后的identified by '123456'
          表示同步用户的密码，然后就查看下主库的状态信息show master status，如下图：
          9G5FE[9%@7%G(B`Q7]E)5@R.png
          把file跟position记下来，然后再开一个terminal，进入从库容器，登陆mysql，然后设置主库

          -
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          7
          change master to
          master_host='xxx.xxx.xxx.xxx',   //如果主从库的容器都在同一个宿主机上，这里的ip是docker容器的ip
          master_user='backup',            //就是上面的赋予权限的用户
          master_password='123456',
          master_log_file='mysql-bin.000004',  //主库中查看到的file
          master_log_pos=312,                  //主库中查看到的position
          master_port=3306;                    //如果是同一宿主机，这里使用真实的3306端口，3308及主库的3307是给外部连接使用的
          -

          通过docker-ip mysql-master可以查看容器的ip
          S(GP)P(M$N3~N1764@OW3E0.png
          这里有一点是要注意的，也是我踩的坑，就是如果是同一宿主机下两个mysql容器互联，我这里只能通过docker-ip和真实
          的3306端口能够连接成功。
          本文参考了这位同学的文章

          +
          log-bin = mysql-bin
+server_id = 2
          +

          主从配置

          同样退出重启容器，然后是配置主从，首先进入主库，用命令mysql -u root -pxxxx进入mysql，然后赋予一个同步
          权限GRANT REPLICATION SLAVE ON *.* to 'backup'@'%' identified by '123456';还是同样说明下，ON *.*表示了数
          据库全部的权限，如果要指定数据库/表的话可以使用类似testDb/testTable，然后是'backup'@'%'表示给予同步
          权限的用户名及其主机ip，%表示不限制ip，当然如果有防火墙的话还是会有限制的，最后的identified by '123456'
          表示同步用户的密码，然后就查看下主库的状态信息show master status，如下图：
          9G5FE[9%@7%G(B`Q7]E)5@R.png
          把file跟position记下来，然后再开一个terminal，进入从库容器，登陆mysql，然后设置主库

          +
          change master to
+master_host='xxx.xxx.xxx.xxx',   //如果主从库的容器都在同一个宿主机上，这里的ip是docker容器的ip
+master_user='backup',            //就是上面的赋予权限的用户
+master_password='123456',
+master_log_file='mysql-bin.000004',  //主库中查看到的file
+master_log_pos=312,                  //主库中查看到的position
+master_port=3306;                    //如果是同一宿主机，这里使用真实的3306端口，3308及主库的3307是给外部连接使用的
          +

          通过docker-ip mysql-master可以查看容器的ip
          S(GP)P(M$N3~N1764@OW3E0.png
          这里有一点是要注意的，也是我踩的坑，就是如果是同一宿主机下两个mysql容器互联，我这里只能通过docker-ip和真实
          的3306端口能够连接成功。
          本文参考了这位同学的文章

          @@ -440,7 +442,7 @@
          -
          1. 1. docker-mysql-cluster
          2. 2. 主从配置
          +
          1. 1. docker-mysql-cluster
          2. 2. 主从配置
          diff --git a/2016/09/29/binary-watch/index.html b/2016/09/29/binary-watch/index.html index 1b7b04db1b..e2d62cd00e 100644 --- a/2016/09/29/binary-watch/index.html +++ b/2016/09/29/binary-watch/index.html @@ -4,7 +4,7 @@ - + @@ -32,9 +32,10 @@ + - + @@ -231,13 +232,6 @@           - - - - - Edited on - - @@ -289,17 +283,31 @@

          problem

          A binary watch has 4 LEDs on the top which represent the hours (0-11), and the 6 LEDs on the bottom represent the minutes (0-59).

          Each LED represents a zero or one, with the least significant bit on the right.

          -

          +

          For example, the above binary watch reads “3:25”.

          Given a non-negative integer n which represents the number of LEDs that are currently on, return all possible times the watch could represent.

          -

          Example:

          1
          2
          Input: n = 1
          Return: ["1:00", "2:00", "4:00", "8:00", "0:01", "0:02", "0:04", "0:08", "0:16", "0:32"]
          +

          Example:

          Input: n = 1
+Return: ["1:00", "2:00", "4:00", "8:00", "0:01", "0:02", "0:04", "0:08", "0:16", "0:32"]

          Note:

          • The order of output does not matter.
          • The hour must not contain a leading zero, for example “01:00” is not valid, it should be “1:00”.
          • The minute must be consist of two digits and may contain a leading zero, for example “10:2” is not valid, it should be “10:02”.
          -

          题解

          又是参（chao）考（xi）别人的代码，嗯，就是这么不要脸，链接

          -

          Code

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          14
          class Solution {
          public:
              vector<string> readBinaryWatch(int num) {
                  vector<string> res;
                  for (int h = 0; h < 12; ++h) {
                      for (int m = 0; m < 60; ++m) {
                          if (bitset<10>((h << 6) + m).count() == num) {
                              res.push_back(to_string(h) + (m < 10 ? ":0" : ":") + to_string(m));
                          }
                      }
                  }
                  return res;
              }
          };
          +

          题解

          又是参（chao）考（xi）别人的代码，嗯，就是这么不要脸，链接

          +

          Code

          class Solution {
+public:
+    vector<string> readBinaryWatch(int num) {
+        vector<string> res;
+        for (int h = 0; h < 12; ++h) {
+            for (int m = 0; m < 60; ++m) {
+                if (bitset<10>((h << 6) + m).count() == num) {
+                    res.push_back(to_string(h) + (m < 10 ? ":0" : ":") + to_string(m));
+                }
+            }
+        }
+        return res;
+    }
+};
          @@ -315,10 +323,10 @@
          34_Search_for_a_Range
        • -
          add-two-number
          +
          Number of 1 Bits
        • -
          Number of 1 Bits
          +
          add-two-number
        • Path Sum
          @@ -447,7 +455,7 @@
          -
          1. 1. problem
            1. 1.1. Example:
            2. 1.2. Note:
          2. 2. 题解
            1. 2.1. Code
          +
          1. 1. problem
            1. 1.1. Example:
            2. 1.2. Note:
          2. 2. 题解
            1. 2.1. Code
          diff --git a/2016/10/11/minimum-size-subarray-sum-209/index.html b/2016/10/11/minimum-size-subarray-sum-209/index.html index c77a0e69c9..951139fd7d 100644 --- a/2016/10/11/minimum-size-subarray-sum-209/index.html +++ b/2016/10/11/minimum-size-subarray-sum-209/index.html @@ -4,7 +4,7 @@ - + @@ -32,8 +32,9 @@ + - + @@ -229,13 +230,6 @@ - - - - - Edited on - - @@ -287,8 +281,30 @@

          problem

          Given an array of n positive integers and a positive integer s, find the minimal length of a subarray of which the sum ≥ s. If there isn’t one, return 0 instead.

          For example, given the array [2,3,1,2,4,3] and s = 7,
          the subarray [4,3] has the minimal length under the problem constraint.

          -

          题解

          参考，滑动窗口，跟之前Data Structure课上的online算法有点像，链接

          -

          Code

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          class Solution {
          public:
              int minSubArrayLen(int s, vector<int>& nums) {
                  int len = nums.size();
                  if(len == 0) return 0;
                  int minlen = INT_MAX;
                  int sum = 0;
                  
                  int left = 0;
                  int right = -1;
                  while(right < len)
                  {
                      while(sum < s && right < len)
                          sum += nums[++right];
                      if(sum >= s)
                      {
                          minlen = minlen < right - left + 1 ? minlen : right - left + 1;
                          sum -= nums[left++];
                      }
                  }
                  return minlen > len ? 0 : minlen;
              }
          };
          +

          题解

          参考，滑动窗口，跟之前Data Structure课上的online算法有点像，链接

          +

          Code

          class Solution {
+public:
+    int minSubArrayLen(int s, vector<int>& nums) {
+        int len = nums.size();
+        if(len == 0) return 0;
+        int minlen = INT_MAX;
+        int sum = 0;
+        
+        int left = 0;
+        int right = -1;
+        while(right < len)
+        {
+            while(sum < s && right < len)
+                sum += nums[++right];
+            if(sum >= s)
+            {
+                minlen = minlen < right - left + 1 ? minlen : right - left + 1;
+                sum -= nums[left++];
+            }
+        }
+        return minlen > len ? 0 : minlen;
+    }
+};
          @@ -305,10 +321,10 @@
          34_Search_for_a_Range
        • -
          add-two-number
          +
          Number of 1 Bits
        • -
          Number of 1 Bits
          +
          add-two-number
        • Path Sum
          @@ -437,7 +453,7 @@
          -
          1. 1. problem
            1. 1.1. 题解
            2. 1.2. Code
          +
          1. 1. problem
            1. 1.1. 题解
            2. 1.2. Code
          diff --git a/2016/10/12/summary-ranges-228/index.html b/2016/10/12/summary-ranges-228/index.html index d352b273b6..b7d898fd08 100644 --- a/2016/10/12/summary-ranges-228/index.html +++ b/2016/10/12/summary-ranges-228/index.html @@ -4,7 +4,7 @@ - + @@ -32,8 +32,9 @@ + - + @@ -229,13 +230,6 @@ - - - - - Edited on - - @@ -287,8 +281,22 @@

          problem

          Given a sorted integer array without duplicates, return the summary of its ranges.

          For example, given [0,1,2,4,5,7], return ["0->2","4->5","7"].

          -

          题解

          每一个区间的起点nums[i]加上j是否等于nums[i+j]
          参考

          -

          Code

          1
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          13
          14
          15
          class Solution {
          public:
              vector<string> summaryRanges(vector<int>& nums) {
                  int i = 0, j = 1, n;
                  vector<string> res;
                  n = nums.size();
                  while(i < n){
                      j = 1;
                      while(j < n && nums[i+j] - nums[i] == j) j++;
                      res.push_back(j <= 1 ? to_string(nums[i]) : to_string(nums[i]) + "->" + to_string(nums[i + j - 1]));
                      i += j;
                  }
                  return res;
              }
          };
          +

          题解

          每一个区间的起点nums[i]加上j是否等于nums[i+j]
          参考

          +

          Code

          class Solution {
+public:
+    vector<string> summaryRanges(vector<int>& nums) {
+        int i = 0, j = 1, n;
+        vector<string> res;
+        n = nums.size();
+        while(i < n){
+            j = 1;
+            while(j < n && nums[i+j] - nums[i] == j) j++;
+            res.push_back(j <= 1 ? to_string(nums[i]) : to_string(nums[i]) + "->" + to_string(nums[i + j - 1]));
+            i += j;
+        }
+        return res;
+    }
+};
          @@ -304,10 +312,10 @@
          34_Search_for_a_Range
        • -
          add-two-number
          +
          Number of 1 Bits
        • -
          Number of 1 Bits
          +
          add-two-number
        • Path Sum
          @@ -436,7 +444,7 @@
          -
          1. 1. problem
          2. 2. 题解
          3. 3. Code
          +
          1. 1. problem
          2. 2. 题解
          3. 3. Code
          diff --git a/2016/11/10/php-abstract-class-and-interface/index.html b/2016/11/10/php-abstract-class-and-interface/index.html index bcb0c229b6..b27c1c84d7 100644 --- a/2016/11/10/php-abstract-class-and-interface/index.html +++ b/2016/11/10/php-abstract-class-and-interface/index.html @@ -4,7 +4,7 @@ - + @@ -26,14 +26,15 @@ var CONFIG = {"hostname":"nicksxs.me","root":"/","scheme":"Pisces","version":"7.8.0","exturl":false,"sidebar":{"position":"left","display":"post","padding":18,"offset":12,"onmobile":false},"copycode":{"enable":true,"show_result":false,"style":null},"back2top":{"enable":true,"sidebar":false,"scrollpercent":false},"bookmark":{"enable":false,"color":"#222","save":"auto"},"fancybox":true,"mediumzoom":false,"lazyload":true,"pangu":false,"comments":{"style":"tabs","active":null,"storage":true,"lazyload":false,"nav":null},"algolia":{"hits":{"per_page":10},"labels":{"input_placeholder":"Search for Posts","hits_empty":"We didn't find any results for the search: ${query}","hits_stats":"${hits} results found in ${time} ms"}},"localsearch":{"enable":false,"trigger":"auto","top_n_per_article":1,"unescape":false,"preload":false},"motion":{"enable":true,"async":false,"transition":{"post_block":"fadeIn","post_header":"slideDownIn","post_body":"slideDownIn","coll_header":"slideLeftIn","sidebar":"slideUpIn"}}}; - + - + + - + @@ -228,13 +229,6 @@ - - - - - Edited on - - @@ -293,9 +287,38 @@
        • 类必须实现抽象类和接口里的抽象方法，不一定要实现抽象类的非抽象方法
        • 接口内不能定义变量，但是可以定义常量
        -

        示例代码

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        28
        <?php
        interface int1{
            const INTER1 = 111;
            function inter1();
        }
        interface int2{
            const INTER1 = 222;
            function inter2();
        }
        abstract class abst1{
            public function abstr1(){
                echo 1111;
            }
            abstract function abstra1(){
                echo 'ahahahha';
            }
        }
        abstract class abst2{
            public function abstr2(){
                echo 1111;
            }
            abstract function abstra2();
        }
        class normal1 extends abst1{
            protected function abstr2(){
                echo 222;
            }
        }
        - -

        result

        1
        2
        3
        PHP Fatal error:  Abstract function abst1::abstra1() cannot contain body in new.php on line 17

        Fatal error: Abstract function abst1::abstra1() cannot contain body in php on line 17
        +

        示例代码

        <?php
+interface int1{
+    const INTER1 = 111;
+    function inter1();
+}
+interface int2{
+    const INTER1 = 222;
+    function inter2();
+}
+abstract class abst1{
+    public function abstr1(){
+        echo 1111;
+    }
+    abstract function abstra1(){
+        echo 'ahahahha';
+    }
+}
+abstract class abst2{
+    public function abstr2(){
+        echo 1111;
+    }
+    abstract function abstra2();
+}
+class normal1 extends abst1{
+    protected function abstr2(){
+        echo 222;
+    }
+}
        + +

        result

        PHP Fatal error:  Abstract function abst1::abstra1() cannot contain body in new.php on line 17
+
+Fatal error: Abstract function abst1::abstra1() cannot contain body in php on line 17
        @@ -431,7 +454,7 @@
        -
        1. 1. PHP抽象类和接口
        2. 2. 示例代码
        3. 3. result
        +
        1. 1. PHP抽象类和接口
        2. 2. 示例代码
        3. 3. result
        diff --git a/2017/03/28/spark-little-tips/index.html b/2017/03/28/spark-little-tips/index.html index 34f9149433..1531942554 100644 --- a/2017/03/28/spark-little-tips/index.html +++ b/2017/03/28/spark-little-tips/index.html @@ -4,7 +4,7 @@ - + @@ -32,8 +32,9 @@ + - + @@ -229,13 +230,6 @@         - - - - - Edited on - - @@ -286,10 +280,17 @@

        spark 的一些粗浅使用经验

        工作中学习使用了一下Spark做数据分析,主要是用spark的python接口，首先是pyspark.SparkContext(appName=xxx)，这是初始化一个Spark应用实例或者说会话，不能重复，
        返回的实例句柄就可以调用textFile(path)读取文本文件，这里的文本文件可以是HDFS上的文本文件，也可以普通文本文件，但是需要在Spark的所有集群上都存在，否则会
        读取失败，parallelize则可以将python生成的集合数据读取后转换成rdd(A Resilient Distributed Dataset (RDD),一种spark下的基本抽象数据集),基于这个RDD就可以做
        数据的流式计算，例如map reduce,在Spark中可以非常方便地实现

        -

        简单的mapreduce word count示例

        1
        2
        3
        4
        textFile = sc.parallelize([(1,1), (2,1), (3,1), (4,1), (5,1),(1,1), (2,1), (3,1), (4,1), (5,1)])
        data = textFile.reduceByKey(lambda x, y: x + y).collect()
        for _ in data:
            print(_)
        +

        简单的mapreduce word count示例

        textFile = sc.parallelize([(1,1), (2,1), (3,1), (4,1), (5,1),(1,1), (2,1), (3,1), (4,1), (5,1)])
+data = textFile.reduceByKey(lambda x, y: x + y).collect()
+for _ in data:
+    print(_)
        -

        结果

        1
        2
        3
        4
        5
        (3, 2)
        (1, 2)
        (4, 2)
        (2, 2)
        (5, 2)
        +

        结果

        (3, 2)
+(1, 2)
+(4, 2)
+(2, 2)
+(5, 2)
        @@ -420,7 +421,7 @@
        -
        1. 1. spark 的一些粗浅使用经验
          1. 1.1. 简单的mapreduce word count示例
          2. 1.2. 结果
        +
        1. 1. spark 的一些粗浅使用经验
          1. 1.1. 简单的mapreduce word count示例
          2. 1.2. 结果
        diff --git a/2017/04/25/rabbitmq-tips/index.html b/2017/04/25/rabbitmq-tips/index.html index b6e548bc93..ab8f3e05d9 100644 --- a/2017/04/25/rabbitmq-tips/index.html +++ b/2017/04/25/rabbitmq-tips/index.html @@ -4,7 +4,7 @@ - + @@ -32,8 +32,9 @@ + - + @@ -230,13 +231,6 @@         - - - - - Edited on - - @@ -286,14 +280,23 @@
        -

        rabbitmq 介绍

        接触了一下rabbitmq，原来在选型的时候是在rabbitmq跟kafka之间做选择，网上搜了一下之后发现kafka的优势在于吞吐量，而rabbitmq相对注重可靠性，因为应用在im上，需要保证消息不能丢失所以就暂时选定rabbitmq，
        Message Queue的需求由来已久，80年代最早在金融交易中，高盛等公司采用Teknekron公司的产品，当时的Message queuing软件叫做：the information bus（TIB）。 TIB被电信和通讯公司采用，路透社收购了Teknekron公司。之后，IBM开发了MQSeries，微软开发了Microsoft Message Queue（MSMQ）。这些商业MQ供应商的问题是厂商锁定，价格高昂。2001年，Java Message queuing试图解决锁定和交互性的问题，但对应用来说反而更加麻烦了。
        RabbitMQ采用Erlang语言开发。Erlang语言由Ericson设计，专门为开发concurrent和distribution系统的一种语言，在电信领域使用广泛。OTP（Open Telecom Platform）作为Erlang语言的一部分，包含了很多基于Erlang开发的中间件／库／工具，如mnesia／SASL，极大方便了Erlang应用的开发。OTP就类似于Python语言中众多的module，用户借助这些module可以很方便的开发应用。
        于是2004年，摩根大通和iMatrix开始着手Advanced Message Queuing Protocol （AMQP）开放标准的开发。2006年，AMQP规范发布。2007年，Rabbit技术公司基于AMQP标准开发的RabbitMQ 1.0 发布。所有主要的编程语言均有与代理接口通讯的客户端库。

        +

        rabbitmq 介绍

        接触了一下rabbitmq，原来在选型的时候是在rabbitmq跟kafka之间做选择，网上搜了一下之后发现kafka的优势在于吞吐量，而rabbitmq相对注重可靠性，因为应用在im上，需要保证消息不能丢失所以就暂时选定rabbitmq，
        Message Queue的需求由来已久，80年代最早在金融交易中，高盛等公司采用Teknekron公司的产品，当时的Message queuing软件叫做：the information bus（TIB）。 TIB被电信和通讯公司采用，路透社收购了Teknekron公司。之后，IBM开发了MQSeries，微软开发了Microsoft Message Queue（MSMQ）。这些商业MQ供应商的问题是厂商锁定，价格高昂。2001年，Java Message queuing试图解决锁定和交互性的问题，但对应用来说反而更加麻烦了。
        RabbitMQ采用Erlang语言开发。Erlang语言由Ericson设计，专门为开发concurrent和distribution系统的一种语言，在电信领域使用广泛。OTP（Open Telecom Platform）作为Erlang语言的一部分，包含了很多基于Erlang开发的中间件／库／工具，如mnesia／SASL，极大方便了Erlang应用的开发。OTP就类似于Python语言中众多的module，用户借助这些module可以很方便的开发应用。
        于是2004年，摩根大通和iMatrix开始着手Advanced Message Queuing Protocol （AMQP）开放标准的开发。2006年，AMQP规范发布。2007年，Rabbit技术公司基于AMQP标准开发的RabbitMQ 1.0 发布。所有主要的编程语言均有与代理接口通讯的客户端库。

        简单的使用经验

        通俗的理解

        这里介绍下其中的一些概念，connection表示和队列服务器的连接，一般情况下是tcp连接， channel表示通道，可以在一个连接上建立多个通道，这里主要是节省了tcp连接握手的成本，exchange可以理解成一个路由器，将消息推送给对应的队列queue，其实是像一个订阅的模式。

        集群经验

        rabbitmqctl stop这个是关闭rabbitmq，在搭建集群时候先关闭服务，然后使用rabbitmq-server -detached静默启动，这时候使用rabbitmqctl cluster_status查看集群状态，因为还没将节点加入集群，所以只能看到类似

        -
        1
        2
        3
        4
        Cluster status of node rabbit@rabbit1 ...
        [{nodes,[{disc,[rabbit@rabbit1,rabbit@rabbit2,rabbit@rabbit3]}]},
         {running_nodes,[rabbit@rabbit2,rabbit@rabbit1]}]
        ...done.
        +
        Cluster status of node rabbit@rabbit1 ...
+[{nodes,[{disc,[rabbit@rabbit1,rabbit@rabbit2,rabbit@rabbit3]}]},
+ {running_nodes,[rabbit@rabbit2,rabbit@rabbit1]}]
+...done.

        然后就可以把当前节点加入集群，

        -
        1
        2
        3
        4
        5
        6
        7
        rabbit2$ rabbitmqctl stop_app #这个stop_app与stop的区别是前者停的是rabbitmq应用，保留erlang节点，
                                      #后者是停止了rabbitmq和erlang节点
        Stopping node rabbit@rabbit2 ...done.
        rabbit2$ rabbitmqctl join_cluster rabbit@rabbit1 #这里可以用--ram指定将当前节点作为内存节点加入集群
        Clustering node rabbit@rabbit2 with [rabbit@rabbit1] ...done.
        rabbit2$ rabbitmqctl start_app
        Starting node rabbit@rabbit2 ...done.
        -

        其他可以参考官方文档

        -

        一些坑

        消息丢失

        这里碰到过一个坑，对于使用exchange来做消息路由的，会有一个情况，就是在routing_key没被订阅的时候，会将该条找不到路由对应的queue的消息丢掉What happens if we break our contract and send a message with one or four words, like "orange" or "quick.orange.male.rabbit"? Well, these messages won't match any bindings and will be lost.对应链接,而当使用空的exchange时，会保留消息，当出现消费者的时候就可以将收到之前生产者所推送的消息对应链接,这里就是用了空的exchange。

        +
        rabbit2$ rabbitmqctl stop_app #这个stop_app与stop的区别是前者停的是rabbitmq应用，保留erlang节点，
+                              #后者是停止了rabbitmq和erlang节点
+Stopping node rabbit@rabbit2 ...done.
+rabbit2$ rabbitmqctl join_cluster rabbit@rabbit1 #这里可以用--ram指定将当前节点作为内存节点加入集群
+Clustering node rabbit@rabbit2 with [rabbit@rabbit1] ...done.
+rabbit2$ rabbitmqctl start_app
+Starting node rabbit@rabbit2 ...done.
        +

        其他可以参考官方文档

        +

        一些坑

        消息丢失

        这里碰到过一个坑，对于使用exchange来做消息路由的，会有一个情况，就是在routing_key没被订阅的时候，会将该条找不到路由对应的queue的消息丢掉What happens if we break our contract and send a message with one or four words, like "orange" or "quick.orange.male.rabbit"? Well, these messages won't match any bindings and will be lost.对应链接,而当使用空的exchange时，会保留消息，当出现消费者的时候就可以将收到之前生产者所推送的消息对应链接,这里就是用了空的exchange。

        集群搭建

        集群搭建的时候有个erlang vm生成的random cookie，这个是用来做集群之间认证的，相同的cookie才能连接，但是如果通过vim打开复制后在其他几点新建文件写入会多一个换行，导致集群建立是报错，所以这里最好使用scp等传输命令直接传输cookie文件，同时要注意下cookie的文件权限。
        另外在集群搭建的时候如果更改过hostname，那么要把rabbitmq的数据库删除，否则启动后会马上挂掉

        @@ -432,7 +435,7 @@
        -
        1. 1. rabbitmq 介绍
        2. 2. 简单的使用经验
          1. 2.1. 通俗的理解
          2. 2.2. 集群经验
        3. 3. 一些坑
          1. 3.1. 消息丢失
          2. 3.2. 集群搭建
        +
        1. 1. rabbitmq 介绍
        2. 2. 简单的使用经验
          1. 2.1. 通俗的理解
          2. 2.2. 集群经验
        3. 3. 一些坑
          1. 3.1. 消息丢失
          2. 3.2. 集群搭建
        diff --git a/2017/05/09/ambari-summary/index.html b/2017/05/09/ambari-summary/index.html index 0864d3b836..8f6ecda128 100644 --- a/2017/05/09/ambari-summary/index.html +++ b/2017/05/09/ambari-summary/index.html @@ -4,7 +4,7 @@ - + @@ -32,8 +32,9 @@ + - + @@ -229,13 +230,6 @@         - - - - - Edited on - - @@ -285,12 +279,12 @@
        -

        初识ambari

        ambari是一个大数据平台的管理工具，包含了hadoop, yarn, hive, hbase, spark等大数据的基础架构和工具，简化了数据平台的搭建，之前只是在同事搭建好平台后的一些使用，这次有机会从头开始用ambari来搭建一个测试的数据平台，过程中也踩到不少坑，简单记录下。

        +

        初识ambari

        ambari是一个大数据平台的管理工具，包含了hadoop, yarn, hive, hbase, spark等大数据的基础架构和工具，简化了数据平台的搭建，之前只是在同事搭建好平台后的一些使用，这次有机会从头开始用ambari来搭建一个测试的数据平台，过程中也踩到不少坑，简单记录下。

        简单过程

          -
        • 第一个坑
          在刚开始是按照官网的指南，用maven构建，因为GFW的原因，导致反复失败等待，也就是这个guide，因为对maven不熟悉导致有些按图索骥，浪费了很多时间，之后才知道可以直接加repo用yum安装，然而用yum安装马上就出现了第二个坑。
          • -
        • 第二个坑
          因为在线的repo还是因为网络原因很慢很慢，用proxychains勉强把ambari-server本身安装好了，ambari.repo将这个放进/etc/yum.repos.d/路径下，然后yum update && yum install ambari-server安装即可，如果有条件就用proxychains走下代理。
          • +
        • 第一个坑
          在刚开始是按照官网的指南，用maven构建，因为GFW的原因，导致反复失败等待，也就是这个guide，因为对maven不熟悉导致有些按图索骥，浪费了很多时间，之后才知道可以直接加repo用yum安装，然而用yum安装马上就出现了第二个坑。
          • +
        • 第二个坑
          因为在线的repo还是因为网络原因很慢很慢，用proxychains勉强把ambari-server本身安装好了，ambari.repo将这个放进/etc/yum.repos.d/路径下，然后yum update && yum install ambari-server安装即可，如果有条件就用proxychains走下代理。
        • 第三步
          安装好ambari-server后先执行ambari-server setup做一些初始化设置，其中包含了JDK路径的设置，数据库设置，设置好就OK了，然后执行ambari-server start启动服务，这里有个小插曲，因为ambari-server涉及到这么多服务，所以管理控制监控之类的模块是必不可少的，这部分可以在ambari-server的web ui界面安装，也可以命令行提前安装，这部分被称为HDF Management Pack，运行```ambari-server install-mpack \
          • -
        • -mpack=http://public-repo-1.hortonworks.com/HDF/centos7/2.x/updates/2.1.4.0/tars/hdf_ambari_mp/hdf-ambari-mpack-2.1.4.0-5.tar.gz \
          • +
        • -mpack=http://public-repo-1.hortonworks.com/HDF/centos7/2.x/updates/2.1.4.0/tars/hdf_ambari_mp/hdf-ambari-mpack-2.1.4.0-5.tar.gz \
        • -purge \
        • -verbose```
          安装，当然这个压缩包可以下载之后指到本地路径安装，然后就可以重启ambari-server
        @@ -424,7 +418,7 @@
        -
        1. 1. 初识ambari
        2. 2. 简单过程
        +
        1. 1. 初识ambari
        2. 2. 简单过程
        diff --git a/2019/06/18/openresty/index.html b/2019/06/18/openresty/index.html index 9d53d104b4..cf3d373425 100644 --- a/2019/06/18/openresty/index.html +++ b/2019/06/18/openresty/index.html @@ -4,7 +4,7 @@ - + @@ -32,8 +32,9 @@ + - + @@ -229,13 +230,6 @@ - - - - - Edited on - - @@ -288,13 +282,20 @@

        目前公司要对一些新的产品功能做灰度测试，因为在后端业务代码层面添加判断比较麻烦，所以想在nginx上做点手脚，就想到了openresty
        前后也踩了不少坑，这边先写一点

        首先是日志
        error_log logs/error.log debug;
        需要nginx开启日志的debug才能看到日志

        使用 lua_code_cache off即可, 另外注意只有使用 content_by_lua_file 才会生效

        -
        1
        2
        3
        4
        5
        6
        7
        8
        http {
          lua_code_cache off;
        }

        location ~* /(\d+-.*)/api/orgunits/load_all(.*) {
           default_type 'application/json;charset=utf-8';
           content_by_lua_file /data/projects/xxx/current/lua/controller/load_data.lua;
        }
        +
        http {
+  lua_code_cache off;
+}
+
+location ~* /(\d+-.*)/api/orgunits/load_all(.*) {
+   default_type 'application/json;charset=utf-8';
+   content_by_lua_file /data/projects/xxx/current/lua/controller/load_data.lua;
+}

        使用lua给nginx请求response头添加内容可以用这个

        -
        1
        ngx.header['response'] = 'header'
        +
        ngx.header['response'] = 'header'
        -

        使用总结

        +

        使用总结

        后续：

        1. 一开始在本地环境的时候使用content_by_lua_file只关注了头，后来发到测试环境发现请求内容都没代理转发到后端服务上
          网上查了下发现content_by_lua_file是将请求的所有内容包括response都用这里面的lua脚本生成了，content这个词就表示是请求内容
          后来改成了access_by_lua_file就正常了，只是要去获取请求内容和修改响应头，并不是要完整的接管请求
          2. @@ -303,18 +304,33 @@

        2. 后来又碰到了一个坑是nginx有个client_body_buffer_size的配置参数，nginx在32位和64位系统里有8K和16K两个默认值，当请求内容大于这两个值的时候，会把请求内容放到临时文件里，这个时候openresty里的ngx.req.get_post_args()就会报“failed to get post args: requesty body in temp file not supported”这个错误，将client_body_buffer_size这个参数配置调大一点就好了

        3. 还有就是lua的异常捕获，网上看一般是用pcall和xpcall来进行保护调用，因为问题主要出在cjson的decode，这里有两个解决方案，一个就是将cjson.decode使用pcall封装，

          - 
          1
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          local decode = require("cjson").decode

          function json_decode( str )
              local ok, t = pcall(decode, str)
              if not ok then
                return nil
              end

              return t
          end
          + 
          local decode = require("cjson").decode
+
+function json_decode( str )
+    local ok, t = pcall(decode, str)
+    if not ok then
+      return nil
+    end
+
+    return t
+end

          这个是使用了pcall，称为保护调用，会在内部错误后返回两个参数，第一个是false，第二个是错误信息
          还有一种是使用cjson.safe包

          - 
          1
          2
          3
          4
          5
          6
          7
          local json = require("cjson.safe")
          local str = [[ {"key:"value"} ]]

          local t = json.decode(str)
          if t then
              ngx.say(" --> ", type(t))
          end
          + 
          local json = require("cjson.safe")
+local str = [[ {"key:"value"} ]]
+
+local t = json.decode(str)
+if t then
+    ngx.say(" --> ", type(t))
+end

          cjson.safe包会在解析失败的时候返回nil

        4. 还有一个是redis链接时如果host使用的是域名的话会提示“failed to connect: no resolver defined to resolve “redis.xxxxxx.com””，这里需要使用nginx的resolver指令，
          resolver 8.8.8.8 valid=3600s;

        5. 还有一点补充下
          就是业务在使用redis的时候使用了db的特性，所以在lua访问redis的时候也需要执行db，这里lua的redis库也支持了这个特性，可以使用instance:select(config:get(‘db’))来切换db

          6. -

        6. 性能优化tips
          建议是尽量少使用阶段钩子，例如content_by_lua_file，*_by_lua

          +

        7. 性能优化tips
          建议是尽量少使用阶段钩子，例如content_by_lua_file，*_by_lua

          8. -

        8. 发现一个不错的openresty站点
          地址

          +

        9. 发现一个不错的openresty站点
          地址

        diff --git a/2019/09/23/AbstractQueuedSynchronizer/index.html b/2019/09/23/AbstractQueuedSynchronizer/index.html index 5ee6ca4aab..1fa9939d0d 100644 --- a/2019/09/23/AbstractQueuedSynchronizer/index.html +++ b/2019/09/23/AbstractQueuedSynchronizer/index.html @@ -4,7 +4,7 @@ - + @@ -26,15 +26,16 @@ var CONFIG = {"hostname":"nicksxs.me","root":"/","scheme":"Pisces","version":"7.8.0","exturl":false,"sidebar":{"position":"left","display":"post","padding":18,"offset":12,"onmobile":false},"copycode":{"enable":true,"show_result":false,"style":null},"back2top":{"enable":true,"sidebar":false,"scrollpercent":false},"bookmark":{"enable":false,"color":"#222","save":"auto"},"fancybox":true,"mediumzoom":false,"lazyload":true,"pangu":false,"comments":{"style":"tabs","active":null,"storage":true,"lazyload":false,"nav":null},"algolia":{"hits":{"per_page":10},"labels":{"input_placeholder":"Search for Posts","hits_empty":"We didn't find any results for the search: ${query}","hits_stats":"${hits} results found in ${time} ms"}},"localsearch":{"enable":false,"trigger":"auto","top_n_per_article":1,"unescape":false,"preload":false},"motion":{"enable":true,"async":false,"transition":{"post_block":"fadeIn","post_header":"slideDownIn","post_body":"slideDownIn","coll_header":"slideLeftIn","sidebar":"slideUpIn"}}}; - + - + + - + @@ -231,13 +232,6 @@         - - - - - Edited on - - @@ -288,10 +282,59 @@

        最近看了大神的 AQS 的文章，之前总是断断续续地看一点，每次都知难而退，下次看又从头开始，昨天总算硬着头皮看完了第一部分
        首先 AQS 只要有这些属性

        -
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        // 头结点，你直接把它当做 当前持有锁的线程 可能是最好理解的
        private transient volatile Node head;

        // 阻塞的尾节点，每个新的节点进来，都插入到最后，也就形成了一个链表
        private transient volatile Node tail;

        // 这个是最重要的，代表当前锁的状态，0代表没有被占用，大于 0 代表有线程持有当前锁
        // 这个值可以大于 1，是因为锁可以重入，每次重入都加上 1
        private volatile int state;

        // 代表当前持有独占锁的线程，举个最重要的使用例子，因为锁可以重入
        // reentrantLock.lock()可以嵌套调用多次，所以每次用这个来判断当前线程是否已经拥有了锁
        // if (currentThread == getExclusiveOwnerThread()) {state++}
        private transient Thread exclusiveOwnerThread; //继承自AbstractOwnableSynchronizer
        -

        大概了解了 aqs 底层的双向等待队列，
        结构是这样的

        每个 node 里面主要是的代码结构也比较简单

        -
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        static final class Node {
            // 标识节点当前在共享模式下
            static final Node SHARED = new Node();
            // 标识节点当前在独占模式下
            static final Node EXCLUSIVE = null;

            // ======== 下面的几个int常量是给waitStatus用的 ===========
            /** waitStatus value to indicate thread has cancelled */
            // 代码此线程取消了争抢这个锁
            static final int CANCELLED =  1;
            /** waitStatus value to indicate successor's thread needs unparking */
            // 官方的描述是，其表示当前node的后继节点对应的线程需要被唤醒
            static final int SIGNAL    = -1;
            /** waitStatus value to indicate thread is waiting on condition */
            // 本文不分析condition，所以略过吧，下一篇文章会介绍这个
            static final int CONDITION = -2;
            /**
             * waitStatus value to indicate the next acquireShared should
             * unconditionally propagate
             */
            // 同样的不分析，略过吧
            static final int PROPAGATE = -3;
            // =====================================================


            // 取值为上面的1、-1、-2、-3，或者0(以后会讲到)
            // 这么理解，暂时只需要知道如果这个值 大于0 代表此线程取消了等待，
            //    ps: 半天抢不到锁，不抢了，ReentrantLock是可以指定timeouot的。。。
            volatile int waitStatus;
            // 前驱节点的引用
            volatile Node prev;
            // 后继节点的引用
            volatile Node next;
            // 这个就是线程本尊
            volatile Thread thread;

        }
        -

        其实可以主要关注这个 waitStatus 因为这个是后面的节点给前面的节点设置的，等于-1 的时候代表后面有节点等待，需要去唤醒，
        这里使用了一个变种的 CLH 队列实现，CLH 队列相关内容可以查看这篇 自旋锁、排队自旋锁、MCS锁、CLH锁

        +
        // 头结点，你直接把它当做 当前持有锁的线程 可能是最好理解的
+private transient volatile Node head;
+
+// 阻塞的尾节点，每个新的节点进来，都插入到最后，也就形成了一个链表
+private transient volatile Node tail;
+
+// 这个是最重要的，代表当前锁的状态，0代表没有被占用，大于 0 代表有线程持有当前锁
+// 这个值可以大于 1，是因为锁可以重入，每次重入都加上 1
+private volatile int state;
+
+// 代表当前持有独占锁的线程，举个最重要的使用例子，因为锁可以重入
+// reentrantLock.lock()可以嵌套调用多次，所以每次用这个来判断当前线程是否已经拥有了锁
+// if (currentThread == getExclusiveOwnerThread()) {state++}
+private transient Thread exclusiveOwnerThread; //继承自AbstractOwnableSynchronizer
        +

        大概了解了 aqs 底层的双向等待队列，
        结构是这样的

        每个 node 里面主要是的代码结构也比较简单

        +
        static final class Node {
+    // 标识节点当前在共享模式下
+    static final Node SHARED = new Node();
+    // 标识节点当前在独占模式下
+    static final Node EXCLUSIVE = null;
+
+    // ======== 下面的几个int常量是给waitStatus用的 ===========
+    /** waitStatus value to indicate thread has cancelled */
+    // 代码此线程取消了争抢这个锁
+    static final int CANCELLED =  1;
+    /** waitStatus value to indicate successor's thread needs unparking */
+    // 官方的描述是，其表示当前node的后继节点对应的线程需要被唤醒
+    static final int SIGNAL    = -1;
+    /** waitStatus value to indicate thread is waiting on condition */
+    // 本文不分析condition，所以略过吧，下一篇文章会介绍这个
+    static final int CONDITION = -2;
+    /**
+     * waitStatus value to indicate the next acquireShared should
+     * unconditionally propagate
+     */
+    // 同样的不分析，略过吧
+    static final int PROPAGATE = -3;
+    // =====================================================
+
+
+    // 取值为上面的1、-1、-2、-3，或者0(以后会讲到)
+    // 这么理解，暂时只需要知道如果这个值 大于0 代表此线程取消了等待，
+    //    ps: 半天抢不到锁，不抢了，ReentrantLock是可以指定timeouot的。。。
+    volatile int waitStatus;
+    // 前驱节点的引用
+    volatile Node prev;
+    // 后继节点的引用
+    volatile Node next;
+    // 这个就是线程本尊
+    volatile Thread thread;
+
+}
        +

        其实可以主要关注这个 waitStatus 因为这个是后面的节点给前面的节点设置的，等于-1 的时候代表后面有节点等待，需要去唤醒，
        这里使用了一个变种的 CLH 队列实现，CLH 队列相关内容可以查看这篇 自旋锁、排队自旋锁、MCS锁、CLH锁

        @@ -302,19 +345,19 @@
        Related Posts
        diff --git a/2019/12/07/JVM-G1-Part-1/index.html b/2019/12/07/JVM-G1-Part-1/index.html index 2ca9f5d018..026dd2ff65 100644 --- a/2019/12/07/JVM-G1-Part-1/index.html +++ b/2019/12/07/JVM-G1-Part-1/index.html @@ -4,7 +4,7 @@ - + @@ -32,6 +32,7 @@ + @@ -299,18 +300,595 @@

        对 Java 的 gc 实现比较感兴趣，原先一般都是看周志明的书，但其实并没有讲具体的 gc 源码，而是把整个思路和流程讲解了一下
        特别是 G1 的具体实现
        一般对 G1 的理解其实就是把原先整块的新生代老年代分成了以 region 为单位的小块内存，简而言之，就是原先对新生代老年代的收集会涉及到整个代的堆内存空间，而G1 把它变成了更细致的小块内存
        这带来了一个很明显的好处和一个很明显的坏处，好处是内存收集可以更灵活，耗时会变短，但整个收集的处理复杂度就变高了
        目前看了一点点关于 G1 收集的预期时间相关的代码

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        HeapWord* G1CollectedHeap::do_collection_pause(size_t word_size,
                                                       uint gc_count_before,
                                                       bool* succeeded,
                                                       GCCause::Cause gc_cause) {
          assert_heap_not_locked_and_not_at_safepoint();
          VM_G1CollectForAllocation op(word_size,
                                       gc_count_before,
                                       gc_cause,
                                       false, /* should_initiate_conc_mark */
                                       g1_policy()->max_pause_time_ms());
          VMThread::execute(&op);

          HeapWord* result = op.result();
          bool ret_succeeded = op.prologue_succeeded() && op.pause_succeeded();
          assert(result == NULL || ret_succeeded,
                 "the result should be NULL if the VM did not succeed");
          *succeeded = ret_succeeded;

          assert_heap_not_locked();
          return result;
        }
        +
        HeapWord* G1CollectedHeap::do_collection_pause(size_t word_size,
+                                               uint gc_count_before,
+                                               bool* succeeded,
+                                               GCCause::Cause gc_cause) {
+  assert_heap_not_locked_and_not_at_safepoint();
+  VM_G1CollectForAllocation op(word_size,
+                               gc_count_before,
+                               gc_cause,
+                               false, /* should_initiate_conc_mark */
+                               g1_policy()->max_pause_time_ms());
+  VMThread::execute(&op);
+
+  HeapWord* result = op.result();
+  bool ret_succeeded = op.prologue_succeeded() && op.pause_succeeded();
+  assert(result == NULL || ret_succeeded,
+         "the result should be NULL if the VM did not succeed");
+  *succeeded = ret_succeeded;
+
+  assert_heap_not_locked();
+  return result;
+}

        这里就是收集时需要停顿的，其中VMThread::execute(&op);是具体执行的，真正执行的是VM_G1CollectForAllocation::doit方法

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        void VM_G1CollectForAllocation::doit() {
          G1CollectedHeap* g1h = G1CollectedHeap::heap();
          assert(!_should_initiate_conc_mark || g1h->should_do_concurrent_full_gc(_gc_cause),
              "only a GC locker, a System.gc(), stats update, whitebox, or a hum allocation induced GC should start a cycle");

          if (_word_size > 0) {
            // An allocation has been requested. So, try to do that first.
            _result = g1h->attempt_allocation_at_safepoint(_word_size,
                                                           false /* expect_null_cur_alloc_region */);
            if (_result != NULL) {
              // If we can successfully allocate before we actually do the
              // pause then we will consider this pause successful.
              _pause_succeeded = true;
              return;
            }
          }

          GCCauseSetter x(g1h, _gc_cause);
          if (_should_initiate_conc_mark) {
            // It's safer to read old_marking_cycles_completed() here, given
            // that noone else will be updating it concurrently. Since we'll
            // only need it if we're initiating a marking cycle, no point in
            // setting it earlier.
            _old_marking_cycles_completed_before = g1h->old_marking_cycles_completed();

            // At this point we are supposed to start a concurrent cycle. We
            // will do so if one is not already in progress.
            bool res = g1h->g1_policy()->force_initial_mark_if_outside_cycle(_gc_cause);

            // The above routine returns true if we were able to force the
            // next GC pause to be an initial mark; it returns false if a
            // marking cycle is already in progress.
            //
            // If a marking cycle is already in progress just return and skip the
            // pause below - if the reason for requesting this initial mark pause
            // was due to a System.gc() then the requesting thread should block in
            // doit_epilogue() until the marking cycle is complete.
            //
            // If this initial mark pause was requested as part of a humongous
            // allocation then we know that the marking cycle must just have
            // been started by another thread (possibly also allocating a humongous
            // object) as there was no active marking cycle when the requesting
            // thread checked before calling collect() in
            // attempt_allocation_humongous(). Retrying the GC, in this case,
            // will cause the requesting thread to spin inside collect() until the
            // just started marking cycle is complete - which may be a while. So
            // we do NOT retry the GC.
            if (!res) {
              assert(_word_size == 0, "Concurrent Full GC/Humongous Object IM shouldn't be allocating");
              if (_gc_cause != GCCause::_g1_humongous_allocation) {
                _should_retry_gc = true;
              }
              return;
            }
          }

          // Try a partial collection of some kind.
          _pause_succeeded = g1h->do_collection_pause_at_safepoint(_target_pause_time_ms);

          if (_pause_succeeded) {
            if (_word_size > 0) {
              // An allocation had been requested. Do it, eventually trying a stronger
              // kind of GC.
              _result = g1h->satisfy_failed_allocation(_word_size, &_pause_succeeded);
            } else {
              bool should_upgrade_to_full = !g1h->should_do_concurrent_full_gc(_gc_cause) &&
                                            !g1h->has_regions_left_for_allocation();
              if (should_upgrade_to_full) {
                // There has been a request to perform a GC to free some space. We have no
                // information on how much memory has been asked for. In case there are
                // absolutely no regions left to allocate into, do a maximally compacting full GC.
                log_info(gc, ergo)("Attempting maximally compacting collection");
                _pause_succeeded = g1h->do_full_collection(false, /* explicit gc */
                                                           true   /* clear_all_soft_refs */);
              }
            }
            guarantee(_pause_succeeded, "Elevated collections during the safepoint must always succeed.");
          } else {
            assert(_result == NULL, "invariant");
            // The only reason for the pause to not be successful is that, the GC locker is
            // active (or has become active since the prologue was executed). In this case
            // we should retry the pause after waiting for the GC locker to become inactive.
            _should_retry_gc = true;
          }
        }
        +
        void VM_G1CollectForAllocation::doit() {
+  G1CollectedHeap* g1h = G1CollectedHeap::heap();
+  assert(!_should_initiate_conc_mark || g1h->should_do_concurrent_full_gc(_gc_cause),
+      "only a GC locker, a System.gc(), stats update, whitebox, or a hum allocation induced GC should start a cycle");
+
+  if (_word_size > 0) {
+    // An allocation has been requested. So, try to do that first.
+    _result = g1h->attempt_allocation_at_safepoint(_word_size,
+                                                   false /* expect_null_cur_alloc_region */);
+    if (_result != NULL) {
+      // If we can successfully allocate before we actually do the
+      // pause then we will consider this pause successful.
+      _pause_succeeded = true;
+      return;
+    }
+  }
+
+  GCCauseSetter x(g1h, _gc_cause);
+  if (_should_initiate_conc_mark) {
+    // It's safer to read old_marking_cycles_completed() here, given
+    // that noone else will be updating it concurrently. Since we'll
+    // only need it if we're initiating a marking cycle, no point in
+    // setting it earlier.
+    _old_marking_cycles_completed_before = g1h->old_marking_cycles_completed();
+
+    // At this point we are supposed to start a concurrent cycle. We
+    // will do so if one is not already in progress.
+    bool res = g1h->g1_policy()->force_initial_mark_if_outside_cycle(_gc_cause);
+
+    // The above routine returns true if we were able to force the
+    // next GC pause to be an initial mark; it returns false if a
+    // marking cycle is already in progress.
+    //
+    // If a marking cycle is already in progress just return and skip the
+    // pause below - if the reason for requesting this initial mark pause
+    // was due to a System.gc() then the requesting thread should block in
+    // doit_epilogue() until the marking cycle is complete.
+    //
+    // If this initial mark pause was requested as part of a humongous
+    // allocation then we know that the marking cycle must just have
+    // been started by another thread (possibly also allocating a humongous
+    // object) as there was no active marking cycle when the requesting
+    // thread checked before calling collect() in
+    // attempt_allocation_humongous(). Retrying the GC, in this case,
+    // will cause the requesting thread to spin inside collect() until the
+    // just started marking cycle is complete - which may be a while. So
+    // we do NOT retry the GC.
+    if (!res) {
+      assert(_word_size == 0, "Concurrent Full GC/Humongous Object IM shouldn't be allocating");
+      if (_gc_cause != GCCause::_g1_humongous_allocation) {
+        _should_retry_gc = true;
+      }
+      return;
+    }
+  }
+
+  // Try a partial collection of some kind.
+  _pause_succeeded = g1h->do_collection_pause_at_safepoint(_target_pause_time_ms);
+
+  if (_pause_succeeded) {
+    if (_word_size > 0) {
+      // An allocation had been requested. Do it, eventually trying a stronger
+      // kind of GC.
+      _result = g1h->satisfy_failed_allocation(_word_size, &_pause_succeeded);
+    } else {
+      bool should_upgrade_to_full = !g1h->should_do_concurrent_full_gc(_gc_cause) &&
+                                    !g1h->has_regions_left_for_allocation();
+      if (should_upgrade_to_full) {
+        // There has been a request to perform a GC to free some space. We have no
+        // information on how much memory has been asked for. In case there are
+        // absolutely no regions left to allocate into, do a maximally compacting full GC.
+        log_info(gc, ergo)("Attempting maximally compacting collection");
+        _pause_succeeded = g1h->do_full_collection(false, /* explicit gc */
+                                                   true   /* clear_all_soft_refs */);
+      }
+    }
+    guarantee(_pause_succeeded, "Elevated collections during the safepoint must always succeed.");
+  } else {
+    assert(_result == NULL, "invariant");
+    // The only reason for the pause to not be successful is that, the GC locker is
+    // active (or has become active since the prologue was executed). In this case
+    // we should retry the pause after waiting for the GC locker to become inactive.
+    _should_retry_gc = true;
+  }
+}

        这里可以看到核心的是G1CollectedHeap::do_collection_pause_at_safepoint这个方法，它带上了目标暂停时间的值

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        G1CollectedHeap::do_collection_pause_at_safepoint(double target_pause_time_ms) {
          assert_at_safepoint_on_vm_thread();
          guarantee(!is_gc_active(), "collection is not reentrant");

          if (GCLocker::check_active_before_gc()) {
            return false;
          }

          _gc_timer_stw->register_gc_start();

          GCIdMark gc_id_mark;
          _gc_tracer_stw->report_gc_start(gc_cause(), _gc_timer_stw->gc_start());

          SvcGCMarker sgcm(SvcGCMarker::MINOR);
          ResourceMark rm;

          g1_policy()->note_gc_start();

          wait_for_root_region_scanning();

          print_heap_before_gc();
          print_heap_regions();
          trace_heap_before_gc(_gc_tracer_stw);

          _verifier->verify_region_sets_optional();
          _verifier->verify_dirty_young_regions();

          // We should not be doing initial mark unless the conc mark thread is running
          if (!_cm_thread->should_terminate()) {
            // This call will decide whether this pause is an initial-mark
            // pause. If it is, in_initial_mark_gc() will return true
            // for the duration of this pause.
            g1_policy()->decide_on_conc_mark_initiation();
          }

          // We do not allow initial-mark to be piggy-backed on a mixed GC.
          assert(!collector_state()->in_initial_mark_gc() ||
                  collector_state()->in_young_only_phase(), "sanity");

          // We also do not allow mixed GCs during marking.
          assert(!collector_state()->mark_or_rebuild_in_progress() || collector_state()->in_young_only_phase(), "sanity");

          // Record whether this pause is an initial mark. When the current
          // thread has completed its logging output and it's safe to signal
          // the CM thread, the flag's value in the policy has been reset.
          bool should_start_conc_mark = collector_state()->in_initial_mark_gc();

          // Inner scope for scope based logging, timers, and stats collection
          {
            EvacuationInfo evacuation_info;

            if (collector_state()->in_initial_mark_gc()) {
              // We are about to start a marking cycle, so we increment the
              // full collection counter.
              increment_old_marking_cycles_started();
              _cm->gc_tracer_cm()->set_gc_cause(gc_cause());
            }

            _gc_tracer_stw->report_yc_type(collector_state()->yc_type());

            GCTraceCPUTime tcpu;

            G1HeapVerifier::G1VerifyType verify_type;
            FormatBuffer<> gc_string("Pause Young ");
            if (collector_state()->in_initial_mark_gc()) {
              gc_string.append("(Concurrent Start)");
              verify_type = G1HeapVerifier::G1VerifyConcurrentStart;
            } else if (collector_state()->in_young_only_phase()) {
              if (collector_state()->in_young_gc_before_mixed()) {
                gc_string.append("(Prepare Mixed)");
              } else {
                gc_string.append("(Normal)");
              }
              verify_type = G1HeapVerifier::G1VerifyYoungNormal;
            } else {
              gc_string.append("(Mixed)");
              verify_type = G1HeapVerifier::G1VerifyMixed;
            }
            GCTraceTime(Info, gc) tm(gc_string, NULL, gc_cause(), true);

            uint active_workers = AdaptiveSizePolicy::calc_active_workers(workers()->total_workers(),
                                                                          workers()->active_workers(),
                                                                          Threads::number_of_non_daemon_threads());
            active_workers = workers()->update_active_workers(active_workers);
            log_info(gc,task)("Using %u workers of %u for evacuation", active_workers, workers()->total_workers());

            TraceCollectorStats tcs(g1mm()->incremental_collection_counters());
            TraceMemoryManagerStats tms(&_memory_manager, gc_cause(),
                                        collector_state()->yc_type() == Mixed /* allMemoryPoolsAffected */);

            G1HeapTransition heap_transition(this);
            size_t heap_used_bytes_before_gc = used();

            // Don't dynamically change the number of GC threads this early.  A value of
            // 0 is used to indicate serial work.  When parallel work is done,
            // it will be set.

            { // Call to jvmpi::post_class_unload_events must occur outside of active GC
              IsGCActiveMark x;

              gc_prologue(false);

              if (VerifyRememberedSets) {
                log_info(gc, verify)("[Verifying RemSets before GC]");
                VerifyRegionRemSetClosure v_cl;
                heap_region_iterate(&v_cl);
              }

              _verifier->verify_before_gc(verify_type);

              _verifier->check_bitmaps("GC Start");

        #if COMPILER2_OR_JVMCI
              DerivedPointerTable::clear();
        #endif

              // Please see comment in g1CollectedHeap.hpp and
              // G1CollectedHeap::ref_processing_init() to see how
              // reference processing currently works in G1.

              // Enable discovery in the STW reference processor
              _ref_processor_stw->enable_discovery();

              {
                // We want to temporarily turn off discovery by the
                // CM ref processor, if necessary, and turn it back on
                // on again later if we do. Using a scoped
                // NoRefDiscovery object will do this.
                NoRefDiscovery no_cm_discovery(_ref_processor_cm);

                // Forget the current alloc region (we might even choose it to be part
                // of the collection set!).
                _allocator->release_mutator_alloc_region();

                // This timing is only used by the ergonomics to handle our pause target.
                // It is unclear why this should not include the full pause. We will
                // investigate this in CR 7178365.
                //
                // Preserving the old comment here if that helps the investigation:
                //
                // The elapsed time induced by the start time below deliberately elides
                // the possible verification above.
                double sample_start_time_sec = os::elapsedTime();

                g1_policy()->record_collection_pause_start(sample_start_time_sec);

                if (collector_state()->in_initial_mark_gc()) {
                  concurrent_mark()->pre_initial_mark();
                }

                g1_policy()->finalize_collection_set(target_pause_time_ms, &_survivor);

                evacuation_info.set_collectionset_regions(collection_set()->region_length());

                // Make sure the remembered sets are up to date. This needs to be
                // done before register_humongous_regions_with_cset(), because the
                // remembered sets are used there to choose eager reclaim candidates.
                // If the remembered sets are not up to date we might miss some
                // entries that need to be handled.
                g1_rem_set()->cleanupHRRS();

                register_humongous_regions_with_cset();

                assert(_verifier->check_cset_fast_test(), "Inconsistency in the InCSetState table.");

                // We call this after finalize_cset() to
                // ensure that the CSet has been finalized.
                _cm->verify_no_cset_oops();

                if (_hr_printer.is_active()) {
                  G1PrintCollectionSetClosure cl(&_hr_printer);
                  _collection_set.iterate(&cl);
                }

                // Initialize the GC alloc regions.
                _allocator->init_gc_alloc_regions(evacuation_info);

                G1ParScanThreadStateSet per_thread_states(this, workers()->active_workers(), collection_set()->young_region_length());
                pre_evacuate_collection_set();

                // Actually do the work...
                evacuate_collection_set(&per_thread_states);

                post_evacuate_collection_set(evacuation_info, &per_thread_states);

                const size_t* surviving_young_words = per_thread_states.surviving_young_words();
                free_collection_set(&_collection_set, evacuation_info, surviving_young_words);

                eagerly_reclaim_humongous_regions();

                record_obj_copy_mem_stats();
                _survivor_evac_stats.adjust_desired_plab_sz();
                _old_evac_stats.adjust_desired_plab_sz();

                double start = os::elapsedTime();
                start_new_collection_set();
                g1_policy()->phase_times()->record_start_new_cset_time_ms((os::elapsedTime() - start) * 1000.0);

                if (evacuation_failed()) {
                  set_used(recalculate_used());
                  if (_archive_allocator != NULL) {
                    _archive_allocator->clear_used();
                  }
                  for (uint i = 0; i < ParallelGCThreads; i++) {
                    if (_evacuation_failed_info_array[i].has_failed()) {
                      _gc_tracer_stw->report_evacuation_failed(_evacuation_failed_info_array[i]);
                    }
                  }
                } else {
                  // The "used" of the the collection set have already been subtracted
                  // when they were freed.  Add in the bytes evacuated.
                  increase_used(g1_policy()->bytes_copied_during_gc());
                }

                if (collector_state()->in_initial_mark_gc()) {
                  // We have to do this before we notify the CM threads that
                  // they can start working to make sure that all the
                  // appropriate initialization is done on the CM object.
                  concurrent_mark()->post_initial_mark();
                  // Note that we don't actually trigger the CM thread at
                  // this point. We do that later when we're sure that
                  // the current thread has completed its logging output.
                }

                allocate_dummy_regions();

                _allocator->init_mutator_alloc_region();

                {
                  size_t expand_bytes = _heap_sizing_policy->expansion_amount();
                  if (expand_bytes > 0) {
                    size_t bytes_before = capacity();
                    // No need for an ergo logging here,
                    // expansion_amount() does this when it returns a value > 0.
                    double expand_ms;
                    if (!expand(expand_bytes, _workers, &expand_ms)) {
                      // We failed to expand the heap. Cannot do anything about it.
                    }
                    g1_policy()->phase_times()->record_expand_heap_time(expand_ms);
                  }
                }

                // We redo the verification but now wrt to the new CSet which
                // has just got initialized after the previous CSet was freed.
                _cm->verify_no_cset_oops();

                // This timing is only used by the ergonomics to handle our pause target.
                // It is unclear why this should not include the full pause. We will
                // investigate this in CR 7178365.
                double sample_end_time_sec = os::elapsedTime();
                double pause_time_ms = (sample_end_time_sec - sample_start_time_sec) * MILLIUNITS;
                size_t total_cards_scanned = g1_policy()->phase_times()->sum_thread_work_items(G1GCPhaseTimes::ScanRS, G1GCPhaseTimes::ScanRSScannedCards);
                g1_policy()->record_collection_pause_end(pause_time_ms, total_cards_scanned, heap_used_bytes_before_gc);

                evacuation_info.set_collectionset_used_before(collection_set()->bytes_used_before());
                evacuation_info.set_bytes_copied(g1_policy()->bytes_copied_during_gc());

                if (VerifyRememberedSets) {
                  log_info(gc, verify)("[Verifying RemSets after GC]");
                  VerifyRegionRemSetClosure v_cl;
                  heap_region_iterate(&v_cl);
                }

                _verifier->verify_after_gc(verify_type);
                _verifier->check_bitmaps("GC End");

                assert(!_ref_processor_stw->discovery_enabled(), "Postcondition");
                _ref_processor_stw->verify_no_references_recorded();

                // CM reference discovery will be re-enabled if necessary.
              }

        #ifdef TRACESPINNING
              ParallelTaskTerminator::print_termination_counts();
        #endif

              gc_epilogue(false);
            }

            // Print the remainder of the GC log output.
            if (evacuation_failed()) {
              log_info(gc)("To-space exhausted");
            }

            g1_policy()->print_phases();
            heap_transition.print();

            // It is not yet to safe to tell the concurrent mark to
            // start as we have some optional output below. We don't want the
            // output from the concurrent mark thread interfering with this
            // logging output either.

            _hrm.verify_optional();
            _verifier->verify_region_sets_optional();

            TASKQUEUE_STATS_ONLY(print_taskqueue_stats());
            TASKQUEUE_STATS_ONLY(reset_taskqueue_stats());

            print_heap_after_gc();
            print_heap_regions();
            trace_heap_after_gc(_gc_tracer_stw);

            // We must call G1MonitoringSupport::update_sizes() in the same scoping level
            // as an active TraceMemoryManagerStats object (i.e. before the destructor for the
            // TraceMemoryManagerStats is called) so that the G1 memory pools are updated
            // before any GC notifications are raised.
            g1mm()->update_sizes();

            _gc_tracer_stw->report_evacuation_info(&evacuation_info);
            _gc_tracer_stw->report_tenuring_threshold(_g1_policy->tenuring_threshold());
            _gc_timer_stw->register_gc_end();
            _gc_tracer_stw->report_gc_end(_gc_timer_stw->gc_end(), _gc_timer_stw->time_partitions());
          }
          // It should now be safe to tell the concurrent mark thread to start
          // without its logging output interfering with the logging output
          // that came from the pause.

          if (should_start_conc_mark) {
            // CAUTION: after the doConcurrentMark() call below,
            // the concurrent marking thread(s) could be running
            // concurrently with us. Make sure that anything after
            // this point does not assume that we are the only GC thread
            // running. Note: of course, the actual marking work will
            // not start until the safepoint itself is released in
            // SuspendibleThreadSet::desynchronize().
            do_concurrent_mark();
          }

          return true;
        }
        +
        G1CollectedHeap::do_collection_pause_at_safepoint(double target_pause_time_ms) {
+  assert_at_safepoint_on_vm_thread();
+  guarantee(!is_gc_active(), "collection is not reentrant");
+
+  if (GCLocker::check_active_before_gc()) {
+    return false;
+  }
+
+  _gc_timer_stw->register_gc_start();
+
+  GCIdMark gc_id_mark;
+  _gc_tracer_stw->report_gc_start(gc_cause(), _gc_timer_stw->gc_start());
+
+  SvcGCMarker sgcm(SvcGCMarker::MINOR);
+  ResourceMark rm;
+
+  g1_policy()->note_gc_start();
+
+  wait_for_root_region_scanning();
+
+  print_heap_before_gc();
+  print_heap_regions();
+  trace_heap_before_gc(_gc_tracer_stw);
+
+  _verifier->verify_region_sets_optional();
+  _verifier->verify_dirty_young_regions();
+
+  // We should not be doing initial mark unless the conc mark thread is running
+  if (!_cm_thread->should_terminate()) {
+    // This call will decide whether this pause is an initial-mark
+    // pause. If it is, in_initial_mark_gc() will return true
+    // for the duration of this pause.
+    g1_policy()->decide_on_conc_mark_initiation();
+  }
+
+  // We do not allow initial-mark to be piggy-backed on a mixed GC.
+  assert(!collector_state()->in_initial_mark_gc() ||
+          collector_state()->in_young_only_phase(), "sanity");
+
+  // We also do not allow mixed GCs during marking.
+  assert(!collector_state()->mark_or_rebuild_in_progress() || collector_state()->in_young_only_phase(), "sanity");
+
+  // Record whether this pause is an initial mark. When the current
+  // thread has completed its logging output and it's safe to signal
+  // the CM thread, the flag's value in the policy has been reset.
+  bool should_start_conc_mark = collector_state()->in_initial_mark_gc();
+
+  // Inner scope for scope based logging, timers, and stats collection
+  {
+    EvacuationInfo evacuation_info;
+
+    if (collector_state()->in_initial_mark_gc()) {
+      // We are about to start a marking cycle, so we increment the
+      // full collection counter.
+      increment_old_marking_cycles_started();
+      _cm->gc_tracer_cm()->set_gc_cause(gc_cause());
+    }
+
+    _gc_tracer_stw->report_yc_type(collector_state()->yc_type());
+
+    GCTraceCPUTime tcpu;
+
+    G1HeapVerifier::G1VerifyType verify_type;
+    FormatBuffer<> gc_string("Pause Young ");
+    if (collector_state()->in_initial_mark_gc()) {
+      gc_string.append("(Concurrent Start)");
+      verify_type = G1HeapVerifier::G1VerifyConcurrentStart;
+    } else if (collector_state()->in_young_only_phase()) {
+      if (collector_state()->in_young_gc_before_mixed()) {
+        gc_string.append("(Prepare Mixed)");
+      } else {
+        gc_string.append("(Normal)");
+      }
+      verify_type = G1HeapVerifier::G1VerifyYoungNormal;
+    } else {
+      gc_string.append("(Mixed)");
+      verify_type = G1HeapVerifier::G1VerifyMixed;
+    }
+    GCTraceTime(Info, gc) tm(gc_string, NULL, gc_cause(), true);
+
+    uint active_workers = AdaptiveSizePolicy::calc_active_workers(workers()->total_workers(),
+                                                                  workers()->active_workers(),
+                                                                  Threads::number_of_non_daemon_threads());
+    active_workers = workers()->update_active_workers(active_workers);
+    log_info(gc,task)("Using %u workers of %u for evacuation", active_workers, workers()->total_workers());
+
+    TraceCollectorStats tcs(g1mm()->incremental_collection_counters());
+    TraceMemoryManagerStats tms(&_memory_manager, gc_cause(),
+                                collector_state()->yc_type() == Mixed /* allMemoryPoolsAffected */);
+
+    G1HeapTransition heap_transition(this);
+    size_t heap_used_bytes_before_gc = used();
+
+    // Don't dynamically change the number of GC threads this early.  A value of
+    // 0 is used to indicate serial work.  When parallel work is done,
+    // it will be set.
+
+    { // Call to jvmpi::post_class_unload_events must occur outside of active GC
+      IsGCActiveMark x;
+
+      gc_prologue(false);
+
+      if (VerifyRememberedSets) {
+        log_info(gc, verify)("[Verifying RemSets before GC]");
+        VerifyRegionRemSetClosure v_cl;
+        heap_region_iterate(&v_cl);
+      }
+
+      _verifier->verify_before_gc(verify_type);
+
+      _verifier->check_bitmaps("GC Start");
+
+#if COMPILER2_OR_JVMCI
+      DerivedPointerTable::clear();
+#endif
+
+      // Please see comment in g1CollectedHeap.hpp and
+      // G1CollectedHeap::ref_processing_init() to see how
+      // reference processing currently works in G1.
+
+      // Enable discovery in the STW reference processor
+      _ref_processor_stw->enable_discovery();
+
+      {
+        // We want to temporarily turn off discovery by the
+        // CM ref processor, if necessary, and turn it back on
+        // on again later if we do. Using a scoped
+        // NoRefDiscovery object will do this.
+        NoRefDiscovery no_cm_discovery(_ref_processor_cm);
+
+        // Forget the current alloc region (we might even choose it to be part
+        // of the collection set!).
+        _allocator->release_mutator_alloc_region();
+
+        // This timing is only used by the ergonomics to handle our pause target.
+        // It is unclear why this should not include the full pause. We will
+        // investigate this in CR 7178365.
+        //
+        // Preserving the old comment here if that helps the investigation:
+        //
+        // The elapsed time induced by the start time below deliberately elides
+        // the possible verification above.
+        double sample_start_time_sec = os::elapsedTime();
+
+        g1_policy()->record_collection_pause_start(sample_start_time_sec);
+
+        if (collector_state()->in_initial_mark_gc()) {
+          concurrent_mark()->pre_initial_mark();
+        }
+
+        g1_policy()->finalize_collection_set(target_pause_time_ms, &_survivor);
+
+        evacuation_info.set_collectionset_regions(collection_set()->region_length());
+
+        // Make sure the remembered sets are up to date. This needs to be
+        // done before register_humongous_regions_with_cset(), because the
+        // remembered sets are used there to choose eager reclaim candidates.
+        // If the remembered sets are not up to date we might miss some
+        // entries that need to be handled.
+        g1_rem_set()->cleanupHRRS();
+
+        register_humongous_regions_with_cset();
+
+        assert(_verifier->check_cset_fast_test(), "Inconsistency in the InCSetState table.");
+
+        // We call this after finalize_cset() to
+        // ensure that the CSet has been finalized.
+        _cm->verify_no_cset_oops();
+
+        if (_hr_printer.is_active()) {
+          G1PrintCollectionSetClosure cl(&_hr_printer);
+          _collection_set.iterate(&cl);
+        }
+
+        // Initialize the GC alloc regions.
+        _allocator->init_gc_alloc_regions(evacuation_info);
+
+        G1ParScanThreadStateSet per_thread_states(this, workers()->active_workers(), collection_set()->young_region_length());
+        pre_evacuate_collection_set();
+
+        // Actually do the work...
+        evacuate_collection_set(&per_thread_states);
+
+        post_evacuate_collection_set(evacuation_info, &per_thread_states);
+
+        const size_t* surviving_young_words = per_thread_states.surviving_young_words();
+        free_collection_set(&_collection_set, evacuation_info, surviving_young_words);
+
+        eagerly_reclaim_humongous_regions();
+
+        record_obj_copy_mem_stats();
+        _survivor_evac_stats.adjust_desired_plab_sz();
+        _old_evac_stats.adjust_desired_plab_sz();
+
+        double start = os::elapsedTime();
+        start_new_collection_set();
+        g1_policy()->phase_times()->record_start_new_cset_time_ms((os::elapsedTime() - start) * 1000.0);
+
+        if (evacuation_failed()) {
+          set_used(recalculate_used());
+          if (_archive_allocator != NULL) {
+            _archive_allocator->clear_used();
+          }
+          for (uint i = 0; i < ParallelGCThreads; i++) {
+            if (_evacuation_failed_info_array[i].has_failed()) {
+              _gc_tracer_stw->report_evacuation_failed(_evacuation_failed_info_array[i]);
+            }
+          }
+        } else {
+          // The "used" of the the collection set have already been subtracted
+          // when they were freed.  Add in the bytes evacuated.
+          increase_used(g1_policy()->bytes_copied_during_gc());
+        }
+
+        if (collector_state()->in_initial_mark_gc()) {
+          // We have to do this before we notify the CM threads that
+          // they can start working to make sure that all the
+          // appropriate initialization is done on the CM object.
+          concurrent_mark()->post_initial_mark();
+          // Note that we don't actually trigger the CM thread at
+          // this point. We do that later when we're sure that
+          // the current thread has completed its logging output.
+        }
+
+        allocate_dummy_regions();
+
+        _allocator->init_mutator_alloc_region();
+
+        {
+          size_t expand_bytes = _heap_sizing_policy->expansion_amount();
+          if (expand_bytes > 0) {
+            size_t bytes_before = capacity();
+            // No need for an ergo logging here,
+            // expansion_amount() does this when it returns a value > 0.
+            double expand_ms;
+            if (!expand(expand_bytes, _workers, &expand_ms)) {
+              // We failed to expand the heap. Cannot do anything about it.
+            }
+            g1_policy()->phase_times()->record_expand_heap_time(expand_ms);
+          }
+        }
+
+        // We redo the verification but now wrt to the new CSet which
+        // has just got initialized after the previous CSet was freed.
+        _cm->verify_no_cset_oops();
+
+        // This timing is only used by the ergonomics to handle our pause target.
+        // It is unclear why this should not include the full pause. We will
+        // investigate this in CR 7178365.
+        double sample_end_time_sec = os::elapsedTime();
+        double pause_time_ms = (sample_end_time_sec - sample_start_time_sec) * MILLIUNITS;
+        size_t total_cards_scanned = g1_policy()->phase_times()->sum_thread_work_items(G1GCPhaseTimes::ScanRS, G1GCPhaseTimes::ScanRSScannedCards);
+        g1_policy()->record_collection_pause_end(pause_time_ms, total_cards_scanned, heap_used_bytes_before_gc);
+
+        evacuation_info.set_collectionset_used_before(collection_set()->bytes_used_before());
+        evacuation_info.set_bytes_copied(g1_policy()->bytes_copied_during_gc());
+
+        if (VerifyRememberedSets) {
+          log_info(gc, verify)("[Verifying RemSets after GC]");
+          VerifyRegionRemSetClosure v_cl;
+          heap_region_iterate(&v_cl);
+        }
+
+        _verifier->verify_after_gc(verify_type);
+        _verifier->check_bitmaps("GC End");
+
+        assert(!_ref_processor_stw->discovery_enabled(), "Postcondition");
+        _ref_processor_stw->verify_no_references_recorded();
+
+        // CM reference discovery will be re-enabled if necessary.
+      }
+
+#ifdef TRACESPINNING
+      ParallelTaskTerminator::print_termination_counts();
+#endif
+
+      gc_epilogue(false);
+    }
+
+    // Print the remainder of the GC log output.
+    if (evacuation_failed()) {
+      log_info(gc)("To-space exhausted");
+    }
+
+    g1_policy()->print_phases();
+    heap_transition.print();
+
+    // It is not yet to safe to tell the concurrent mark to
+    // start as we have some optional output below. We don't want the
+    // output from the concurrent mark thread interfering with this
+    // logging output either.
+
+    _hrm.verify_optional();
+    _verifier->verify_region_sets_optional();
+
+    TASKQUEUE_STATS_ONLY(print_taskqueue_stats());
+    TASKQUEUE_STATS_ONLY(reset_taskqueue_stats());
+
+    print_heap_after_gc();
+    print_heap_regions();
+    trace_heap_after_gc(_gc_tracer_stw);
+
+    // We must call G1MonitoringSupport::update_sizes() in the same scoping level
+    // as an active TraceMemoryManagerStats object (i.e. before the destructor for the
+    // TraceMemoryManagerStats is called) so that the G1 memory pools are updated
+    // before any GC notifications are raised.
+    g1mm()->update_sizes();
+
+    _gc_tracer_stw->report_evacuation_info(&evacuation_info);
+    _gc_tracer_stw->report_tenuring_threshold(_g1_policy->tenuring_threshold());
+    _gc_timer_stw->register_gc_end();
+    _gc_tracer_stw->report_gc_end(_gc_timer_stw->gc_end(), _gc_timer_stw->time_partitions());
+  }
+  // It should now be safe to tell the concurrent mark thread to start
+  // without its logging output interfering with the logging output
+  // that came from the pause.
+
+  if (should_start_conc_mark) {
+    // CAUTION: after the doConcurrentMark() call below,
+    // the concurrent marking thread(s) could be running
+    // concurrently with us. Make sure that anything after
+    // this point does not assume that we are the only GC thread
+    // running. Note: of course, the actual marking work will
+    // not start until the safepoint itself is released in
+    // SuspendibleThreadSet::desynchronize().
+    do_concurrent_mark();
+  }
+
+  return true;
+}

        往下走就是这一步G1Policy::finalize_collection_set,去处理新生代和老年代

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        void G1Policy::finalize_collection_set(double target_pause_time_ms, G1SurvivorRegions* survivor) {
          double time_remaining_ms = _collection_set->finalize_young_part(target_pause_time_ms, survivor);
          _collection_set->finalize_old_part(time_remaining_ms);
        }
        +
        void G1Policy::finalize_collection_set(double target_pause_time_ms, G1SurvivorRegions* survivor) {
+  double time_remaining_ms = _collection_set->finalize_young_part(target_pause_time_ms, survivor);
+  _collection_set->finalize_old_part(time_remaining_ms);
+}

        这里分别调用了两个方法，可以看到剩余时间是往下传的，来看一下具体的方法

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        double G1CollectionSet::finalize_young_part(double target_pause_time_ms, G1SurvivorRegions* survivors) {
          double young_start_time_sec = os::elapsedTime();

          finalize_incremental_building();

          guarantee(target_pause_time_ms > 0.0,
                    "target_pause_time_ms = %1.6lf should be positive", target_pause_time_ms);

          size_t pending_cards = _policy->pending_cards();
          double base_time_ms = _policy->predict_base_elapsed_time_ms(pending_cards);
          double time_remaining_ms = MAX2(target_pause_time_ms - base_time_ms, 0.0);

          log_trace(gc, ergo, cset)("Start choosing CSet. pending cards: " SIZE_FORMAT " predicted base time: %1.2fms remaining time: %1.2fms target pause time: %1.2fms",
                                    pending_cards, base_time_ms, time_remaining_ms, target_pause_time_ms);

          // The young list is laid with the survivor regions from the previous
          // pause are appended to the RHS of the young list, i.e.
          //   [Newly Young Regions ++ Survivors from last pause].

          uint survivor_region_length = survivors->length();
          uint eden_region_length = _g1h->eden_regions_count();
          init_region_lengths(eden_region_length, survivor_region_length);

          verify_young_cset_indices();

          // Clear the fields that point to the survivor list - they are all young now.
          survivors->convert_to_eden();

          _bytes_used_before = _inc_bytes_used_before;
          time_remaining_ms = MAX2(time_remaining_ms - _inc_predicted_elapsed_time_ms, 0.0);

          log_trace(gc, ergo, cset)("Add young regions to CSet. eden: %u regions, survivors: %u regions, predicted young region time: %1.2fms, target pause time: %1.2fms",
                                    eden_region_length, survivor_region_length, _inc_predicted_elapsed_time_ms, target_pause_time_ms);

          // The number of recorded young regions is the incremental
          // collection set's current size
          set_recorded_rs_lengths(_inc_recorded_rs_lengths);

          double young_end_time_sec = os::elapsedTime();
          phase_times()->record_young_cset_choice_time_ms((young_end_time_sec - young_start_time_sec) * 1000.0);

          return time_remaining_ms;
        }
        +
        double G1CollectionSet::finalize_young_part(double target_pause_time_ms, G1SurvivorRegions* survivors) {
+  double young_start_time_sec = os::elapsedTime();
+
+  finalize_incremental_building();
+
+  guarantee(target_pause_time_ms > 0.0,
+            "target_pause_time_ms = %1.6lf should be positive", target_pause_time_ms);
+
+  size_t pending_cards = _policy->pending_cards();
+  double base_time_ms = _policy->predict_base_elapsed_time_ms(pending_cards);
+  double time_remaining_ms = MAX2(target_pause_time_ms - base_time_ms, 0.0);
+
+  log_trace(gc, ergo, cset)("Start choosing CSet. pending cards: " SIZE_FORMAT " predicted base time: %1.2fms remaining time: %1.2fms target pause time: %1.2fms",
+                            pending_cards, base_time_ms, time_remaining_ms, target_pause_time_ms);
+
+  // The young list is laid with the survivor regions from the previous
+  // pause are appended to the RHS of the young list, i.e.
+  //   [Newly Young Regions ++ Survivors from last pause].
+
+  uint survivor_region_length = survivors->length();
+  uint eden_region_length = _g1h->eden_regions_count();
+  init_region_lengths(eden_region_length, survivor_region_length);
+
+  verify_young_cset_indices();
+
+  // Clear the fields that point to the survivor list - they are all young now.
+  survivors->convert_to_eden();
+
+  _bytes_used_before = _inc_bytes_used_before;
+  time_remaining_ms = MAX2(time_remaining_ms - _inc_predicted_elapsed_time_ms, 0.0);
+
+  log_trace(gc, ergo, cset)("Add young regions to CSet. eden: %u regions, survivors: %u regions, predicted young region time: %1.2fms, target pause time: %1.2fms",
+                            eden_region_length, survivor_region_length, _inc_predicted_elapsed_time_ms, target_pause_time_ms);
+
+  // The number of recorded young regions is the incremental
+  // collection set's current size
+  set_recorded_rs_lengths(_inc_recorded_rs_lengths);
+
+  double young_end_time_sec = os::elapsedTime();
+  phase_times()->record_young_cset_choice_time_ms((young_end_time_sec - young_start_time_sec) * 1000.0);
+
+  return time_remaining_ms;
+}

        下面是老年代的部分

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        void G1CollectionSet::finalize_old_part(double time_remaining_ms) {
          double non_young_start_time_sec = os::elapsedTime();
          double predicted_old_time_ms = 0.0;

          if (collector_state()->in_mixed_phase()) {
            cset_chooser()->verify();
            const uint min_old_cset_length = _policy->calc_min_old_cset_length();
            const uint max_old_cset_length = _policy->calc_max_old_cset_length();

            uint expensive_region_num = 0;
            bool check_time_remaining = _policy->adaptive_young_list_length();

            HeapRegion* hr = cset_chooser()->peek();
            while (hr != NULL) {
              if (old_region_length() >= max_old_cset_length) {
                // Added maximum number of old regions to the CSet.
                log_debug(gc, ergo, cset)("Finish adding old regions to CSet (old CSet region num reached max). old %u regions, max %u regions",
                                          old_region_length(), max_old_cset_length);
                break;
              }

              // Stop adding regions if the remaining reclaimable space is
              // not above G1HeapWastePercent.
              size_t reclaimable_bytes = cset_chooser()->remaining_reclaimable_bytes();
              double reclaimable_percent = _policy->reclaimable_bytes_percent(reclaimable_bytes);
              double threshold = (double) G1HeapWastePercent;
              if (reclaimable_percent <= threshold) {
                // We've added enough old regions that the amount of uncollected
                // reclaimable space is at or below the waste threshold. Stop
                // adding old regions to the CSet.
                log_debug(gc, ergo, cset)("Finish adding old regions to CSet (reclaimable percentage not over threshold). "
                                          "old %u regions, max %u regions, reclaimable: " SIZE_FORMAT "B (%1.2f%%) threshold: " UINTX_FORMAT "%%",
                                          old_region_length(), max_old_cset_length, reclaimable_bytes, reclaimable_percent, G1HeapWastePercent);
                break;
              }

              double predicted_time_ms = predict_region_elapsed_time_ms(hr);
              if (check_time_remaining) {
                if (predicted_time_ms > time_remaining_ms) {
                  // Too expensive for the current CSet.

                  if (old_region_length() >= min_old_cset_length) {
                    // We have added the minimum number of old regions to the CSet,
                    // we are done with this CSet.
                    log_debug(gc, ergo, cset)("Finish adding old regions to CSet (predicted time is too high). "
                                              "predicted time: %1.2fms, remaining time: %1.2fms old %u regions, min %u regions",
                                              predicted_time_ms, time_remaining_ms, old_region_length(), min_old_cset_length);
                    break;
                  }

                  // We'll add it anyway given that we haven't reached the
                  // minimum number of old regions.
                  expensive_region_num += 1;
                }
              } else {
                if (old_region_length() >= min_old_cset_length) {
                  // In the non-auto-tuning case, we'll finish adding regions
                  // to the CSet if we reach the minimum.

                  log_debug(gc, ergo, cset)("Finish adding old regions to CSet (old CSet region num reached min). old %u regions, min %u regions",
                                            old_region_length(), min_old_cset_length);
                  break;
                }
              }

              // We will add this region to the CSet.
              time_remaining_ms = MAX2(time_remaining_ms - predicted_time_ms, 0.0);
              predicted_old_time_ms += predicted_time_ms;
              cset_chooser()->pop(); // already have region via peek()
              _g1h->old_set_remove(hr);
              add_old_region(hr);

              hr = cset_chooser()->peek();
            }
            if (hr == NULL) {
              log_debug(gc, ergo, cset)("Finish adding old regions to CSet (candidate old regions not available)");
            }

            if (expensive_region_num > 0) {
              // We print the information once here at the end, predicated on
              // whether we added any apparently expensive regions or not, to
              // avoid generating output per region.
              log_debug(gc, ergo, cset)("Added expensive regions to CSet (old CSet region num not reached min)."
                                        "old: %u regions, expensive: %u regions, min: %u regions, remaining time: %1.2fms",
                                        old_region_length(), expensive_region_num, min_old_cset_length, time_remaining_ms);
            }

            cset_chooser()->verify();
          }

          stop_incremental_building();

          log_debug(gc, ergo, cset)("Finish choosing CSet. old: %u regions, predicted old region time: %1.2fms, time remaining: %1.2f",
                                    old_region_length(), predicted_old_time_ms, time_remaining_ms);

          double non_young_end_time_sec = os::elapsedTime();
          phase_times()->record_non_young_cset_choice_time_ms((non_young_end_time_sec - non_young_start_time_sec) * 1000.0);

          QuickSort::sort(_collection_set_regions, _collection_set_cur_length, compare_region_idx, true);
        }
        -

        上面第三行是个判断，当前是否是 mixed 回收阶段，如果不是的话其实是没有老年代什么事的，所以可以看到代码基本是从这个 if 判断
        if (collector_state()->in_mixed_phase()) {开始往下走的
        先写到这，偏向于做笔记用，有错轻拍

        +
        void G1CollectionSet::finalize_old_part(double time_remaining_ms) {
+  double non_young_start_time_sec = os::elapsedTime();
+  double predicted_old_time_ms = 0.0;
+
+  if (collector_state()->in_mixed_phase()) {
+    cset_chooser()->verify();
+    const uint min_old_cset_length = _policy->calc_min_old_cset_length();
+    const uint max_old_cset_length = _policy->calc_max_old_cset_length();
+
+    uint expensive_region_num = 0;
+    bool check_time_remaining = _policy->adaptive_young_list_length();
+
+    HeapRegion* hr = cset_chooser()->peek();
+    while (hr != NULL) {
+      if (old_region_length() >= max_old_cset_length) {
+        // Added maximum number of old regions to the CSet.
+        log_debug(gc, ergo, cset)("Finish adding old regions to CSet (old CSet region num reached max). old %u regions, max %u regions",
+                                  old_region_length(), max_old_cset_length);
+        break;
+      }
+
+      // Stop adding regions if the remaining reclaimable space is
+      // not above G1HeapWastePercent.
+      size_t reclaimable_bytes = cset_chooser()->remaining_reclaimable_bytes();
+      double reclaimable_percent = _policy->reclaimable_bytes_percent(reclaimable_bytes);
+      double threshold = (double) G1HeapWastePercent;
+      if (reclaimable_percent <= threshold) {
+        // We've added enough old regions that the amount of uncollected
+        // reclaimable space is at or below the waste threshold. Stop
+        // adding old regions to the CSet.
+        log_debug(gc, ergo, cset)("Finish adding old regions to CSet (reclaimable percentage not over threshold). "
+                                  "old %u regions, max %u regions, reclaimable: " SIZE_FORMAT "B (%1.2f%%) threshold: " UINTX_FORMAT "%%",
+                                  old_region_length(), max_old_cset_length, reclaimable_bytes, reclaimable_percent, G1HeapWastePercent);
+        break;
+      }
+
+      double predicted_time_ms = predict_region_elapsed_time_ms(hr);
+      if (check_time_remaining) {
+        if (predicted_time_ms > time_remaining_ms) {
+          // Too expensive for the current CSet.
+
+          if (old_region_length() >= min_old_cset_length) {
+            // We have added the minimum number of old regions to the CSet,
+            // we are done with this CSet.
+            log_debug(gc, ergo, cset)("Finish adding old regions to CSet (predicted time is too high). "
+                                      "predicted time: %1.2fms, remaining time: %1.2fms old %u regions, min %u regions",
+                                      predicted_time_ms, time_remaining_ms, old_region_length(), min_old_cset_length);
+            break;
+          }
+
+          // We'll add it anyway given that we haven't reached the
+          // minimum number of old regions.
+          expensive_region_num += 1;
+        }
+      } else {
+        if (old_region_length() >= min_old_cset_length) {
+          // In the non-auto-tuning case, we'll finish adding regions
+          // to the CSet if we reach the minimum.
+
+          log_debug(gc, ergo, cset)("Finish adding old regions to CSet (old CSet region num reached min). old %u regions, min %u regions",
+                                    old_region_length(), min_old_cset_length);
+          break;
+        }
+      }
+
+      // We will add this region to the CSet.
+      time_remaining_ms = MAX2(time_remaining_ms - predicted_time_ms, 0.0);
+      predicted_old_time_ms += predicted_time_ms;
+      cset_chooser()->pop(); // already have region via peek()
+      _g1h->old_set_remove(hr);
+      add_old_region(hr);
+
+      hr = cset_chooser()->peek();
+    }
+    if (hr == NULL) {
+      log_debug(gc, ergo, cset)("Finish adding old regions to CSet (candidate old regions not available)");
+    }
+
+    if (expensive_region_num > 0) {
+      // We print the information once here at the end, predicated on
+      // whether we added any apparently expensive regions or not, to
+      // avoid generating output per region.
+      log_debug(gc, ergo, cset)("Added expensive regions to CSet (old CSet region num not reached min)."
+                                "old: %u regions, expensive: %u regions, min: %u regions, remaining time: %1.2fms",
+                                old_region_length(), expensive_region_num, min_old_cset_length, time_remaining_ms);
+    }
+
+    cset_chooser()->verify();
+  }
+
+  stop_incremental_building();
+
+  log_debug(gc, ergo, cset)("Finish choosing CSet. old: %u regions, predicted old region time: %1.2fms, time remaining: %1.2f",
+                            old_region_length(), predicted_old_time_ms, time_remaining_ms);
+
+  double non_young_end_time_sec = os::elapsedTime();
+  phase_times()->record_non_young_cset_choice_time_ms((non_young_end_time_sec - non_young_start_time_sec) * 1000.0);
+
+  QuickSort::sort(_collection_set_regions, _collection_set_cur_length, compare_region_idx, true);
+}
        +

        上面第三行是个判断，当前是否是 mixed 回收阶段，如果不是的话其实是没有老年代什么事的，所以可以看到代码基本是从这个 if 判断
        if (collector_state()->in_mixed_phase()) {开始往下走的
        先写到这，偏向于做笔记用，有错轻拍

        @@ -324,7 +902,7 @@
        G1收集器概述
      • -
        聊聊我刚学会的应用诊断方法
        +
        聊聊 Dubbo 的 SPI 续之自适应拓展
      • Apollo 的 value 注解是怎么自动更新的
        diff --git a/2019/12/10/Redis-Part-1/index.html b/2019/12/10/Redis-Part-1/index.html index 44255a8a65..09f5d486e4 100644 --- a/2019/12/10/Redis-Part-1/index.html +++ b/2019/12/10/Redis-Part-1/index.html @@ -4,7 +4,7 @@ - + @@ -32,8 +32,9 @@ + - + @@ -231,13 +232,6 @@ - - - - - Edited on - - @@ -303,11 +297,15 @@

        加锁

        原先我对 redis 锁的概念就是加锁使用 setnx，解锁使用 lua 脚本，但是 setnx 具体是啥，lua 脚本是啥不是很清楚
        首先简单思考下这个问题，首先为啥不是先 get 一下 key 存不存在，然后再 set 一个 key value，因为加锁这个操作我们是要保证两点，一个是不能中途被打断，也就是说要原子性，如果是先 get 一下 key，如果不存在再 set 值的话，那就不是原子操作了；第二个是可不可以直接 set 值呢，显然不行，锁要保证唯一性，有且只能有一个线程或者其他应用单位获得该锁，正好 setnx 给了我们这种原子命令

        然后是 setnx 的键和值分别是啥，键比较容易想到是要锁住的资源，比如 user_id, 这里有个我自己之前比较容易陷进去的误区，但是这个误区后
        面再说，这里其实是把user_id 作为要锁住的资源，在我获得锁的时候别的线程不允许操作，以此保证业务的正确性，不会被多个线程同时修改，确定了键，再来看看值是啥，其实原先我认为值是啥都没关系，我只要锁住了，光键就够我用了，但是考虑下多个线程的问题，如果我这个线程加了锁，然后我因为 gc 停顿等原因卡死了，这个时候redis 的锁或者说就是 redis 的缓存已经过期了，这时候另一个线程获得锁成功，然后我这个线程又活过来了，然后我就仍然认为我拿着锁，我去对数据进行修改或者释放锁，是不是就出现问题了，所以是不是我们还需要一个东西来区分这个锁是哪个线程加的，所以我们可以将值设置成为一个线程独有识别的值，至少在相对长的一段时间内不会重复。

        上面其实还有两个问题，一个是当 gc 超时时，我这个线程如何知道我手里的锁已经过期了，一种方法是我在加好锁之后就维护一个超时时间，这里其实还有个问题，不过跟第二个问题相关，就一起说了，就是设置超时时间，有些对于不是锁的 redis 缓存操作可以是先设置好值，然后在设置过期时间，那么这就又有上面说到的不是原子性的问题，那么就需要在同一条指令里把超时时间也设置了，幸好 redis 提供了这种支持

        -
        1
        SET resource_name my_random_value NX PX 30000
        +
        SET resource_name my_random_value NX PX 30000

        这里借鉴一下解释下，resource_name就是 key，代表要锁住的东西，my_random_value就是识别我这个线程的，NX代表只有在不存在的时候才设置，然后PX 30000表示超时时间是 30秒自动过期

        PS：记录下我原先有的一个误区，是不是要用 key 来区分加锁的线程，这样只有一个用处，就是自身线程可以识别是否是自己加的锁，但是最大的问题是别的线程不知道，其实这个用户的出发点是我在担心前面提过的一个问题，就是当 gc 停顿后，我要去判断当前的这个锁是否是我加的，还有就是当释放锁的时候，如果保证不会错误释放了其他线程加的锁，但是这样附带很多其他问题，最大的就是其他线程怎么知道能不能加这个锁。

        解锁

        当线程在锁过期之前就处理完了业务逻辑，那就可以提前释放这个锁，那么提前释放要怎么操作，直接del key显然是不行的，因为这样就是我前面想用线程随机值加资源名作为锁的初衷，我不能去释放别的线程加的锁，那么我要怎么办呢，先 get 一下看是不是我的？那又变成非原子的操作了，幸好redis 也考虑到了这个问题，给了lua 脚本来操作这种

        -
        1
        2
        3
        4
        5
        if redis.call("get",KEYS[1]) == ARGV[1] then
            return redis.call("del",KEYS[1])
        else
            return 0
        end
        +
        if redis.call("get",KEYS[1]) == ARGV[1] then
+    return redis.call("del",KEYS[1])
+else
+    return 0
+end

        这里的KEYS[1]就是前面加锁的resource_name,ARGV[1]就是线程的随机值my_random_value

        多节点

        前面说的其实是单节点 redis 作为分布式锁的情况，那么当我们的 redis 有多节点的情况呢，如果多节点下处于加锁或者解锁或者锁有效情况下
        redis 的某个节点宕掉了怎么办，这里就有一些需要思考的地方，是否单独搞一个单节点的 redis作为分布式锁专用的，但是如果这个单节点的挂了呢，还有就是成本问题，所以我们需要一个多节点的分布式锁方案
        这里就引出了开头说到的redlock，这个可是 redis的作者写的, 他的加锁过程是分以下几步去做这个事情

          @@ -455,7 +453,7 @@
          -
          1. 1. 加锁
          2. 2. 解锁
          3. 3. 多节点
          +
          1. 1. 加锁
          2. 2. 解锁
          3. 3. 多节点
          diff --git a/2019/12/18/1Q84读后感/index.html b/2019/12/18/1Q84读后感/index.html index 5679d0ef50..314a42a8e4 100644 --- a/2019/12/18/1Q84读后感/index.html +++ b/2019/12/18/1Q84读后感/index.html @@ -4,7 +4,7 @@ - + @@ -32,6 +32,7 @@ + diff --git a/2019/12/21/聊聊Java中的单例模式/index.html b/2019/12/21/聊聊Java中的单例模式/index.html index 2cbc00faf4..567a9772c4 100644 --- a/2019/12/21/聊聊Java中的单例模式/index.html +++ b/2019/12/21/聊聊Java中的单例模式/index.html @@ -4,7 +4,7 @@ - + @@ -32,16 +32,14 @@ + - - + - - - + @@ -299,14 +297,63 @@

          这是个 Java 面试的高频问题，我也遇到过，以往都是觉得这类题没意思，网上一搜一大堆，也不愿意记，其实说回来，主要还是没静下心来好好去理解，今天无意中看到一个课程，基本帮我把一些疑惑的点讲清楚了，首先单例是啥意思，这个其实是有范围一说，比如我起了个Spring Boot应用，在这个应用范围内，我的常规 bean 是单例的，意味着 getBean 的时候其实永远只会拿到那一个对象，那要怎么来写一个单例呢，首先就是传说中的饿汉模式，也是最简单的

          -

          饿汉模式

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          14
          public class Singleton1 {
              // 首先，将构造方法变成私有的
              private Singleton1() {};
              // 创建私有静态实例，这样第一次使用的时候就会进行创建
              private static Singleton instance = new Singleton1();

              // 使用这个对象都是通过这个 getInstance 来获取
              public static Singleton1 getInstance() {
                  return instance;
              }
              // 瞎写一个静态方法。这里想说的是，如果我们只是要调用 Singleton.getDate(...)，
              // 本来是不想要生成 Singleton 实例的，不过没办法，已经生成了
              public static Date getDate(String mode) {return new Date();}
          }
          +

          饿汉模式

          public class Singleton1 {
+    // 首先，将构造方法变成私有的
+    private Singleton1() {};
+    // 创建私有静态实例，这样第一次使用的时候就会进行创建
+    private static Singleton instance = new Singleton1();
+
+    // 使用这个对象都是通过这个 getInstance 来获取
+    public static Singleton1 getInstance() {
+        return instance;
+    }
+    // 瞎写一个静态方法。这里想说的是，如果我们只是要调用 Singleton.getDate(...)，
+    // 本来是不想要生成 Singleton 实例的，不过没办法，已经生成了
+    public static Date getDate(String mode) {return new Date();}
+}

          上面借鉴了一些代码，其实这是最基本，也不会错的方法，但是正如其中getDate方法里说的问题，有时候并没有想那这个对象，但是因为我调用了这个类的静态方法，导致对象已经生成了，可能这也是饿汉模式名字的来由，不管三七二十一给你生成个单例就完事了，不管有没有用，但是这种个人觉得也没啥大问题，如果是面试的话最好说出来它的缺点

          -

          饱汉模式

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          21
          public class Singleton2 {
              // 首先，也是先堵死 new Singleton() 这条路,将构造方法变成私有
              private Singleton2() {}
              // 和饿汉模式相比，这边不需要先实例化出来，注意这里的 volatile，它是必须的
              private static volatile Singleton2 instance = null;

              private int m = 9;

              public static Singleton getInstance() {
                  if (instance == null) {
                      // 加锁
                      synchronized (Singleton2.class) {
                          // 这一次判断也是必须的，不然会有并发问题
                          if (instance == null) {
                              instance = new Singleton2();
                          }
                      }
                  }
                  return instance;
              }
          }
          +

          饱汉模式

          public class Singleton2 {
+    // 首先，也是先堵死 new Singleton() 这条路,将构造方法变成私有
+    private Singleton2() {}
+    // 和饿汉模式相比，这边不需要先实例化出来，注意这里的 volatile，它是必须的
+    private static volatile Singleton2 instance = null;
+
+    private int m = 9;
+
+    public static Singleton getInstance() {
+        if (instance == null) {
+            // 加锁
+            synchronized (Singleton2.class) {
+                // 这一次判断也是必须的，不然会有并发问题
+                if (instance == null) {
+                    instance = new Singleton2();
+                }
+            }
+        }
+        return instance;
+    }
+}

          这里容易错的有三点，理解了其实就比较好记了

          第一点，为啥不在 getInstance 上整个代码块加 synchronized，这个其实比较容易理解，就是锁的力度太大，性能太差了，这点其实也要去理解，可以举个夸张的例子，比如我一个电商的服务，如果为了避免一个人的订单出现问题，是不是可以从请求入口就把他锁住，到请求结束释放，那么里面做的事情都有保障，然而这显然不可能，因为我们想要这种竞态条件抢占资源的时间尽量减少，防止其他线程等待。
          第二点，为啥synchronized之已经检查了 instance == null,还要在里面再检查一次，这个有个术语，叫 double check lock,但是为啥要这么做呢，其实很简单，想象当有两个线程，都过了第一步为空判断，这个时候只有一个线程能拿到这个锁，另一个线程就等待了，如果不再判断一次，那么第一个线程新建完对象释放锁之后，第二个线程又能拿到锁，再去创建一个对象。
          第三点，为啥要volatile关键字，原先对它的理解是它修饰的变量在 JMM 中能及时将变量值写到主存中，但是它还有个很重要的作用，就是防止指令重排序，instance = new Singleton();这行代码其实在底层是分成三条指令执行的，第一条是在堆上申请了一块内存放这个对象，但是对象的字段啥的都还是默认值，第二条是设置对象的值，比如上面的 m 是 9，然后第三条是将这个对象和虚拟机栈上的指针建立引用关联，那么如果我不用volatile关键字，这三条指令就有可能出现重排，比如变成了 1-3-2 这种顺序，当执行完第二步时，有个线程来访问这个对象了，先判断是不是空，发现不是空的，就拿去直接用了，是不是就出现问题了，所以这个volatile也是不可缺少的

          -

          嵌套类

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          public class Singleton3 {

              private Singleton3() {}
              // 主要是使用了 嵌套类可以访问外部类的静态属性和静态方法 的特性
              private static class Holder {
                  private static Singleton3 instance = new Singleton3();
              }
              public static Singleton3 getInstance() {
                  return Holder.instance;
              }
          }
          +

          嵌套类

          public class Singleton3 {
+
+    private Singleton3() {}
+    // 主要是使用了 嵌套类可以访问外部类的静态属性和静态方法 的特性
+    private static class Holder {
+        private static Singleton3 instance = new Singleton3();
+    }
+    public static Singleton3 getInstance() {
+        return Holder.instance;
+    }
+}

          这个我个人感觉是饿汉模式的升级版，可以在调用getInstance的时候去实例化对象，也是比较推荐的

          -

          枚举单例

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          public enum Singleton {
              INSTANCE;
              
              public void doSomething(){
                  //todo doSomething
              }
          }
          +

          枚举单例

          public enum Singleton {
+    INSTANCE;
+    
+    public void doSomething(){
+        //todo doSomething
+    }
+}

          枚举很特殊，它在类加载的时候会初始化里面的所有的实例，而且 JVM 保证了它们不会再被实例化，所以它天生就是单例的。

          @@ -440,7 +487,7 @@
          -
          1. 1. 饿汉模式
          2. 2. 饱汉模式
          3. 3. 嵌套类
          4. 4. 枚举单例
          +
          1. 1. 饿汉模式
          2. 2. 饱汉模式
          3. 3. 嵌套类
          4. 4. 枚举单例
          diff --git a/2019/12/26/redis数据结构介绍/index.html b/2019/12/26/redis数据结构介绍/index.html index 107d387236..5a9194d8b3 100644 --- a/2019/12/26/redis数据结构介绍/index.html +++ b/2019/12/26/redis数据结构介绍/index.html @@ -4,7 +4,7 @@ - + @@ -32,20 +32,14 @@ + - + - - + - - - - - - @@ -239,13 +233,6 @@ - - - - - Edited on - - @@ -313,14 +300,73 @@

          redis是现在服务端很常用的缓存中间件，其实原来还有memcache之类的竞品，但是现在貌似 redis 快一统江湖，这里当然不是在吹，只是个人角度的一个感觉，不权威只是主观感觉。
          redis 主要有五种数据结构，Strings，Lists，Sets，Hashes，Sorted Sets，这五种数据结构先简单介绍下，Strings类型的其实就是我们最常用的 key-value，实际开发中也会用的最多；Lists是列表，这个有些会用来做队列，因为 redis 目前常用的版本支持丰富的列表操作；还有是Sets集合，这个主要的特点就是集合中元素不重复，可以用在有这类需求的场景里；Hashes是叫散列，类似于 Python 中的字典结构；还有就是Sorted Sets这个是个有序集合；一眼看这些其实没啥特别的，除了最后这个有序集合，不过去了解背后的实现方式还是比较有意思的。

          SDS 简单动态字符串

          先从Strings开始说，了解过 C 语言的应该知道，C 语言中的字符串其实是个 char[] 字符数组，redis 也不例外，只是最开始的版本就对这个做了一丢丢的优化，而正是这一丢丢的优化，让这个 redis 的使用效率提升了数倍

          -
          1
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          8
          struct sdshdr {
              // 字符串长度
              int len;
              // 字符串空余字符数
              int free;
              // 字符串内容
              char buf[];
          };
          +
          struct sdshdr {
+    // 字符串长度
+    int len;
+    // 字符串空余字符数
+    int free;
+    // 字符串内容
+    char buf[];
+};

          这里引用了 redis 在 github 上最早的 2.2 版本的代码，代码路径是https://github.com/antirez/redis/blob/2.2/src/sds.h,可以看到这个结构体里只有仨元素，两个 int 型和一个 char 型数组，两个 int 型其实就是我说的优化，因为 C 语言本身的字符串数组，有两个问题，一个是要知道它实际已被占用的长度，需要去遍历这个数组，第二个就是比较容易踩坑的是遍历的时候要注意它有个以\0作为结尾的特点；通过上面的两个 int 型参数，一个是知道字符串目前的长度，一个是知道字符串还剩余多少位空间，这样子坐着两个操作从 O(N)简化到了O(1)了，还有第二个 free 还有个比较重要的作用就是能防止 C 字符串的溢出问题，在存储之前可以先判断 free 长度，如果长度不够就先扩容了，先介绍到这，这个系列可以写蛮多的，慢慢介绍吧

          链表

          链表是比较常见的数据结构了，但是因为 redis 是用 C 写的，所以在不依赖第三方库的情况下只能自己写一个了，redis 的链表是个有头的链表，而且是无环的，具体的结构我也找了 github 上最早版本的代码

          -
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          typedef struct listNode {
              // 前置节点
              struct listNode *prev;
              // 后置节点
              struct listNode *next;
              // 值
              void *value;
          } listNode;

          typedef struct list {
              // 链表表头
              listNode *head;
              // 当前节点，也可以说是最后节点
              listNode *tail;
              // 节点复制函数
              void *(*dup)(void *ptr);
              // 节点值释放函数
              void (*free)(void *ptr);
              // 节点值比较函数
              int (*match)(void *ptr, void *key);
              // 链表包含的节点数量
              unsigned int len;
          } list;
          +
          typedef struct listNode {
+    // 前置节点
+    struct listNode *prev;
+    // 后置节点
+    struct listNode *next;
+    // 值
+    void *value;
+} listNode;
+
+typedef struct list {
+    // 链表表头
+    listNode *head;
+    // 当前节点，也可以说是最后节点
+    listNode *tail;
+    // 节点复制函数
+    void *(*dup)(void *ptr);
+    // 节点值释放函数
+    void (*free)(void *ptr);
+    // 节点值比较函数
+    int (*match)(void *ptr, void *key);
+    // 链表包含的节点数量
+    unsigned int len;
+} list;

          代码地址是这个https://github.com/antirez/redis/blob/2.2/src/adlist.h
          可以看下节点是由listNode承载的，包括值和一个指向前节点跟一个指向后一节点的两个指针，然后值是 void 指针类型，所以可以承载不同类型的值
          然后是 list结构用来承载一个链表，包含了表头，和表尾，复制函数，释放函数和比较函数，还有链表长度，因为包含了前两个节点，找到表尾节点跟表头都是 O(1)的时间复杂度，还有节点数量，其实这个跟 SDS 是同一个做法，就是空间换时间，这也是写代码里比较常见的做法，以此让一些高频的操作提速。

          字典

          字典也是个常用的数据结构，其实只是叫法不同，数据结构中叫 hash 散列，Java 中叫 Map，PHP 中是数组 array，Python 中也叫字典 dict，因为纯 C 语言本身不带这些数据结构，所以这也是个痛并快乐着的过程，享受 C 语言的高性能的同时也要接受它只提供了语言的基本功能的现实，各种轮子都需要自己造，redis 同样实现了自己的字典
          下面来看看代码

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          typedef struct dictEntry {
              void *key;
              void *val;
              struct dictEntry *next;
          } dictEntry;

          typedef struct dictType {
              unsigned int (*hashFunction)(const void *key);
              void *(*keyDup)(void *privdata, const void *key);
              void *(*valDup)(void *privdata, const void *obj);
              int (*keyCompare)(void *privdata, const void *key1, const void *key2);
              void (*keyDestructor)(void *privdata, void *key);
              void (*valDestructor)(void *privdata, void *obj);
          } dictType;

          /* This is our hash table structure. Every dictionary has two of this as we
           * implement incremental rehashing, for the old to the new table. */
          typedef struct dictht {
              dictEntry **table;
              unsigned long size;
              unsigned long sizemask;
              unsigned long used;
          } dictht;

          typedef struct dict {
              dictType *type;
              void *privdata;
              dictht ht[2];
              int rehashidx; /* rehashing not in progress if rehashidx == -1 */
              int iterators; /* number of iterators currently running */
          } dict;
          -

          看了下这个 2.2 版本的代码跟最新版的其实也差的不是很多，所以还是照旧用老代码，可以看到上面四个结构体中，其实只有三个是存储数据用的，dictType 是用来放操作函数的，那么三个存放数据的结构体分别是干嘛的，这时候感觉需要一个图来说明比较好，稍等，我去画个图~

          这个图看着应该比较清楚这些都是用来干嘛的了，dict 是我们的主体结构，它有一个指向 dictType 的指针，这里面包含了字典的操作函数，然后是一个私有数据指针，接下来是一个 dictht 的数组，包含两个dictht，这个就是用来存数据的了，然后是 rehashidx 表示重哈希的状态，当是-1 的时候表示当前没有重哈希，iterators 表示正在遍历的迭代器的数量。
          首先说说为啥需要有两个 dictht，这是因为字典 dict 这个数据结构随着数据量的增减，会需要在中途做扩容或者缩容操作，如果只有一个的话，对它进行扩容缩容时会影响正常的访问和修改操作，或者说保证正常查询，修改的正确性会比较复杂，并且因为需要高效利用空间，不能一下子申请一个非常大的空间来存很少的数据。当 dict 中 dictht 中的数据量超过 size 的时候负载就超过了 1，就需要进行扩容，这里的其实跟 Java 中的 HashMap 比较类似，超过一定的负载之后进行扩容。这里为啥 size 会超过 1 呢，可能有部分不了解这类结构的同学会比较奇怪，其实就是上图中画的，在数据结构中对于散列的冲突有几类解决方法，比如转换成链表，二次散列，找下个空槽等，这里就使用了链表法，或者说拉链法。当一个新元素通过 hashFunction 得出的 key 跟 sizemask 取模之后的值相同了，那就将其放在原来的节点之前，变成链表挂在数组 dictht.table下面，放在原有节点前是考虑到可能会优先访问。
          忘了说明下 dictht 跟 dictEntry 的关系了，dictht 就是个哈希表，它里面是个dictEntry 的二维数组，而 dictEntry 是个包含了 key-value 结构之外还有一个 next 指针，因此可以将哈希冲突的以链表的形式保存下来。
          在重点说下重哈希，可能同样写 Java 的同学对这个比较有感觉，跟 HashMap 一样，会以 2 的 N 次方进行扩容，那么扩容的方法就会比较简单，每个键重哈希要不就在原来这个槽，要不就在原来的槽加原 dictht.size 的位置；然后是重头戏，具体是怎么做扩容呢，其实这里就把第二个 ht 用上了，其实这两个hashtable 的具体作用有点类似于 jvm 中的两个 survival 区，但是又不全一样，因为 redis 在扩容的时候是采用的渐进式地重哈希，什么叫渐进式的呢，就是它不是像 jvm 那种标记复制的模式直接将一个 eden 区和原来的 survival 区存活的对象复制到另一个 survival 区，而是在每一次添加，删除，查找或者更新操作时，都会额外的帮忙搬运一部分的原 dictht 中的数据，这里会根据 rehashidx 的值来判断，如果是-1 表示并没有在重哈希中，如果是 0 表示开始重哈希了，然后rehashidx 还会随着每次的帮忙搬运往上加，但全部被搬运完成后 rehashidx 又变回了-1，又可以扯到Java 中的 Concurrent HashMap, 他在扩容的时候也使用了类似的操作。

          +
          typedef struct dictEntry {
+    void *key;
+    void *val;
+    struct dictEntry *next;
+} dictEntry;
+
+typedef struct dictType {
+    unsigned int (*hashFunction)(const void *key);
+    void *(*keyDup)(void *privdata, const void *key);
+    void *(*valDup)(void *privdata, const void *obj);
+    int (*keyCompare)(void *privdata, const void *key1, const void *key2);
+    void (*keyDestructor)(void *privdata, void *key);
+    void (*valDestructor)(void *privdata, void *obj);
+} dictType;
+
+/* This is our hash table structure. Every dictionary has two of this as we
+ * implement incremental rehashing, for the old to the new table. */
+typedef struct dictht {
+    dictEntry **table;
+    unsigned long size;
+    unsigned long sizemask;
+    unsigned long used;
+} dictht;
+
+typedef struct dict {
+    dictType *type;
+    void *privdata;
+    dictht ht[2];
+    int rehashidx; /* rehashing not in progress if rehashidx == -1 */
+    int iterators; /* number of iterators currently running */
+} dict;
          +

          看了下这个 2.2 版本的代码跟最新版的其实也差的不是很多，所以还是照旧用老代码，可以看到上面四个结构体中，其实只有三个是存储数据用的，dictType 是用来放操作函数的，那么三个存放数据的结构体分别是干嘛的，这时候感觉需要一个图来说明比较好，稍等，我去画个图~

          这个图看着应该比较清楚这些都是用来干嘛的了，dict 是我们的主体结构，它有一个指向 dictType 的指针，这里面包含了字典的操作函数，然后是一个私有数据指针，接下来是一个 dictht 的数组，包含两个dictht，这个就是用来存数据的了，然后是 rehashidx 表示重哈希的状态，当是-1 的时候表示当前没有重哈希，iterators 表示正在遍历的迭代器的数量。
          首先说说为啥需要有两个 dictht，这是因为字典 dict 这个数据结构随着数据量的增减，会需要在中途做扩容或者缩容操作，如果只有一个的话，对它进行扩容缩容时会影响正常的访问和修改操作，或者说保证正常查询，修改的正确性会比较复杂，并且因为需要高效利用空间，不能一下子申请一个非常大的空间来存很少的数据。当 dict 中 dictht 中的数据量超过 size 的时候负载就超过了 1，就需要进行扩容，这里的其实跟 Java 中的 HashMap 比较类似，超过一定的负载之后进行扩容。这里为啥 size 会超过 1 呢，可能有部分不了解这类结构的同学会比较奇怪，其实就是上图中画的，在数据结构中对于散列的冲突有几类解决方法，比如转换成链表，二次散列，找下个空槽等，这里就使用了链表法，或者说拉链法。当一个新元素通过 hashFunction 得出的 key 跟 sizemask 取模之后的值相同了，那就将其放在原来的节点之前，变成链表挂在数组 dictht.table下面，放在原有节点前是考虑到可能会优先访问。
          忘了说明下 dictht 跟 dictEntry 的关系了，dictht 就是个哈希表，它里面是个dictEntry 的二维数组，而 dictEntry 是个包含了 key-value 结构之外还有一个 next 指针，因此可以将哈希冲突的以链表的形式保存下来。
          在重点说下重哈希，可能同样写 Java 的同学对这个比较有感觉，跟 HashMap 一样，会以 2 的 N 次方进行扩容，那么扩容的方法就会比较简单，每个键重哈希要不就在原来这个槽，要不就在原来的槽加原 dictht.size 的位置；然后是重头戏，具体是怎么做扩容呢，其实这里就把第二个 ht 用上了，其实这两个hashtable 的具体作用有点类似于 jvm 中的两个 survival 区，但是又不全一样，因为 redis 在扩容的时候是采用的渐进式地重哈希，什么叫渐进式的呢，就是它不是像 jvm 那种标记复制的模式直接将一个 eden 区和原来的 survival 区存活的对象复制到另一个 survival 区，而是在每一次添加，删除，查找或者更新操作时，都会额外的帮忙搬运一部分的原 dictht 中的数据，这里会根据 rehashidx 的值来判断，如果是-1 表示并没有在重哈希中，如果是 0 表示开始重哈希了，然后rehashidx 还会随着每次的帮忙搬运往上加，但全部被搬运完成后 rehashidx 又变回了-1，又可以扯到Java 中的 Concurrent HashMap, 他在扩容的时候也使用了类似的操作。

          @@ -340,10 +386,10 @@
          redis数据结构介绍五-第五部分 对象
        • -
          redis数据结构介绍四-第四部分 压缩表
          +
          redis数据结构介绍六 快表
        • -
          redis数据结构介绍六 快表
          +
          redis数据结构介绍四-第四部分 压缩表
        @@ -470,7 +516,7 @@
        -
        1. 1. SDS 简单动态字符串
        2. 2. 链表
        3. 3. 字典
        +
        1. 1. SDS 简单动态字符串
        2. 2. 链表
        3. 3. 字典
        diff --git a/2020/01/04/redis数据结构介绍二/index.html b/2020/01/04/redis数据结构介绍二/index.html index 40bff81135..41de348633 100644 --- a/2020/01/04/redis数据结构介绍二/index.html +++ b/2020/01/04/redis数据结构介绍二/index.html @@ -4,7 +4,7 @@ - + @@ -32,19 +32,16 @@ + - + - - + - - - @@ -238,13 +235,6 @@         - - - - - Edited on - - @@ -310,10 +300,36 @@
        -

        跳表 skiplist

        跳表是个在我们日常的代码中不太常用到的数据结构，相对来讲就没有像数组，链表，字典，散列，树等结构那么熟悉，所以就从头开始分析下，首先是链表，跳表跟链表都有个表字（太硬扯了我🤦‍♀️），注意这是个有序链表

        如上图，在这个链表里如果我要找到 23，是不是我需要从3，5，9开始一直往后找直到找到 23，也就是说时间复杂度是 O(N),N 的一次幂复杂度，那么我们来看看第二个

        这个结构跟原先有点不一样，它给链表中偶数位的节点又加了一个指针把它们链接起来，这样子当我们要寻找 23 的时候就可以从原来的一个个往下找变成跳着找，先找到 5，然后是 10，接着是 19，然后是 28，这时候发现 28 比 23 大了，那我在退回到 19，然后从下一层原来的链表往前找，

        这里毛估估是不是前面的节点我就少找了一半,有那么点二分法的意思。
        前面的其实是跳表的引子，真正的跳表其实不是这样，因为上面的其实有个比较大的问题，就是插入一个元素后需要调整每个元素的指针，在 redis 中的跳表其实是做了个随机层数的优化，因为沿着前面的例子，其实当数据量很大的时候，是不是层数越多，其查询效率越高，但是随着层数变多，要保持这种严格的层数规则其实也会增大处理复杂度，所以 redis 插入每个元素的时候都是使用随机的方式，看一眼代码

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        /* ZSETs use a specialized version of Skiplists */
        typedef struct zskiplistNode {
            sds ele;
            double score;
            struct zskiplistNode *backward;
            struct zskiplistLevel {
                struct zskiplistNode *forward;
                unsigned long span;
            } level[];
        } zskiplistNode;

        typedef struct zskiplist {
            struct zskiplistNode *header, *tail;
            unsigned long length;
            int level;
        } zskiplist;

        typedef struct zset {
            dict *dict;
            zskiplist *zsl;
        } zset;
        +

        跳表 skiplist

        跳表是个在我们日常的代码中不太常用到的数据结构，相对来讲就没有像数组，链表，字典，散列，树等结构那么熟悉，所以就从头开始分析下，首先是链表，跳表跟链表都有个表字（太硬扯了我🤦‍♀️），注意这是个有序链表

        如上图，在这个链表里如果我要找到 23，是不是我需要从3，5，9开始一直往后找直到找到 23，也就是说时间复杂度是 O(N),N 的一次幂复杂度，那么我们来看看第二个

        这个结构跟原先有点不一样，它给链表中偶数位的节点又加了一个指针把它们链接起来，这样子当我们要寻找 23 的时候就可以从原来的一个个往下找变成跳着找，先找到 5，然后是 10，接着是 19，然后是 28，这时候发现 28 比 23 大了，那我在退回到 19，然后从下一层原来的链表往前找，

        这里毛估估是不是前面的节点我就少找了一半,有那么点二分法的意思。
        前面的其实是跳表的引子，真正的跳表其实不是这样，因为上面的其实有个比较大的问题，就是插入一个元素后需要调整每个元素的指针，在 redis 中的跳表其实是做了个随机层数的优化，因为沿着前面的例子，其实当数据量很大的时候，是不是层数越多，其查询效率越高，但是随着层数变多，要保持这种严格的层数规则其实也会增大处理复杂度，所以 redis 插入每个元素的时候都是使用随机的方式，看一眼代码

        +
        /* ZSETs use a specialized version of Skiplists */
+typedef struct zskiplistNode {
+    sds ele;
+    double score;
+    struct zskiplistNode *backward;
+    struct zskiplistLevel {
+        struct zskiplistNode *forward;
+        unsigned long span;
+    } level[];
+} zskiplistNode;
+
+typedef struct zskiplist {
+    struct zskiplistNode *header, *tail;
+    unsigned long length;
+    int level;
+} zskiplist;
+
+typedef struct zset {
+    dict *dict;
+    zskiplist *zsl;
+} zset;

        忘了说了，redis 是把 skiplist 跳表用在 zset 里，zset 是个有序的集合，可以看到 zskiplist 就是个跳表的结构，里面用 header 保存跳表的表头，tail 保存表尾，还有长度和最大层级，具体的跳表节点元素使用 zskiplistNode 表示，里面包含了 sds 类型的元素值，double 类型的分值，用来排序，一个 backward 后向指针和一个 zskiplistLevel 数组，每个 level 包含了一个前向指针，和一个 span，span 表示的是跳表前向指针的跨度，这里再补充一点，前面说了为了灵活这个跳表的新增修改，redis 使用了随机层高的方式插入新节点，但是如果所有节点都随机到很高的层级或者所有都很低的话，跳表的效率优势就会减小，所以 redis 使用了个小技巧，贴下代码

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        #define ZSKIPLIST_P 0.25      /* Skiplist P = 1/4 */
        int zslRandomLevel(void) {
            int level = 1;
            while ((random()&0xFFFF) < (ZSKIPLIST_P * 0xFFFF))
                level += 1;
            return (level<ZSKIPLIST_MAXLEVEL) ? level : ZSKIPLIST_MAXLEVEL;
        }
        +
        #define ZSKIPLIST_P 0.25      /* Skiplist P = 1/4 */
+int zslRandomLevel(void) {
+    int level = 1;
+    while ((random()&0xFFFF) < (ZSKIPLIST_P * 0xFFFF))
+        level += 1;
+    return (level<ZSKIPLIST_MAXLEVEL) ? level : ZSKIPLIST_MAXLEVEL;
+}

        当随机值跟0xFFFF进行与操作小于ZSKIPLIST_P * 0xFFFF时才会增大 level 的值，因此保持了一个相对递减的概率
        可以简单分析下，当 random() 的值小于 0xFFFF 的 1/4,才会 level + 1，就意味着当有 1 - 1/4也就是3/4的概率是直接跳出，所以一层的概率是3/4,也就是 1-P，二层的概率是 P*(1-P),三层的概率是 P² * (1-P) 依次递推。

        @@ -325,19 +341,19 @@
        Related Posts
        @@ -464,7 +480,7 @@
        -
        1. 1. 跳表 skiplist
        +
        1. 1. 跳表 skiplist
        diff --git a/2020/01/10/redis数据结构介绍三/index.html b/2020/01/10/redis数据结构介绍三/index.html index a5dce3fccf..14ad6f956c 100644 --- a/2020/01/10/redis数据结构介绍三/index.html +++ b/2020/01/10/redis数据结构介绍三/index.html @@ -4,7 +4,7 @@ - + @@ -26,23 +26,20 @@ var CONFIG = {"hostname":"nicksxs.me","root":"/","scheme":"Pisces","version":"7.8.0","exturl":false,"sidebar":{"position":"left","display":"post","padding":18,"offset":12,"onmobile":false},"copycode":{"enable":true,"show_result":false,"style":null},"back2top":{"enable":true,"sidebar":false,"scrollpercent":false},"bookmark":{"enable":false,"color":"#222","save":"auto"},"fancybox":true,"mediumzoom":false,"lazyload":true,"pangu":false,"comments":{"style":"tabs","active":null,"storage":true,"lazyload":false,"nav":null},"algolia":{"hits":{"per_page":10},"labels":{"input_placeholder":"Search for Posts","hits_empty":"We didn't find any results for the search: ${query}","hits_stats":"${hits} results found in ${time} ms"}},"localsearch":{"enable":false,"trigger":"auto","top_n_per_article":1,"unescape":false,"preload":false},"motion":{"enable":true,"async":false,"transition":{"post_block":"fadeIn","post_header":"slideDownIn","post_body":"slideDownIn","coll_header":"slideLeftIn","sidebar":"slideUpIn"}}}; - + - + + - + - - + - - - @@ -236,13 +233,6 @@         - - - - - Edited on - - @@ -309,13 +299,29 @@

        redis中对于 set 其实有两种处理，对于元素均为整型，并且元素数目较少时，使用 intset 作为底层数据结构，否则使用 dict 作为底层数据结构，先看一下代码先

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        typedef struct intset {
            // 编码方式
            uint32_t encoding;
            // 集合包含的元素数量
            uint32_t length;
            // 保存元素的数组
            int8_t contents[];
        } intset;

        /* Note that these encodings are ordered, so:
         * INTSET_ENC_INT16 < INTSET_ENC_INT32 < INTSET_ENC_INT64. */
        #define INTSET_ENC_INT16 (sizeof(int16_t))
        #define INTSET_ENC_INT32 (sizeof(int32_t))
        #define INTSET_ENC_INT64 (sizeof(int64_t))
        +
        typedef struct intset {
+    // 编码方式
+    uint32_t encoding;
+    // 集合包含的元素数量
+    uint32_t length;
+    // 保存元素的数组
+    int8_t contents[];
+} intset;
+
+/* Note that these encodings are ordered, so:
+ * INTSET_ENC_INT16 < INTSET_ENC_INT32 < INTSET_ENC_INT64. */
+#define INTSET_ENC_INT16 (sizeof(int16_t))
+#define INTSET_ENC_INT32 (sizeof(int32_t))
+#define INTSET_ENC_INT64 (sizeof(int64_t))

        一眼看，为啥整型还需要编码，然后 int8_t 怎么能存下大整形呢，带着这些疑问，我们一步步分析下去，这里的编码其实指的是这个整型集合里存的究竟是多大的整型，16 位，还是 32 位，还是 64 位，结构体下面的宏定义就是表示了 encoding 的可能取值，INTSET_ENC_INT16 表示每个元素用2个字节存储，INTSET_ENC_INT32 表示每个元素用4个字节存储，INTSET_ENC_INT64 表示每个元素用8个字节存储。因此，intset中存储的整数最多只能占用64bit。length 就是正常的表示集合中元素的数量。最奇怪的应该就是这个 contents 了，是个 int8_t 的数组，那放毛线数据啊，最小的都有 16 位，这里我在看代码和《redis 设计与实现》的时候也有点懵逼，后来查了下发现这是个比较取巧的用法，这里我用自己的理解表述一下，先看看 8，16，32，64 的关系，一眼看就知道都是 2 的 N 次，并且呈两倍关系，而且 8 位刚好一个字节，所以呢其实这里的contents 不是个常规意义上的 int8_t 类型的数组，而是个柔性数组。看下 wiki 的定义

        -

        Flexible array members1 were introduced in the C99 standard of the C programming language (in particular, in section §6.7.2.1, item 16, page 103).2 It is a member of a struct, which is an array without a given dimension. It must be the last member of such a struct and it must be accompanied by at least one other member, as in the following example:

        +

        Flexible array members1 were introduced in the C99 standard of the C programming language (in particular, in section §6.7.2.1, item 16, page 103).2 It is a member of a struct, which is an array without a given dimension. It must be the last member of such a struct and it must be accompanied by at least one other member, as in the following example:

        -
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        struct vectord {
            size_t len;
            double arr[]; // the flexible array member must be last
        };
        -

        在初始化这个 intset 的时候，这个contents数组是不占用空间的，后面的反正用到了申请，那么这里就有一个问题，给出了三种可能的 encoding 值，他们能随便换吗，显然不行，首先在 intset 中数据的存放是有序的，这个有部分原因是方便二分查找，然后存放数据其实随着数据的大小不同会有一个升级的过程，看下图

        新创建的intset只有一个header，总共8个字节。其中encoding = 2, length = 0, 类型都是uint32_t，各占 4 字节，添加15, 5两个元素之后，因为它们是比较小的整数，都能使用2个字节表示，所以encoding不变，值还是2，也就是默认的 INTSET_ENC_INT16，当添加32768的时候，它不再能用2个字节来表示了（2个字节能表达的数据范围是-215~215-1，而32768等于215，超出范围了），因此encoding必须升级到INTSET_ENC_INT32（值为4），即用4个字节表示一个元素。在添加每个元素的过程中，intset始终保持从小到大有序。与ziplist类似，intset也是按小端（little endian）模式存储的（参见维基百科词条Endianness）。比如，在上图中intset添加完所有数据之后，表示encoding字段的4个字节应该解释成0x00000004，而第4个数据应该解释成0x00008000 = 32768

        +
        struct vectord {
+    size_t len;
+    double arr[]; // the flexible array member must be last
+};
        +

        在初始化这个 intset 的时候，这个contents数组是不占用空间的，后面的反正用到了申请，那么这里就有一个问题，给出了三种可能的 encoding 值，他们能随便换吗，显然不行，首先在 intset 中数据的存放是有序的，这个有部分原因是方便二分查找，然后存放数据其实随着数据的大小不同会有一个升级的过程，看下图

        新创建的intset只有一个header，总共8个字节。其中encoding = 2, length = 0, 类型都是uint32_t，各占 4 字节，添加15, 5两个元素之后，因为它们是比较小的整数，都能使用2个字节表示，所以encoding不变，值还是2，也就是默认的 INTSET_ENC_INT16，当添加32768的时候，它不再能用2个字节来表示了（2个字节能表达的数据范围是-215~215-1，而32768等于215，超出范围了），因此encoding必须升级到INTSET_ENC_INT32（值为4），即用4个字节表示一个元素。在添加每个元素的过程中，intset始终保持从小到大有序。与ziplist类似，intset也是按小端（little endian）模式存储的（参见维基百科词条Endianness）。比如，在上图中intset添加完所有数据之后，表示encoding字段的4个字节应该解释成0x00000004，而第4个数据应该解释成0x00008000 = 32768

        @@ -326,19 +332,19 @@
        Related Posts
        diff --git a/2020/01/19/redis数据结构介绍四/index.html b/2020/01/19/redis数据结构介绍四/index.html index d06d199d27..2a9472c25a 100644 --- a/2020/01/19/redis数据结构介绍四/index.html +++ b/2020/01/19/redis数据结构介绍四/index.html @@ -4,7 +4,7 @@ - + @@ -32,16 +32,13 @@ + - - + - - - @@ -303,13 +300,40 @@

        The ziplist is a specially encoded dually linked list that is designed to be very memory efficient.
        这是摘自 redis 源码中ziplist.c 文件的注释，也说明了原因，它的大概结构是这样子

        -
        1
        <zlbytes> <zltail> <zllen> <entry> <entry> ... <entry> <zlend>
        +
        <zlbytes> <zltail> <zllen> <entry> <entry> ... <entry> <zlend>

        其中
        <zlbytes>表示 ziplist 占用的字节总数，类型是uint32_t，32 位的无符号整型，当然表示的字节数也包含自己本身占用的 4 个
        <zltail> 类型也是是uint32_t，表示ziplist表中最后一项（entry）在ziplist中的偏移字节数。<zltail>的存在，使得我们可以很方便地找到最后一项（不用遍历整个ziplist），从而可以在ziplist尾端快速地执行push或pop操作。
        <uint16_t zllen> 表示ziplist 中的数据项个数，因为是 16 位，所以当数量超过所能表示的最大的数量，它的 16 位全会置为 1，但是真实的数量需要遍历整个 ziplist 才能知道
        <entry>是具体的数据项，后面解释
        <zlend> ziplist 的最后一个字节，固定是255。
        再看一下<entry>中的具体结构，

        -
        1
        <prevlen> <encoding> <entry-data>
        +
        <prevlen> <encoding> <entry-data>

        首先这个<prevlen>有两种情况，一种是前面的元素的长度，如果是小于等于 253的时候就用一个uint8_t 来表示前一元素的长度，如果大于的话他将占用五个字节，第一个字节是 254，即表示这个字节已经表示不下了，需要后面的四个字节帮忙表示
        <encoding>这个就比较复杂，把源码的注释放下面先看下

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        * |00pppppp| - 1 byte
        *      String value with length less than or equal to 63 bytes (6 bits).
        *      "pppppp" represents the unsigned 6 bit length.
        * |01pppppp|qqqqqqqq| - 2 bytes
        *      String value with length less than or equal to 16383 bytes (14 bits).
        *      IMPORTANT: The 14 bit number is stored in big endian.
        * |10000000|qqqqqqqq|rrrrrrrr|ssssssss|tttttttt| - 5 bytes
        *      String value with length greater than or equal to 16384 bytes.
        *      Only the 4 bytes following the first byte represents the length
        *      up to 32^2-1. The 6 lower bits of the first byte are not used and
        *      are set to zero.
        *      IMPORTANT: The 32 bit number is stored in big endian.
        * |11000000| - 3 bytes
        *      Integer encoded as int16_t (2 bytes).
        * |11010000| - 5 bytes
        *      Integer encoded as int32_t (4 bytes).
        * |11100000| - 9 bytes
        *      Integer encoded as int64_t (8 bytes).
        * |11110000| - 4 bytes
        *      Integer encoded as 24 bit signed (3 bytes).
        * |11111110| - 2 bytes
        *      Integer encoded as 8 bit signed (1 byte).
        * |1111xxxx| - (with xxxx between 0000 and 1101) immediate 4 bit integer.
        *      Unsigned integer from 0 to 12. The encoded value is actually from
        *      1 to 13 because 0000 and 1111 can not be used, so 1 should be
        *      subtracted from the encoded 4 bit value to obtain the right value.
        * |11111111| - End of ziplist special entry.
        +
        * |00pppppp| - 1 byte
+*      String value with length less than or equal to 63 bytes (6 bits).
+*      "pppppp" represents the unsigned 6 bit length.
+* |01pppppp|qqqqqqqq| - 2 bytes
+*      String value with length less than or equal to 16383 bytes (14 bits).
+*      IMPORTANT: The 14 bit number is stored in big endian.
+* |10000000|qqqqqqqq|rrrrrrrr|ssssssss|tttttttt| - 5 bytes
+*      String value with length greater than or equal to 16384 bytes.
+*      Only the 4 bytes following the first byte represents the length
+*      up to 32^2-1. The 6 lower bits of the first byte are not used and
+*      are set to zero.
+*      IMPORTANT: The 32 bit number is stored in big endian.
+* |11000000| - 3 bytes
+*      Integer encoded as int16_t (2 bytes).
+* |11010000| - 5 bytes
+*      Integer encoded as int32_t (4 bytes).
+* |11100000| - 9 bytes
+*      Integer encoded as int64_t (8 bytes).
+* |11110000| - 4 bytes
+*      Integer encoded as 24 bit signed (3 bytes).
+* |11111110| - 2 bytes
+*      Integer encoded as 8 bit signed (1 byte).
+* |1111xxxx| - (with xxxx between 0000 and 1101) immediate 4 bit integer.
+*      Unsigned integer from 0 to 12. The encoded value is actually from
+*      1 to 13 because 0000 and 1111 can not be used, so 1 should be
+*      subtracted from the encoded 4 bit value to obtain the right value.
+* |11111111| - End of ziplist special entry.

        首先如果 encoding 的前两位是 00 的话代表这个元素是个 6 位的字符串，即直接将数据保存在 encoding 中，不消耗额外的<entry-data>，如果前两位是 01 的话表示是个 14 位的字符串，如果是 10 的话表示encoding 块之后的四个字节是存放字符串类型的数据，encoding 的剩余 6 位置 0。
        如果 encoding 的前两位是 11 的话表示这是个整型，具体的如果后两位是00的话，表示后面是个2字节的 int16_t 类型，如果是01的话，后面是个4字节的int32_t,如果是10的话后面是8字节的int64_t,如果是 11 的话后面是 3 字节的有符号整型，这些都要最后 4 位都是 0 的情况噢
        剩下当是11111110时，则表示是一个1 字节的有符号数，如果是 1111xxxx，其中xxxx在0000 到 1101 表示实际的 1 到 13，为啥呢，因为 0000 前面已经用过了，而 1110 跟 1111 也都有用了。
        看个具体的例子(上下有点对不齐，将就看)

        -
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        [0f 00 00 00] [0c 00 00 00] [02 00] [00 f3] [02 f6] [ff]
        |**zlbytes***|  |***zltail***|  |*zllen*|  |entry1 entry2|  |zlend|
        +
        [0f 00 00 00] [0c 00 00 00] [02 00] [00 f3] [02 f6] [ff]
+|**zlbytes***|  |***zltail***|  |*zllen*|  |entry1 entry2|  |zlend|

        第一部分代表整个 ziplist 有 15 个字节，zlbytes 自己占了 4 个 zltail 表示最后一个元素的偏移量，第 13 个字节起，zllen 表示有 2 个元素，第一个元素是00f3,00表示前一个元素长度是 0，本来前面就没元素(不过不知道这个能不能优化这一字节)，然后是 f3，换成二进制就是11110011,对照上面的注释，是落在|1111xxxx|这个类型里，注意这个其实是用 0001 到 1101 也就是 1到 13 来表示 0到 12，所以 f3 应该就是 2，第一个元素是 2，第二个元素呢，02 代表前一个元素也就是刚才说的这个，占用 2 字节，f6 展开也是刚才的类型，实际是 5，ff 表示 ziplist 的结尾，所以这个 ziplist 里面是两个元素，2 跟 5

        @@ -320,6 +344,9 @@
        Related Posts
          +
        • +
          redis数据结构介绍-第一部分 SDS，链表，字典
          +
        • redis数据结构介绍三-第三部分 整数集合
          • @@ -329,9 +356,6 @@
        • redis数据结构介绍五-第五部分 对象
          • -
        • -
          redis数据结构介绍-第一部分 SDS，链表，字典
          -
        • redis数据结构介绍六 快表
          • diff --git a/2020/01/20/redis数据结构介绍五/index.html b/2020/01/20/redis数据结构介绍五/index.html index 80c86bb2e4..0bece86eb9 100644 --- a/2020/01/20/redis数据结构介绍五/index.html +++ b/2020/01/20/redis数据结构介绍五/index.html @@ -4,7 +4,7 @@ - + @@ -32,16 +32,13 @@ + - - + - - - @@ -300,7 +297,42 @@

          前面说了这么些数据结构，其实大家对于 redis 最初的印象应该就是个 key-value 的缓存，类似于 memcache，redis 其实也是个 key-value，key 还是一样的字符串，或者说就是用 redis 自己的动态字符串实现，但是 value 其实就是前面说的那些数据结构，差不多快说完了，还有个 quicklist 后面还有一篇，这里先介绍下 redis 对于这些不同类型的 value 是怎么实现的，首先看下 redisObject 的源码头文件

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          /* The actual Redis Object */
          #define OBJ_STRING 0    /* String object. */
          #define OBJ_LIST 1      /* List object. */
          #define OBJ_SET 2       /* Set object. */
          #define OBJ_ZSET 3      /* Sorted set object. */
          #define OBJ_HASH 4      /* Hash object. */
          /*
           * Objects encoding. Some kind of objects like Strings and Hashes can be
           * internally represented in multiple ways. The 'encoding' field of the object
           * is set to one of this fields for this object. */
          #define OBJ_ENCODING_RAW 0     /* Raw representation */
          #define OBJ_ENCODING_INT 1     /* Encoded as integer */
          #define OBJ_ENCODING_HT 2      /* Encoded as hash table */
          #define OBJ_ENCODING_ZIPMAP 3  /* Encoded as zipmap */
          #define OBJ_ENCODING_LINKEDLIST 4 /* No longer used: old list encoding. */
          #define OBJ_ENCODING_ZIPLIST 5 /* Encoded as ziplist */
          #define OBJ_ENCODING_INTSET 6  /* Encoded as intset */
          #define OBJ_ENCODING_SKIPLIST 7  /* Encoded as skiplist */
          #define OBJ_ENCODING_EMBSTR 8  /* Embedded sds string encoding */
          #define OBJ_ENCODING_QUICKLIST 9 /* Encoded as linked list of ziplists */
          #define OBJ_ENCODING_STREAM 10 /* Encoded as a radix tree of listpacks */

          #define LRU_BITS 24
          #define LRU_CLOCK_MAX ((1<<LRU_BITS)-1) /* Max value of obj->lru */
          #define LRU_CLOCK_RESOLUTION 1000 /* LRU clock resolution in ms */

          #define OBJ_SHARED_REFCOUNT INT_MAX
          typedef struct redisObject {
              unsigned type:4;
              unsigned encoding:4;
              unsigned lru:LRU_BITS; /* LRU time (relative to global lru_clock) or
                                      * LFU data (least significant 8 bits frequency
                                      * and most significant 16 bits access time). */
              int refcount;
              void *ptr;
          } robj;
          +
          /* The actual Redis Object */
+#define OBJ_STRING 0    /* String object. */
+#define OBJ_LIST 1      /* List object. */
+#define OBJ_SET 2       /* Set object. */
+#define OBJ_ZSET 3      /* Sorted set object. */
+#define OBJ_HASH 4      /* Hash object. */
+/*
+ * Objects encoding. Some kind of objects like Strings and Hashes can be
+ * internally represented in multiple ways. The 'encoding' field of the object
+ * is set to one of this fields for this object. */
+#define OBJ_ENCODING_RAW 0     /* Raw representation */
+#define OBJ_ENCODING_INT 1     /* Encoded as integer */
+#define OBJ_ENCODING_HT 2      /* Encoded as hash table */
+#define OBJ_ENCODING_ZIPMAP 3  /* Encoded as zipmap */
+#define OBJ_ENCODING_LINKEDLIST 4 /* No longer used: old list encoding. */
+#define OBJ_ENCODING_ZIPLIST 5 /* Encoded as ziplist */
+#define OBJ_ENCODING_INTSET 6  /* Encoded as intset */
+#define OBJ_ENCODING_SKIPLIST 7  /* Encoded as skiplist */
+#define OBJ_ENCODING_EMBSTR 8  /* Embedded sds string encoding */
+#define OBJ_ENCODING_QUICKLIST 9 /* Encoded as linked list of ziplists */
+#define OBJ_ENCODING_STREAM 10 /* Encoded as a radix tree of listpacks */
+
+#define LRU_BITS 24
+#define LRU_CLOCK_MAX ((1<<LRU_BITS)-1) /* Max value of obj->lru */
+#define LRU_CLOCK_RESOLUTION 1000 /* LRU clock resolution in ms */
+
+#define OBJ_SHARED_REFCOUNT INT_MAX
+typedef struct redisObject {
+    unsigned type:4;
+    unsigned encoding:4;
+    unsigned lru:LRU_BITS; /* LRU time (relative to global lru_clock) or
+                            * LFU data (least significant 8 bits frequency
+                            * and most significant 16 bits access time). */
+    int refcount;
+    void *ptr;
+} robj;

          主体结构就是这个 redisObject，

          • type： 字段表示对象的类型，它对应的就是 redis 的对外暴露的，或者说用户可以使用的五种类型，OBJ_STRING, OBJ_LIST, OBJ_SET, OBJ_ZSET, OBJ_HASH
            • @@ -319,19 +351,19 @@
            Related Posts
            diff --git a/2020/01/22/redis数据结构介绍六/index.html b/2020/01/22/redis数据结构介绍六/index.html index f3a8d81836..49cb73a01f 100644 --- a/2020/01/22/redis数据结构介绍六/index.html +++ b/2020/01/22/redis数据结构介绍六/index.html @@ -4,7 +4,7 @@ - + @@ -32,16 +32,13 @@ + - + - - + - - - @@ -234,13 +231,6 @@ - - - - - Edited on - - @@ -307,10 +297,80 @@

            这应该是 redis 系列的最后一篇了，讲下快表，其实最前面讲的链表在早先的 redis 版本中也作为 list 的数据结构使用过，但是单纯的链表的缺陷之前也说了，插入便利，但是空间利用率低，并且不能进行二分查找等，检索效率低，ziplist 压缩表的产生也是同理，希望获得更好的性能，包括存储空间和访问性能等，原来我也不懂这个快表要怎么快，然后明白了一个道理，其实并没有什么银弹，只是大牛们会在适合的时候使用最适合的数据结构来实现性能的最大化，这里面有一招就是不同数据结构的组合调整，比如 Java 中的 HashMap，在链表节点数大于 8 时会转变成红黑树，以此提高访问效率，不费话了，回到快表，quicklist，这个数据结构主要使用在 list 类型中，如果我说其实这个 quicklist 就是个链表，可能大家不太会相信，但是事实上的确可以认为 quicklist 是个双向链表，看下代码

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            /* quicklistNode is a 32 byte struct describing a ziplist for a quicklist.
             * We use bit fields keep the quicklistNode at 32 bytes.
             * count: 16 bits, max 65536 (max zl bytes is 65k, so max count actually < 32k).
             * encoding: 2 bits, RAW=1, LZF=2.
             * container: 2 bits, NONE=1, ZIPLIST=2.
             * recompress: 1 bit, bool, true if node is temporarry decompressed for usage.
             * attempted_compress: 1 bit, boolean, used for verifying during testing.
             * extra: 10 bits, free for future use; pads out the remainder of 32 bits */
            typedef struct quicklistNode {
                struct quicklistNode *prev;
                struct quicklistNode *next;
                unsigned char *zl;
                unsigned int sz;             /* ziplist size in bytes */
                unsigned int count : 16;     /* count of items in ziplist */
                unsigned int encoding : 2;   /* RAW==1 or LZF==2 */
                unsigned int container : 2;  /* NONE==1 or ZIPLIST==2 */
                unsigned int recompress : 1; /* was this node previous compressed? */
                unsigned int attempted_compress : 1; /* node can't compress; too small */
                unsigned int extra : 10; /* more bits to steal for future usage */
            } quicklistNode;

            /* quicklistLZF is a 4+N byte struct holding 'sz' followed by 'compressed'.
             * 'sz' is byte length of 'compressed' field.
             * 'compressed' is LZF data with total (compressed) length 'sz'
             * NOTE: uncompressed length is stored in quicklistNode->sz.
             * When quicklistNode->zl is compressed, node->zl points to a quicklistLZF */
            typedef struct quicklistLZF {
                unsigned int sz; /* LZF size in bytes*/
                char compressed[];
            } quicklistLZF;

            /* quicklist is a 40 byte struct (on 64-bit systems) describing a quicklist.
             * 'count' is the number of total entries.
             * 'len' is the number of quicklist nodes.
             * 'compress' is: -1 if compression disabled, otherwise it's the number
             *                of quicklistNodes to leave uncompressed at ends of quicklist.
             * 'fill' is the user-requested (or default) fill factor. */
            typedef struct quicklist {
                quicklistNode *head;
                quicklistNode *tail;
                unsigned long count;        /* total count of all entries in all ziplists */
                unsigned long len;          /* number of quicklistNodes */
                int fill : 16;              /* fill factor for individual nodes */
                unsigned int compress : 16; /* depth of end nodes not to compress;0=off */
            } quicklist;
            +
            /* quicklistNode is a 32 byte struct describing a ziplist for a quicklist.
+ * We use bit fields keep the quicklistNode at 32 bytes.
+ * count: 16 bits, max 65536 (max zl bytes is 65k, so max count actually < 32k).
+ * encoding: 2 bits, RAW=1, LZF=2.
+ * container: 2 bits, NONE=1, ZIPLIST=2.
+ * recompress: 1 bit, bool, true if node is temporarry decompressed for usage.
+ * attempted_compress: 1 bit, boolean, used for verifying during testing.
+ * extra: 10 bits, free for future use; pads out the remainder of 32 bits */
+typedef struct quicklistNode {
+    struct quicklistNode *prev;
+    struct quicklistNode *next;
+    unsigned char *zl;
+    unsigned int sz;             /* ziplist size in bytes */
+    unsigned int count : 16;     /* count of items in ziplist */
+    unsigned int encoding : 2;   /* RAW==1 or LZF==2 */
+    unsigned int container : 2;  /* NONE==1 or ZIPLIST==2 */
+    unsigned int recompress : 1; /* was this node previous compressed? */
+    unsigned int attempted_compress : 1; /* node can't compress; too small */
+    unsigned int extra : 10; /* more bits to steal for future usage */
+} quicklistNode;
+
+/* quicklistLZF is a 4+N byte struct holding 'sz' followed by 'compressed'.
+ * 'sz' is byte length of 'compressed' field.
+ * 'compressed' is LZF data with total (compressed) length 'sz'
+ * NOTE: uncompressed length is stored in quicklistNode->sz.
+ * When quicklistNode->zl is compressed, node->zl points to a quicklistLZF */
+typedef struct quicklistLZF {
+    unsigned int sz; /* LZF size in bytes*/
+    char compressed[];
+} quicklistLZF;
+
+/* quicklist is a 40 byte struct (on 64-bit systems) describing a quicklist.
+ * 'count' is the number of total entries.
+ * 'len' is the number of quicklist nodes.
+ * 'compress' is: -1 if compression disabled, otherwise it's the number
+ *                of quicklistNodes to leave uncompressed at ends of quicklist.
+ * 'fill' is the user-requested (or default) fill factor. */
+typedef struct quicklist {
+    quicklistNode *head;
+    quicklistNode *tail;
+    unsigned long count;        /* total count of all entries in all ziplists */
+    unsigned long len;          /* number of quicklistNodes */
+    int fill : 16;              /* fill factor for individual nodes */
+    unsigned int compress : 16; /* depth of end nodes not to compress;0=off */
+} quicklist;

            粗略看下，quicklist 里有 head，tail, quicklistNode里有 prev，next 指针，是不是有链表的基本轮廓了，那么为啥这玩意要称为快表呢，快在哪，关键就在这个unsigned char *zl;zl 是不是前面又看到过，就是 ziplist ，这是什么鬼，链表里用压缩表，这不套娃么，先别急，回顾下前面说的 ziplist，ziplist 有哪些特点，内存利用率高，可以从表头快速定位到尾节点，节点可以从后往前找，但是有个缺点，就是从中间插入的效率比较低，需要整体往后移，这个其实是普通数组的优化版，但还是有数组的一些劣势，所以要真的快，是不是可以将链表跟数组真的结合起来。

            ziplist

            这里有两个 redis 的配置参数，list-max-ziplist-size 和 list-compress-depth，先来说第一个，既然快表是将链表跟压缩表数组结合起来使用，那么具体怎么用呢，比如我有一个 10 个元素的 list，那具体怎么放，每个 quicklistNode 里放多大的 ziplist，假如每个快表节点的 ziplist 只放一个元素，那么其实这就退化成了一个链表，如果 10 个元素放在一个 quicklistNode 的 ziplist 里，那就退化成了一个 ziplist，所以有了这个 list-max-ziplist-size,而且它还比较牛，能取正负值，当是正值时，对应的就是每个 quicklistNode 的 ziplist 中的元素个数，比如配置了 list-max-ziplist-size = 5，那么我刚才的 10 个元素的 list 就是一个两个 quicklistNode 组成的快表，每个 quicklistNode 中的 ziplist 包含了五个元素，当 list-max-ziplist-size取负值的时候，它限制了 ziplist 的字节数

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            size_t offset = (-fill) - 1;
            if (offset < (sizeof(optimization_level) / sizeof(*optimization_level))) {
                if (sz <= optimization_level[offset]) {
                    return 1;
                } else {
                    return 0;
                }
            } else {
                return 0;
            }

            /* Optimization levels for size-based filling */
            static const size_t optimization_level[] = {4096, 8192, 16384, 32768, 65536};

            /* Create a new quicklist.
             * Free with quicklistRelease(). */
            quicklist *quicklistCreate(void) {
                struct quicklist *quicklist;

                quicklist = zmalloc(sizeof(*quicklist));
                quicklist->head = quicklist->tail = NULL;
                quicklist->len = 0;
                quicklist->count = 0;
                quicklist->compress = 0;
                quicklist->fill = -2;
                return quicklist;
            }
            +
            size_t offset = (-fill) - 1;
+if (offset < (sizeof(optimization_level) / sizeof(*optimization_level))) {
+    if (sz <= optimization_level[offset]) {
+        return 1;
+    } else {
+        return 0;
+    }
+} else {
+    return 0;
+}
+
+/* Optimization levels for size-based filling */
+static const size_t optimization_level[] = {4096, 8192, 16384, 32768, 65536};
+
+/* Create a new quicklist.
+ * Free with quicklistRelease(). */
+quicklist *quicklistCreate(void) {
+    struct quicklist *quicklist;
+
+    quicklist = zmalloc(sizeof(*quicklist));
+    quicklist->head = quicklist->tail = NULL;
+    quicklist->len = 0;
+    quicklist->count = 0;
+    quicklist->compress = 0;
+    quicklist->fill = -2;
+    return quicklist;
+}

            这个 fill 就是传进来的 list-max-ziplist-size, 具体对应的就是

            • -5: 每个quicklist节点上的ziplist大小不能超过64 Kb。（注：1kb => 1024 bytes）
              • @@ -320,15 +380,121 @@
            • -1: 每个quicklist节点上的ziplist大小不能超过4 Kb。

            压缩

            list-compress-depth这个参数呢是用来配置压缩的，等等压缩是为啥，不是里面已经是压缩表了么，大牛们就是为了性能殚精竭虑，这里考虑到的是一个场景，一般状况下，list 都是两端的访问频率比较高，那么是不是可以对中间的数据进行压缩，那么这个参数就是用来表示

            -
            1
            /* depth of end nodes not to compress;0=off */
            +
            /* depth of end nodes not to compress;0=off */
            • 0，代表不压缩，默认值
            • 1，两端各一个节点不压缩
            • 2，两端各两个节点不压缩
              • -
            • … 依次类推
              压缩后的 ziplist 就会变成 quicklistLZF，然后替换 zl 指针，这里使用的是 LZF 压缩算法，压缩后的 quicklistLZF 中的 compressed 也是个柔性数组，压缩后的 ziplist 整个就放进这个柔性数组
              • +
            • … 依次类推
              压缩后的 ziplist 就会变成 quicklistLZF，然后替换 zl 指针，这里使用的是 LZF 压缩算法，压缩后的 quicklistLZF 中的 compressed 也是个柔性数组，压缩后的 ziplist 整个就放进这个柔性数组

            插入过程

            简单说下插入元素的过程

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            /* Wrapper to allow argument-based switching between HEAD/TAIL pop */
            void quicklistPush(quicklist *quicklist, void *value, const size_t sz,
                               int where) {
                if (where == QUICKLIST_HEAD) {
                    quicklistPushHead(quicklist, value, sz);
                } else if (where == QUICKLIST_TAIL) {
                    quicklistPushTail(quicklist, value, sz);
                }
            }

            /* Add new entry to head node of quicklist.
             *
             * Returns 0 if used existing head.
             * Returns 1 if new head created. */
            int quicklistPushHead(quicklist *quicklist, void *value, size_t sz) {
                quicklistNode *orig_head = quicklist->head;
                if (likely(
                        _quicklistNodeAllowInsert(quicklist->head, quicklist->fill, sz))) {
                    quicklist->head->zl =
                        ziplistPush(quicklist->head->zl, value, sz, ZIPLIST_HEAD);
                    quicklistNodeUpdateSz(quicklist->head);
                } else {
                    quicklistNode *node = quicklistCreateNode();
                    node->zl = ziplistPush(ziplistNew(), value, sz, ZIPLIST_HEAD);

                    quicklistNodeUpdateSz(node);
                    _quicklistInsertNodeBefore(quicklist, quicklist->head, node);
                }
                quicklist->count++;
                quicklist->head->count++;
                return (orig_head != quicklist->head);
            }

            /* Add new entry to tail node of quicklist.
             *
             * Returns 0 if used existing tail.
             * Returns 1 if new tail created. */
            int quicklistPushTail(quicklist *quicklist, void *value, size_t sz) {
                quicklistNode *orig_tail = quicklist->tail;
                if (likely(
                        _quicklistNodeAllowInsert(quicklist->tail, quicklist->fill, sz))) {
                    quicklist->tail->zl =
                        ziplistPush(quicklist->tail->zl, value, sz, ZIPLIST_TAIL);
                    quicklistNodeUpdateSz(quicklist->tail);
                } else {
                    quicklistNode *node = quicklistCreateNode();
                    node->zl = ziplistPush(ziplistNew(), value, sz, ZIPLIST_TAIL);

                    quicklistNodeUpdateSz(node);
                    _quicklistInsertNodeAfter(quicklist, quicklist->tail, node);
                }
                quicklist->count++;
                quicklist->tail->count++;
                return (orig_tail != quicklist->tail);
            }

            /* Wrappers for node inserting around existing node. */
            REDIS_STATIC void _quicklistInsertNodeBefore(quicklist *quicklist,
                                                         quicklistNode *old_node,
                                                         quicklistNode *new_node) {
                __quicklistInsertNode(quicklist, old_node, new_node, 0);
            }

            REDIS_STATIC void _quicklistInsertNodeAfter(quicklist *quicklist,
                                                        quicklistNode *old_node,
                                                        quicklistNode *new_node) {
                __quicklistInsertNode(quicklist, old_node, new_node, 1);
            }

            /* Insert 'new_node' after 'old_node' if 'after' is 1.
             * Insert 'new_node' before 'old_node' if 'after' is 0.
             * Note: 'new_node' is *always* uncompressed, so if we assign it to
             *       head or tail, we do not need to uncompress it. */
            REDIS_STATIC void __quicklistInsertNode(quicklist *quicklist,
                                                    quicklistNode *old_node,
                                                    quicklistNode *new_node, int after) {
                if (after) {
                    new_node->prev = old_node;
                    if (old_node) {
                        new_node->next = old_node->next;
                        if (old_node->next)
                            old_node->next->prev = new_node;
                        old_node->next = new_node;
                    }
                    if (quicklist->tail == old_node)
                        quicklist->tail = new_node;
                } else {
                    new_node->next = old_node;
                    if (old_node) {
                        new_node->prev = old_node->prev;
                        if (old_node->prev)
                            old_node->prev->next = new_node;
                        old_node->prev = new_node;
                    }
                    if (quicklist->head == old_node)
                        quicklist->head = new_node;
                }
                /* If this insert creates the only element so far, initialize head/tail. */
                if (quicklist->len == 0) {
                    quicklist->head = quicklist->tail = new_node;
                }

                if (old_node)
                    quicklistCompress(quicklist, old_node);

                quicklist->len++;
            }
            +
            /* Wrapper to allow argument-based switching between HEAD/TAIL pop */
+void quicklistPush(quicklist *quicklist, void *value, const size_t sz,
+                   int where) {
+    if (where == QUICKLIST_HEAD) {
+        quicklistPushHead(quicklist, value, sz);
+    } else if (where == QUICKLIST_TAIL) {
+        quicklistPushTail(quicklist, value, sz);
+    }
+}
+
+/* Add new entry to head node of quicklist.
+ *
+ * Returns 0 if used existing head.
+ * Returns 1 if new head created. */
+int quicklistPushHead(quicklist *quicklist, void *value, size_t sz) {
+    quicklistNode *orig_head = quicklist->head;
+    if (likely(
+            _quicklistNodeAllowInsert(quicklist->head, quicklist->fill, sz))) {
+        quicklist->head->zl =
+            ziplistPush(quicklist->head->zl, value, sz, ZIPLIST_HEAD);
+        quicklistNodeUpdateSz(quicklist->head);
+    } else {
+        quicklistNode *node = quicklistCreateNode();
+        node->zl = ziplistPush(ziplistNew(), value, sz, ZIPLIST_HEAD);
+
+        quicklistNodeUpdateSz(node);
+        _quicklistInsertNodeBefore(quicklist, quicklist->head, node);
+    }
+    quicklist->count++;
+    quicklist->head->count++;
+    return (orig_head != quicklist->head);
+}
+
+/* Add new entry to tail node of quicklist.
+ *
+ * Returns 0 if used existing tail.
+ * Returns 1 if new tail created. */
+int quicklistPushTail(quicklist *quicklist, void *value, size_t sz) {
+    quicklistNode *orig_tail = quicklist->tail;
+    if (likely(
+            _quicklistNodeAllowInsert(quicklist->tail, quicklist->fill, sz))) {
+        quicklist->tail->zl =
+            ziplistPush(quicklist->tail->zl, value, sz, ZIPLIST_TAIL);
+        quicklistNodeUpdateSz(quicklist->tail);
+    } else {
+        quicklistNode *node = quicklistCreateNode();
+        node->zl = ziplistPush(ziplistNew(), value, sz, ZIPLIST_TAIL);
+
+        quicklistNodeUpdateSz(node);
+        _quicklistInsertNodeAfter(quicklist, quicklist->tail, node);
+    }
+    quicklist->count++;
+    quicklist->tail->count++;
+    return (orig_tail != quicklist->tail);
+}
+
+/* Wrappers for node inserting around existing node. */
+REDIS_STATIC void _quicklistInsertNodeBefore(quicklist *quicklist,
+                                             quicklistNode *old_node,
+                                             quicklistNode *new_node) {
+    __quicklistInsertNode(quicklist, old_node, new_node, 0);
+}
+
+REDIS_STATIC void _quicklistInsertNodeAfter(quicklist *quicklist,
+                                            quicklistNode *old_node,
+                                            quicklistNode *new_node) {
+    __quicklistInsertNode(quicklist, old_node, new_node, 1);
+}
+
+/* Insert 'new_node' after 'old_node' if 'after' is 1.
+ * Insert 'new_node' before 'old_node' if 'after' is 0.
+ * Note: 'new_node' is *always* uncompressed, so if we assign it to
+ *       head or tail, we do not need to uncompress it. */
+REDIS_STATIC void __quicklistInsertNode(quicklist *quicklist,
+                                        quicklistNode *old_node,
+                                        quicklistNode *new_node, int after) {
+    if (after) {
+        new_node->prev = old_node;
+        if (old_node) {
+            new_node->next = old_node->next;
+            if (old_node->next)
+                old_node->next->prev = new_node;
+            old_node->next = new_node;
+        }
+        if (quicklist->tail == old_node)
+            quicklist->tail = new_node;
+    } else {
+        new_node->next = old_node;
+        if (old_node) {
+            new_node->prev = old_node->prev;
+            if (old_node->prev)
+                old_node->prev->next = new_node;
+            old_node->prev = new_node;
+        }
+        if (quicklist->head == old_node)
+            quicklist->head = new_node;
+    }
+    /* If this insert creates the only element so far, initialize head/tail. */
+    if (quicklist->len == 0) {
+        quicklist->head = quicklist->tail = new_node;
+    }
+
+    if (old_node)
+        quicklistCompress(quicklist, old_node);
+
+    quicklist->len++;
+}

            前面第一步先根据插入的是头还是尾选择不同的 push 函数，quicklistPushHead 或者 quicklistPushTail，举例分析下从头插入的 quicklistPushHead，先判断当前的 quicklistNode 节点还能不能允许再往 ziplist 里添加元素，如果可以就添加，如果不允许就新建一个 quicklistNode，然后调用 _quicklistInsertNodeBefore 将节点插进去，具体插入quicklist节点的操作类似链表的插入。

            @@ -339,6 +505,9 @@
            Related Posts
            @@ -479,7 +645,7 @@
            -
            1. 1. ziplist
            2. 2. 压缩
            3. 3. 插入过程
            +
            1. 1. ziplist
            2. 2. 压缩
            3. 3. 插入过程
            diff --git a/2020/02/01/2019年终总结/index.html b/2020/02/01/2019年终总结/index.html index 727ccb5c99..a649b8f63b 100644 --- a/2020/02/01/2019年终总结/index.html +++ b/2020/02/01/2019年终总结/index.html @@ -4,7 +4,7 @@ - + @@ -32,11 +32,12 @@ + - + - + @@ -227,9 +228,8 @@ Posted on - - + @@ -318,13 +318,13 @@
            在老丈人家的小工记四
          • -
            周末我在老丈人家打了天小工
            +
            从丁仲礼被美国制裁聊点啥
          • -
            从清华美院学姐聊聊我们身边的恶人
            +
            关于公共交通再吐个槽
          • -
            在老丈人家的小工记三
            +
            周末我在老丈人家打了天小工
          @@ -451,7 +451,7 @@
          -
          1. 1. 跳槽
          2. 2. 面试
          3. 3. 技术方向
          4. 4. 生活
          5. 5. 期待
          +
          1. 1. 跳槽
          2. 2. 面试
          3. 3. 技术方向
          4. 4. 生活
          5. 5. 期待
          diff --git a/2020/02/09/G1收集器概述/index.html b/2020/02/09/G1收集器概述/index.html index b307f5e87a..cb089d8e07 100644 --- a/2020/02/09/G1收集器概述/index.html +++ b/2020/02/09/G1收集器概述/index.html @@ -4,7 +4,7 @@ - + @@ -32,14 +32,17 @@ + - + + - + + @@ -231,9 +234,8 @@ Posted on - - + @@ -297,8 +299,62 @@

          G1: The Garbage-First Collector, 垃圾回收优先的垃圾回收器，目标是用户多核 cpu 和大内存的机器，最大的特点就是可预测的停顿时间，官方给出的介绍是提供一个用户在大的堆内存情况下一个低延迟表现的解决方案，通常是 6GB 及以上的堆大小，有低于 0.5 秒稳定的可预测的停顿时间。

          -

          这里主要介绍这个比较新的垃圾回收器，在 G1 之前的垃圾回收器都是基于如下图的内存结构分布，有新生代，老年代和永久代（jdk8 之前），然后G1 往前的那些垃圾回收器都有个分代，比如 serial，parallel 等，一般有个应用的组合，最初的 serial 和 serial old，因为新生代和老年代的收集方式不太一样，新生代主要是标记复制，所以有 eden 跟两个 survival区，老年代一般用标记整理方式，而 G1 对这个不太一样。

          看一下 G1 的内存分布

          可以看到这有很大的不同，G1 通过将内存分成大小相等的 region，每个region是存在于一个连续的虚拟内存范围，对于某个 region 来说其角色是类似于原来的收集器的Eden、Survivor、Old Generation，这个具体在代码层面

          -
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          // We encode the value of the heap region type so the generation can be
           // determined quickly. The tag is split into two parts:
           //
           //   major type (young, old, humongous, archive)           : top N-1 bits
           //   minor type (eden / survivor, starts / cont hum, etc.) : bottom 1 bit
           //
           // If there's need to increase the number of minor types in the
           // future, we'll have to increase the size of the latter and hence
           // decrease the size of the former.
           //
           // 00000 0 [ 0] Free
           //
           // 00001 0 [ 2] Young Mask
           // 00001 0 [ 2] Eden
           // 00001 1 [ 3] Survivor
           //
           // 00010 0 [ 4] Humongous Mask
           // 00100 0 [ 8] Pinned Mask
           // 00110 0 [12] Starts Humongous
           // 00110 1 [13] Continues Humongous
           //
           // 01000 0 [16] Old Mask
           //
           // 10000 0 [32] Archive Mask
           // 11100 0 [56] Open Archive
           // 11100 1 [57] Closed Archive
           //
           typedef enum {
             FreeTag               = 0,

             YoungMask             = 2,
             EdenTag               = YoungMask,
             SurvTag               = YoungMask + 1,

             HumongousMask         = 4,
             PinnedMask            = 8,
             StartsHumongousTag    = HumongousMask | PinnedMask,
             ContinuesHumongousTag = HumongousMask | PinnedMask + 1,

             OldMask               = 16,
             OldTag                = OldMask,

             // Archive regions are regions with immutable content (i.e. not reclaimed, and
             // not allocated into during regular operation). They differ in the kind of references
             // allowed for the contained objects:
             // - Closed archive regions form a separate self-contained (closed) object graph
             // within the set of all of these regions. No references outside of closed
             // archive regions are allowed.
             // - Open archive regions have no restrictions on the references of their objects.
             // Objects within these regions are allowed to have references to objects
             // contained in any other kind of regions.
             ArchiveMask           = 32,
             OpenArchiveTag        = ArchiveMask | PinnedMask | OldMask,
             ClosedArchiveTag      = ArchiveMask | PinnedMask | OldMask + 1
           } Tag;
          +

          这里主要介绍这个比较新的垃圾回收器，在 G1 之前的垃圾回收器都是基于如下图的内存结构分布，有新生代，老年代和永久代（jdk8 之前），然后G1 往前的那些垃圾回收器都有个分代，比如 serial，parallel 等，一般有个应用的组合，最初的 serial 和 serial old，因为新生代和老年代的收集方式不太一样，新生代主要是标记复制，所以有 eden 跟两个 survival区，老年代一般用标记整理方式，而 G1 对这个不太一样。

          看一下 G1 的内存分布

          可以看到这有很大的不同，G1 通过将内存分成大小相等的 region，每个region是存在于一个连续的虚拟内存范围，对于某个 region 来说其角色是类似于原来的收集器的Eden、Survivor、Old Generation，这个具体在代码层面

          +
          // We encode the value of the heap region type so the generation can be
+ // determined quickly. The tag is split into two parts:
+ //
+ //   major type (young, old, humongous, archive)           : top N-1 bits
+ //   minor type (eden / survivor, starts / cont hum, etc.) : bottom 1 bit
+ //
+ // If there's need to increase the number of minor types in the
+ // future, we'll have to increase the size of the latter and hence
+ // decrease the size of the former.
+ //
+ // 00000 0 [ 0] Free
+ //
+ // 00001 0 [ 2] Young Mask
+ // 00001 0 [ 2] Eden
+ // 00001 1 [ 3] Survivor
+ //
+ // 00010 0 [ 4] Humongous Mask
+ // 00100 0 [ 8] Pinned Mask
+ // 00110 0 [12] Starts Humongous
+ // 00110 1 [13] Continues Humongous
+ //
+ // 01000 0 [16] Old Mask
+ //
+ // 10000 0 [32] Archive Mask
+ // 11100 0 [56] Open Archive
+ // 11100 1 [57] Closed Archive
+ //
+ typedef enum {
+   FreeTag               = 0,
+
+   YoungMask             = 2,
+   EdenTag               = YoungMask,
+   SurvTag               = YoungMask + 1,
+
+   HumongousMask         = 4,
+   PinnedMask            = 8,
+   StartsHumongousTag    = HumongousMask | PinnedMask,
+   ContinuesHumongousTag = HumongousMask | PinnedMask + 1,
+
+   OldMask               = 16,
+   OldTag                = OldMask,
+
+   // Archive regions are regions with immutable content (i.e. not reclaimed, and
+   // not allocated into during regular operation). They differ in the kind of references
+   // allowed for the contained objects:
+   // - Closed archive regions form a separate self-contained (closed) object graph
+   // within the set of all of these regions. No references outside of closed
+   // archive regions are allowed.
+   // - Open archive regions have no restrictions on the references of their objects.
+   // Objects within these regions are allowed to have references to objects
+   // contained in any other kind of regions.
+   ArchiveMask           = 32,
+   OpenArchiveTag        = ArchiveMask | PinnedMask | OldMask,
+   ClosedArchiveTag      = ArchiveMask | PinnedMask | OldMask + 1
+ } Tag;

          hotspot/share/gc/g1/heapRegionType.hpp

          当执行垃圾收集时，G1以类似于CMS收集器的方式运行。 G1执行并发全局标记阶段，以确定整个堆中对象的存活性。标记阶段完成后，G1知道哪些region是基本空的。它首先收集这些region，通常会产生大量的可用空间。这就是为什么这种垃圾收集方法称为“垃圾优先”的原因。顾名思义，G1将其收集和压缩活动集中在可能充满可回收对象（即垃圾）的堆区域。 G1使用暂停预测模型来满足用户定义的暂停时间目标，并根据指定的暂停时间目标选择要收集的区域数。

          @@ -319,7 +375,7 @@
          JVM源码分析之G1垃圾收集器分析一
        • -
          聊聊 dubbo 的线程池
          +
          聊聊 Dubbo 的容错机制
        • Maven实用小技巧
          @@ -328,7 +384,7 @@
          mybatis 的 $ 和 # 是有啥区别
        • -
          聊聊 Dubbo 的 SPI 续之自适应拓展
          +
          mybatis 的缓存是怎么回事
        diff --git a/2020/02/16/Maven实用小技巧/index.html b/2020/02/16/Maven实用小技巧/index.html index aae90fd31e..57a1cfd021 100644 --- a/2020/02/16/Maven实用小技巧/index.html +++ b/2020/02/16/Maven实用小技巧/index.html @@ -4,7 +4,7 @@ - + @@ -32,8 +32,9 @@ + - + @@ -226,9 +227,8 @@         Posted on - - +         @@ -297,15 +297,55 @@
      • mvn deploy
        将打出来的 jar 包上传到远程仓库里

      与 composer 对比

      因为我也是个 PHP 程序员，所以对比一下两种语言，很容易想到在 PHP 的 composer 跟 Java 的 maven 是比较类似的作用，有一点两者是非常相似的，就是原仓库都是因为某些原因连接拉取都会很慢，所以像 composer 会有一些国内源，前阵子阿里也出了一个，类似的 maven 一般也会使用阿里的镜像仓库，通过在 setting.xml 文件中的设置

      -
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      <mirrors>
          <mirror>
              <id>aliyun</id>
              <name>aliyun maven</name>
              <url>http://maven.aliyun.com/nexus/content/groups/public/</url>
              <mirrorOf>central</mirrorOf>
          </mirror> 
      </mirrors>
      +
      <mirrors>
+    <mirror>
+        <id>aliyun</id>
+        <name>aliyun maven</name>
+        <url>http://maven.aliyun.com/nexus/content/groups/public/</url>
+        <mirrorOf>central</mirrorOf>
+    </mirror> 
+</mirrors>

      这算是个尴尬的共同点，然后因为 PHP 是解释型脚本语言，所以 php 打出来的 composer 包其实就是个 php 代码包，使用SPL Autoload等方式加载代码包，maven 包则是经过编译的 class 包，还有一点是 composer 也可以直接使用 github 地址作为包代码的拉取源，这点也是比较大的区别，maven使用 pom 文件管理依赖

      maven 的个人小技巧

      • maven 拉取依赖时，同时将 snapshot 也更新了，就是 mvn compile加个-U参数，如果还不行就需要将本地仓库的 snapshot 删掉，
        这个命令的 help 命令解释是 -U,–update-snapshots Forces a check for missing releases and updated snapshots on
        remote repositories，这个在日常使用中还是很经常使用的
        • -
      • maven 出现依赖冲突的时候的解决方法
        首先是依赖分析，使用mvn dependency:tree分析下依赖关系，如果要找具体某个包的依赖引用关系可以使用mvn dependency:tree -Dverbose -Dincludes=org.springframework:spring-webmvc命令进行分析，如果发现有冲突的依赖关系，本身 maven 中依赖引用有相对的顺序，大致来说是引用路径短的优先，pom 文件中定义的顺序优先，如果要把冲突的包排除掉可以在 pom 中用
        1
        2
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        6
        <exclusions>
          <exclusion>
              <groupId>ch.qos.logback</groupId>
              <artifactId>logback-classic</artifactId>
          </exclusion>
        </exclusions>
        +
      • maven 出现依赖冲突的时候的解决方法
        首先是依赖分析，使用mvn dependency:tree分析下依赖关系，如果要找具体某个包的依赖引用关系可以使用mvn dependency:tree -Dverbose -Dincludes=org.springframework:spring-webmvc命令进行分析，如果发现有冲突的依赖关系，本身 maven 中依赖引用有相对的顺序，大致来说是引用路径短的优先，pom 文件中定义的顺序优先，如果要把冲突的包排除掉可以在 pom 中用
        <exclusions>
+  <exclusion>
+      <groupId>ch.qos.logback</groupId>
+      <artifactId>logback-classic</artifactId>
+  </exclusion>
+</exclusions>
        将冲突的包排除掉
        • -
      • maven 依赖的 jdk 版本管理
        前面介绍的mvn -v可以查看 maven 的安装信息
        比如
        1
        2
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        Apache Maven 3.6.3 (cecedd343002696d0abb50b32b541b8a6ba2883f)
        Maven home: /usr/local/Cellar/maven/3.6.3_1/libexec
        Java version: 1.8.0_201, vendor: Oracle Corporation, runtime: /Library/Java/JavaVirtualMachines/jdk1.8.0_201.jdk/Contents/Home/jre
        Default locale: zh_CN, platform encoding: UTF-8
        OS name: "mac os x", version: "10.14.6", arch: "x86_64", family: "mac"
        -这里可以看到用了 mac 自带的 jdk1.8，结合我之前碰到的一个问题，因为使用 homebrew 升级了 gradle，而 gradle 又依赖了 jdk13，因为这个 mvn 的 Java version 也变成 jdk13 了，然后 mvn 编译的时候出现了 java.lang.ExceptionInInitializerError: com.sun.tools.javac.code.TypeTags这个问题，所以需要把这个版本给改回来，但是咋改呢，网上搜来的一大堆都是在 pom 文件里的
        source和 target 版本
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        <build>
          <plugins>
        <plugin>
        	<groupId>org.apache.maven.plugins</groupId>
        	<artifactId>maven-compiler-plugin</artifactId>
        	<configuration>
        		<source>1.8</source>
        		<target>1.8</target>
        		<encoding>UTF-8</encoding>
        	</configuration>
        </plugin>
          </plugins>
        <build>
        -或者修改 maven 的 setting.xml中的
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        <profiles>
              <profile>
                  <id>ngmm-nexus</id>
                <activation>
                  <jdk>1.8</jdk>
                </activation>
                <properties>
                  <maven.compiler.source>1.8</maven.compiler.source>
                  <maven.compiler.target>1.8</maven.compiler.target>
                  <maven.compiler.compilerVersion>1.8</maven.compiler.compilerVersion>
              </properties>
              </profile>
        </profiles>
        +
      • maven 依赖的 jdk 版本管理
        前面介绍的mvn -v可以查看 maven 的安装信息
        比如
        Apache Maven 3.6.3 (cecedd343002696d0abb50b32b541b8a6ba2883f)
+Maven home: /usr/local/Cellar/maven/3.6.3_1/libexec
+Java version: 1.8.0_201, vendor: Oracle Corporation, runtime: /Library/Java/JavaVirtualMachines/jdk1.8.0_201.jdk/Contents/Home/jre
+Default locale: zh_CN, platform encoding: UTF-8
+OS name: "mac os x", version: "10.14.6", arch: "x86_64", family: "mac"
        +这里可以看到用了 mac 自带的 jdk1.8，结合我之前碰到的一个问题，因为使用 homebrew 升级了 gradle，而 gradle 又依赖了 jdk13，因为这个 mvn 的 Java version 也变成 jdk13 了，然后 mvn 编译的时候出现了 java.lang.ExceptionInInitializerError: com.sun.tools.javac.code.TypeTags这个问题，所以需要把这个版本给改回来，但是咋改呢，网上搜来的一大堆都是在 pom 文件里的
        source和 target 版本
        <build>
+  <plugins>
+<plugin>
+	<groupId>org.apache.maven.plugins</groupId>
+	<artifactId>maven-compiler-plugin</artifactId>
+	<configuration>
+		<source>1.8</source>
+		<target>1.8</target>
+		<encoding>UTF-8</encoding>
+	</configuration>
+</plugin>
+  </plugins>
+<build>
        +或者修改 maven 的 setting.xml中的
        <profiles>
+      <profile>
+          <id>ngmm-nexus</id>
+        <activation>
+          <jdk>1.8</jdk>
+        </activation>
+        <properties>
+          <maven.compiler.source>1.8</maven.compiler.source>
+          <maven.compiler.target>1.8</maven.compiler.target>
+          <maven.compiler.compilerVersion>1.8</maven.compiler.compilerVersion>
+      </properties>
+      </profile>
+</profiles>
        但是这些都没啥用啊，真正有办法的是建个 .mavenrc，这个顾名思义就是 maven 的资源文件，类似于 .bashrc和.zshrc，在里面添加 MAVEN_HOME 和 JAVA_HOME,然后执行 source .mavenrc就 OK 啦
      @@ -318,7 +358,7 @@
      Related Posts
      @@ -456,7 +496,7 @@
      -
      1. 1. maven的基本操作
      2. 2. 与 composer 对比
      3. 3. maven 的个人小技巧
      +
      1. 1. maven的基本操作
      2. 2. 与 composer 对比
      3. 3. maven 的个人小技巧
      diff --git a/2020/02/22/gogs使用webhook部署react单页应用/index.html b/2020/02/22/gogs使用webhook部署react单页应用/index.html index ff9dde6405..b18c890dad 100644 --- a/2020/02/22/gogs使用webhook部署react单页应用/index.html +++ b/2020/02/22/gogs使用webhook部署react单页应用/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,12 @@ + - + - @@ -230,13 +230,6 @@       - - - - - Edited on - - @@ -286,23 +279,88 @@
      -

      众所周知，我是个前端彩笔，但是也想做点自己可以用的工具页面，所以就让朋友推荐了蚂蚁出品的 ant design，说基本可以直接 ctrl-c ctrl-v，实测对我这种来说还是有点难的，不过也能写点，但是现在碰到的问题是怎么部署到自己的服务器上去
      用 ant design 写的是个单页应用，实际来说就是一个 html 加 css 跟 js，最初的时候是直接 build 完就 scp 上去，也考虑过 rsync 之类的，但是都感觉不够自动化，正好自己还没这方面的经验就想折腾下，因为我自己搭的仓库应用是 gogs，搜了一下主要是跟 drones 配合做 ci/cd，研究了一下发现其实这个事情没必要这么搞(PS：drone 也不好用)，整个 hook 就可以了, 但是实际上呢，这东西也不是那么简单
      首先是需要在服务器上装 webhook，这个我一开始用 snap 安装，但是出现问题，run 的时候会出现后面参数带的 hooks.json 文件找不到，然后索性就直接 github 上下最新版，放 /usr/local/bin 了，webhook 的原理呢其实也比较简单，就是起一个 http 服务，通过 post 请求调用，解析下参数，如果跟配置的参数一致，就调用对应的命令或者脚本。

      +

      众所周知，我是个前端彩笔，但是也想做点自己可以用的工具页面，所以就让朋友推荐了蚂蚁出品的 ant design，说基本可以直接 ctrl-c ctrl-v，实测对我这种来说还是有点难的，不过也能写点，但是现在碰到的问题是怎么部署到自己的服务器上去
      用 ant design 写的是个单页应用，实际来说就是一个 html 加 css 跟 js，最初的时候是直接 build 完就 scp 上去，也考虑过 rsync 之类的，但是都感觉不够自动化，正好自己还没这方面的经验就想折腾下，因为我自己搭的仓库应用是 gogs，搜了一下主要是跟 drones 配合做 ci/cd，研究了一下发现其实这个事情没必要这么搞(PS：drone 也不好用)，整个 hook 就可以了, 但是实际上呢，这东西也不是那么简单
      首先是需要在服务器上装 webhook，这个我一开始用 snap 安装，但是出现问题，run 的时候会出现后面参数带的 hooks.json 文件找不到，然后索性就直接 github 上下最新版，放 /usr/local/bin 了，webhook 的原理呢其实也比较简单，就是起一个 http 服务，通过 post 请求调用，解析下参数，如果跟配置的参数一致，就调用对应的命令或者脚本。

      配置 hooks.json

      webhook 的配置，需要的两个文件，一个是 hooks.json，这个是 webhook 服务的配置文件，像这样

      -
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      [
        {
          "id": "redeploy-app",
          "execute-command": "/opt/scripts/redeploy.sh",
          "command-working-directory": "/opt/scripts",
          "pass-arguments-to-command":
          [
            {
              "source": "payload",
              "name": "head_commit.message"
            },
            {
              "source": "payload",
              "name": "pusher.name"
            },
            {
              "source": "payload",
              "name": "head_commit.id"
            }
          ],
          "trigger-rule":
          {
            "and":
            [
              {
                "match":
                {
                  "type": "payload-hash-sha1",
                  "secret": "your-github-secret",
                  "parameter":
                  {
                    "source": "header",
                    "name": "X-Hub-Signature"
                  }
                }
              },
              {
                "match":
                {
                  "type": "value",
                  "value": "refs/heads/master",
                  "parameter":
                  {
                    "source": "payload",
                    "name": "ref"
                  }
                }
              }
            ]
          }
        }
      ]
      +
      [
+  {
+    "id": "redeploy-app",
+    "execute-command": "/opt/scripts/redeploy.sh",
+    "command-working-directory": "/opt/scripts",
+    "pass-arguments-to-command":
+    [
+      {
+        "source": "payload",
+        "name": "head_commit.message"
+      },
+      {
+        "source": "payload",
+        "name": "pusher.name"
+      },
+      {
+        "source": "payload",
+        "name": "head_commit.id"
+      }
+    ],
+    "trigger-rule":
+    {
+      "and":
+      [
+        {
+          "match":
+          {
+            "type": "payload-hash-sha1",
+            "secret": "your-github-secret",
+            "parameter":
+            {
+              "source": "header",
+              "name": "X-Hub-Signature"
+            }
+          }
+        },
+        {
+          "match":
+          {
+            "type": "value",
+            "value": "refs/heads/master",
+            "parameter":
+            {
+              "source": "payload",
+              "name": "ref"
+            }
+          }
+        }
+      ]
+    }
+  }
+]

      这是个跟 github搭配的示例，首先 id 表示的是这个对应 hook 的识别 id，也可以看到这个 hooks.json 的结构是这样的一个数组，然后就是要执行的命令和命令执行的参数，值得注意的是这个trigger-rule,就是请求进来了回去匹配里面的，比如前一个是一个加密的，放在请求头里，第二个 match 表示请求里的 ref 是个 master 分支，就可以区分分支进行不同操作，但是前面的加密配合 gogs 使用的时候有个问题(PS: webhook 的文档是真的烂)，gogs 设置 webhook 的加密是用的

      密钥文本将被用于计算推送内容的 SHA256 HMAC 哈希值，并设置为 X-Gogs-Signature 请求头的值。

      -

      这种加密方式，所以 webhook 的这个示例的加密方式不行，但这货的文档里居然没有说明支持哪些加密，神TM，后来还是翻 issue 翻到了, 需要使用这个payload-hash-sha256

      +

      这种加密方式，所以 webhook 的这个示例的加密方式不行，但这货的文档里居然没有说明支持哪些加密，神TM，后来还是翻 issue 翻到了, 需要使用这个payload-hash-sha256

      执行脚本 redeploy.sh

      脚本类似于这样

      -
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      #!/bin/bash -e

      function cleanup {
            echo "Error occoured"
      }
      trap cleanup ERR

      commit_message=$1 # head_commit.message
      pusher_name=$2 # pusher.name
      commit_id=$3 # head_commit.id


      cd ~/do-react-example-app/
      git pull origin master
      yarn && yarn build
      +
      #!/bin/bash -e
+
+function cleanup {
+      echo "Error occoured"
+}
+trap cleanup ERR
+
+commit_message=$1 # head_commit.message
+pusher_name=$2 # pusher.name
+commit_id=$3 # head_commit.id
+
+
+cd ~/do-react-example-app/
+git pull origin master
+yarn && yarn build

      就是简单的拉代码，然后构建下，真实使用时可能不是这样，因为页面会部署在 nginx 的作用目录，还需要 rsync 过去，这部分可能还涉及到两个问题第一个是使用 rsync 还是其他的 cp，不过这个无所谓；第二个是目录权限的问题，以我的系统ubuntu 为例，默认用户是 ubuntu，nginx 部署的目录是 www，所以需要切换用户等操作，一开始是想用在shell 文件中直接写了密码，但是不知道咋传，查了下是类似于这样 echo "passwd" | sudo -S cmd，通过管道命令往后传，然后就是这个-S, 参数的解释是-S, --stdin read password from standard input,但是这样么也不是太安全的赶脚，又看了下还有两种方法，

      • 就是给root 设置一个不需要密码的命令类似于这样，

        -
        1
        2
        myusername ALL = (ALL) ALL
        myusername ALL = (root) NOPASSWD: /path/to/my/program
        -
        • +
        myusername ALL = (ALL) ALL
+myusername ALL = (root) NOPASSWD: /path/to/my/program

      • 另一种就是把默认用户跟 root 设置成同一个 group 的

      @@ -437,7 +495,7 @@
      -
      1. 1. 配置 hooks.json
      2. 2. 执行脚本 redeploy.sh
      3. 3. 使用
      +
      1. 1. 配置 hooks.json
      2. 2. 执行脚本 redeploy.sh
      3. 3. 使用
      diff --git a/2020/03/01/寄生虫观后感/index.html b/2020/03/01/寄生虫观后感/index.html index 6b77cf828b..c34e2968a3 100644 --- a/2020/03/01/寄生虫观后感/index.html +++ b/2020/03/01/寄生虫观后感/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,13 @@ + - + + - @@ -227,9 +228,8 @@ Posted on - - + @@ -307,16 +307,16 @@
      在老丈人家的小工记五
    • -
      2019年终总结
      +
      2020年中总结
    • 2020 年终总结
    • -
      周末我在老丈人家打了天小工
      +
      从丁仲礼被美国制裁聊点啥
    • -
      从清华美院学姐聊聊我们身边的恶人
      +
      关于公共交通再吐个槽
    diff --git a/2020/03/08/docker比一般多一点的初学者介绍/index.html b/2020/03/08/docker比一般多一点的初学者介绍/index.html index 4ccb8819fe..c653e7539d 100644 --- a/2020/03/08/docker比一般多一点的初学者介绍/index.html +++ b/2020/03/08/docker比一般多一点的初学者介绍/index.html @@ -4,7 +4,7 @@ - + @@ -32,6 +32,7 @@ + @@ -41,7 +42,7 @@ - + @@ -239,13 +240,6 @@     - - - - - Edited on - - @@ -304,41 +298,43 @@

    之前写的 mysql 集群，一主二备，这种架构在很多小型应用里都是这么配置的，而且一般是直接在三台 vps 里启动三个 mysql 实例，但是如果换成 docker 会有什么好处呢，其实就是方便部署，比如其中一台备库挂了，我要加一台，或者说备库的 qps 太高了，需要再加一个，如果要在 vps 上搭建的话，首先要买一台机器，等初始化，然后在上面修改源，更新，装 mysql ，然后配置主从，可能还要处理防火墙等等，如果把这些打包成一个 docker 镜像，并且放在自己的 docker registry，那就直接run 一下就可以了；还有比如在公司要给一个新同学整一套开发测试环境，以 Java 开发为例，要装 git，maven，jdk，配置 maven settings 和各种 rc，整合在一个镜像里的话，就会很方便了；再比如微服务的水平扩展。

    但是为啥 docker 会有这种优势，听起来好像虚拟机也可以干这个事，但是虚拟机动辄上 G，而且需要 VMware，virtual box 等支持，不适合在Linux服务器环境使用，而且占用资源也会非常大。说得这么好，那么 docker 是啥呢

    docker 主要使用 Linux 中已经存在的两种技术的一个整合升级，一个是 namespace，一个是cgroups，相比于虚拟机需要完整虚拟出一个操作系统运行基础，docker 基于宿主机内核，通过 namespace 和 cgroups 分隔进程，理念就是提供一个隔离的最小化运行依赖，这样子相对于虚拟机就有了巨大的便利性，具体的 namespace 和 cgroups 就先不展开讲，可以参考耗子叔的文章

    -

    安装

    那么我们先安装下 docker，参考官方的教程，安装，我的系统是 ubuntu 的，就贴了 ubuntu 的链接，用其他系统的可以找到对应的系统文档安装，安装完了的话看看 docker 的信息

    -
    1
    sudo docker info
    +

    安装

    那么我们先安装下 docker，参考官方的教程，安装，我的系统是 ubuntu 的，就贴了 ubuntu 的链接，用其他系统的可以找到对应的系统文档安装，安装完了的话看看 docker 的信息

    +
    sudo docker info
    -

    输出以下信息

    +

    输出以下信息

    简单运行

    然后再来运行个 hello world 呗，

    -
    1
    sudo docker run hello-world
    +
    sudo docker run hello-world
    -

    输出了这些

    +

    输出了这些

    看看这个运行命令是怎么用的，一般都会看到这样子的，sudo docker run -it ubuntu bash, 前面的 docker run 反正就是运行一个容器的意思，-it是啥呢，还有这个什么 ubuntu bash，来看看docker run`的命令帮助信息

    -
    1
    -i, --interactive                    Keep STDIN open even if not attached
    +
    -i, --interactive                    Keep STDIN open even if not attached

    就是要有输入，我们运行的时候能输入

    -
    1
    -t, --tty                            Allocate a pseudo-TTY
    +
    -t, --tty                            Allocate a pseudo-TTY

    要有个虚拟终端，

    -
    1
    2
    3
    Usage:	docker run [OPTIONS] IMAGE [COMMAND] [ARG...]

    Run a command in a new container
    +
    Usage:	docker run [OPTIONS] IMAGE [COMMAND] [ARG...]
+
+Run a command in a new container

    镜像

    上面说的-it 就是这里的 options，后面那个 ubuntu 就是 image 辣，image 是啥呢

    Docker 把应用程序及其依赖，打包在 image 文件里面，可以把它理解成为类似于虚拟机的镜像或者运行一个进程的代码，跑起来了的叫docker 容器或者进程，比如我们将要运行的docker run -it ubuntu bash的ubuntu 就是个 ubuntu 容器的镜像，将这个镜像运行起来后，我们可以进入容器像使用 ubuntu 一样使用它，来看下我们的镜像，使用sudo docker image ls就能列出我们宿主机上的 docker 镜像了

    -

    +

    一个 ubuntu 镜像才 64MB，非常小巧，然后是后面的bash，我通过交互式启动了一个 ubuntu 容器，然后在这个启动的容器里运行了 bash 命令，这样就可以在容器里玩一下了

    -

    在容器里看下进程，

    +

    在容器里看下进程，

    只有刚才运行容器的 bash 进程和我刚执行的 ps，这里有个可以注意下的，bash 这个进程的 pid 是 1，其实这里就用到了 linux 中的PID Namespace，容器会隔离出一个 pid 的名字空间，这里面的进程跟外部的 pid 命名独立

    -

    查看宿主机上的容器

    1
    sudo docker ps -a
    +

    查看宿主机上的容器

    sudo docker ps -a
    -

    +

    如何进入一个正在运行中的 docker 容器

    这个应该是比较常用的，因为比如是一个微服务容器，有时候就像看下运行状态，日志啥的

    -
    1
    sudo docker exec -it [containerID] bash
    +
    sudo docker exec -it [containerID] bash
    -

    -

    查看日志

    1
    sudo docker logs [containerID]
    +

    +

    查看日志

    sudo docker logs [containerID]

    我在运行容器的终端里胡乱输入点啥，然后通过上面的命令就可以看到啦

    -

    -

    +

    +

    @@ -482,7 +478,7 @@
    -
    1. 1. 安装
    2. 2. 简单运行
    3. 3. 镜像
    4. 4. 在容器里看下进程，
    5. 5. 查看宿主机上的容器
    6. 6. 如何进入一个正在运行中的 docker 容器
    7. 7. 查看日志
    +
    1. 1. 安装
    2. 2. 简单运行
    3. 3. 镜像
    4. 4. 在容器里看下进程，
    5. 5. 查看宿主机上的容器
    6. 6. 如何进入一个正在运行中的 docker 容器
    7. 7. 查看日志
    diff --git a/2020/03/15/docker比一般多一点的初学者介绍二/index.html b/2020/03/15/docker比一般多一点的初学者介绍二/index.html index 8301a9b3f2..32e21f3764 100644 --- a/2020/03/15/docker比一般多一点的初学者介绍二/index.html +++ b/2020/03/15/docker比一般多一点的初学者介绍二/index.html @@ -4,7 +4,7 @@ - + @@ -26,12 +26,13 @@ var CONFIG = {"hostname":"nicksxs.me","root":"/","scheme":"Pisces","version":"7.8.0","exturl":false,"sidebar":{"position":"left","display":"post","padding":18,"offset":12,"onmobile":false},"copycode":{"enable":true,"show_result":false,"style":null},"back2top":{"enable":true,"sidebar":false,"scrollpercent":false},"bookmark":{"enable":false,"color":"#222","save":"auto"},"fancybox":true,"mediumzoom":false,"lazyload":true,"pangu":false,"comments":{"style":"tabs","active":null,"storage":true,"lazyload":false,"nav":null},"algolia":{"hits":{"per_page":10},"labels":{"input_placeholder":"Search for Posts","hits_empty":"We didn't find any results for the search: ${query}","hits_stats":"${hits} results found in ${time} ms"}},"localsearch":{"enable":false,"trigger":"auto","top_n_per_article":1,"unescape":false,"preload":false},"motion":{"enable":true,"async":false,"transition":{"post_block":"fadeIn","post_header":"slideDownIn","post_body":"slideDownIn","coll_header":"slideLeftIn","sidebar":"slideUpIn"}}}; - + - + + @@ -42,12 +43,11 @@ - + - @@ -241,13 +241,6 @@     - - - - - Edited on - - @@ -302,17 +295,31 @@

    限制下 docker 的 cpu 使用率

    这里我们开始玩一点有意思的，我们在容器里装下 vim 和 gcc，然后写这样一段 c 代码

    -
    1
    2
    3
    4
    5
    6
    7
    #include <stdio.h>
    int main(void)
    {
        int i = 0;
        for(;;) i++;
        return 0;
    }
    +
    #include <stdio.h>
+int main(void)
+{
+    int i = 0;
+    for(;;) i++;
+    return 0;
+}

    就是一个最简单的死循环，然后在容器里跑起来

    -
    1
    2
    $ gcc 1.c 
    $ ./a.out
    +
    $ gcc 1.c 
+$ ./a.out

    然后我们来看下系统资源占用（CPU）
    Xs562iawhHyMxeO
    上图是在容器里的，可以看到 cpu 已经 100%了
    然后看看容器外面的
    ecqH8XJ4k7rKhzu
    可以看到一个核的 cpu 也被占满了，因为是个双核的机器，并且代码是单线程的
    然后呢我们要做点啥
    因为已经在这个 ubuntu 容器中装了 vim 和 gcc，考虑到国内的网络，所以我们先把这个容器 commit 一下，

    -
    1
    docker commit -a "nick" -m "my ubuntu" f63c5607df06 my_ubuntu:v1
    +
    docker commit -a "nick" -m "my ubuntu" f63c5607df06 my_ubuntu:v1

    然后再运行起来

    -
    1
    docker run -it --cpus=0.1 my_ubuntu:v1 bash
    -


    我们的代码跟可执行文件都还在，要的就是这个效果，然后再运行一下

    结果是这个样子的，有点神奇是不，关键就在于 run 的时候的--cpus=0.1这个参数，它其实就是基于我前一篇说的 cgroup 技术，能将进程之间的cpu，内存等资源进行隔离

    +
    docker run -it --cpus=0.1 my_ubuntu:v1 bash
    +


    我们的代码跟可执行文件都还在，要的就是这个效果，然后再运行一下

    结果是这个样子的，有点神奇是不，关键就在于 run 的时候的--cpus=0.1这个参数，它其实就是基于我前一篇说的 cgroup 技术，能将进程之间的cpu，内存等资源进行隔离

    开始第一个 Dockerfile

    上一面为了复用那个我装了 vim 跟 gcc 的容器，我把它提交到了本地，使用了docker commit命令，有点类似于 git 的 commit，但是这个不是个很好的操作方式，需要手动介入，这里更推荐使用 Dockerfile 来构建镜像

    -
    1
    2
    3
    4
    5
    6
    7
    8
    From ubuntu:latest
    MAINTAINER Nicksxs "nicksxs@hotmail.com"
    RUN  sed -i s@/archive.ubuntu.com/@/mirrors.aliyun.com/@g /etc/apt/sources.list
    RUN apt-get clean
    RUN apt-get update && apt install -y nginx
    RUN echo 'Hi, i am in container' \
        > /usr/share/nginx/html/index.html
    EXPOSE 80
    -

    先解释下这是在干嘛，首先是这个From ubuntu:latest基于的 ubuntu 的最新版本的镜像，然后第二行是维护人的信息，第三四行么作为墙内人你懂的，把 ubuntu 的源换成阿里云的，不然就有的等了，然后就是装下 nginx，往默认的 nginx 的入口 html 文件里输入一行欢迎语，然后暴露 80 端口
    然后我们使用sudo docker build -t="nicksxs/static_web" .命令来基于这个 Dockerfile 构建我们自己的镜像，过程中是这样的


    可以看到图中，我的 Dockerfile 是 7 行，里面就执行了 7 步，并且每一步都有一个类似于容器 id 的层 id 出来，这里就是一个比较重要的东西，docker 在构建的时候其实是有这个层的概念，Dockerfile 里的每一行都会往上加一层，这里有还注意下命令后面的.，代表当前目录下会自行去寻找 Dockerfile 进行构建，构建完了之后我们再看下我们的本地镜像

    我们自己的镜像出现啦
    然后有个问题，如果这个构建中途报了错咋办呢，来试试看，我们把 nginx 改成随便的一个错误名，nginxx(不知道会不会运气好真的有这玩意)，再来 build 一把

    找不到 nginxx 包，是不是这个镜像就完全不能用呢，当然也不是，因为前面说到了，docker 是基于层去构建的，可以看到前面的 4 个 step 都没报错，那我们基于最后的成功步骤创建下容器看看
    也就是sudo docker run -t -i bd26f991b6c8 /bin/bash
    答案是可以的，只是没装成功 nginx

    还有一点注意到没，前面的几个 step 都有一句 Using cache，说明 docker 在构建镜像的时候是有缓存的，这也更能说明 docker 是基于层去构建镜像，同样的底包，同样的步骤，这些层是可以被复用的，这就是 docker 的构建缓存，当然我们也可以在 build 的时候加上--no-cache去把构建缓存禁用掉。

    +
    From ubuntu:latest
+MAINTAINER Nicksxs "nicksxs@hotmail.com"
+RUN  sed -i s@/archive.ubuntu.com/@/mirrors.aliyun.com/@g /etc/apt/sources.list
+RUN apt-get clean
+RUN apt-get update && apt install -y nginx
+RUN echo 'Hi, i am in container' \
+    > /usr/share/nginx/html/index.html
+EXPOSE 80
    +

    先解释下这是在干嘛，首先是这个From ubuntu:latest基于的 ubuntu 的最新版本的镜像，然后第二行是维护人的信息，第三四行么作为墙内人你懂的，把 ubuntu 的源换成阿里云的，不然就有的等了，然后就是装下 nginx，往默认的 nginx 的入口 html 文件里输入一行欢迎语，然后暴露 80 端口
    然后我们使用sudo docker build -t="nicksxs/static_web" .命令来基于这个 Dockerfile 构建我们自己的镜像，过程中是这样的


    可以看到图中，我的 Dockerfile 是 7 行，里面就执行了 7 步，并且每一步都有一个类似于容器 id 的层 id 出来，这里就是一个比较重要的东西，docker 在构建的时候其实是有这个层的概念，Dockerfile 里的每一行都会往上加一层，这里有还注意下命令后面的.，代表当前目录下会自行去寻找 Dockerfile 进行构建，构建完了之后我们再看下我们的本地镜像

    我们自己的镜像出现啦
    然后有个问题，如果这个构建中途报了错咋办呢，来试试看，我们把 nginx 改成随便的一个错误名，nginxx(不知道会不会运气好真的有这玩意)，再来 build 一把

    找不到 nginxx 包，是不是这个镜像就完全不能用呢，当然也不是，因为前面说到了，docker 是基于层去构建的，可以看到前面的 4 个 step 都没报错，那我们基于最后的成功步骤创建下容器看看
    也就是sudo docker run -t -i bd26f991b6c8 /bin/bash
    答案是可以的，只是没装成功 nginx

    还有一点注意到没，前面的几个 step 都有一句 Using cache，说明 docker 在构建镜像的时候是有缓存的，这也更能说明 docker 是基于层去构建镜像，同样的底包，同样的步骤，这些层是可以被复用的，这就是 docker 的构建缓存，当然我们也可以在 build 的时候加上--no-cache去把构建缓存禁用掉。

    @@ -456,7 +463,7 @@
    -
    1. 1. 限制下 docker 的 cpu 使用率
    2. 2. 开始第一个 Dockerfile
    +
    1. 1. 限制下 docker 的 cpu 使用率
    2. 2. 开始第一个 Dockerfile
    diff --git a/2020/03/21/docker比一般多一点的初学者介绍三/index.html b/2020/03/21/docker比一般多一点的初学者介绍三/index.html index 22202e30b2..c083f22173 100644 --- a/2020/03/21/docker比一般多一点的初学者介绍三/index.html +++ b/2020/03/21/docker比一般多一点的初学者介绍三/index.html @@ -4,7 +4,7 @@ - + @@ -26,12 +26,13 @@ var CONFIG = {"hostname":"nicksxs.me","root":"/","scheme":"Pisces","version":"7.8.0","exturl":false,"sidebar":{"position":"left","display":"post","padding":18,"offset":12,"onmobile":false},"copycode":{"enable":true,"show_result":false,"style":null},"back2top":{"enable":true,"sidebar":false,"scrollpercent":false},"bookmark":{"enable":false,"color":"#222","save":"auto"},"fancybox":true,"mediumzoom":false,"lazyload":true,"pangu":false,"comments":{"style":"tabs","active":null,"storage":true,"lazyload":false,"nav":null},"algolia":{"hits":{"per_page":10},"labels":{"input_placeholder":"Search for Posts","hits_empty":"We didn't find any results for the search: ${query}","hits_stats":"${hits} results found in ${time} ms"}},"localsearch":{"enable":false,"trigger":"auto","top_n_per_article":1,"unescape":false,"preload":false},"motion":{"enable":true,"async":false,"transition":{"post_block":"fadeIn","post_header":"slideDownIn","post_body":"slideDownIn","coll_header":"slideLeftIn","sidebar":"slideUpIn"}}}; - + - + + @@ -40,16 +41,11 @@ - + - - - - - @@ -240,9 +236,8 @@     Posted on - - +     @@ -298,15 +293,19 @@

    运行第一个 Dockerfile

    上一篇的 Dockerfile 我们停留在构建阶段，现在来把它跑起来

    -
    1
    2
    docker run -d -p 80 --name static_web nicksxs/static_web \
    nginx -g "daemon off;"
    -

    这里的-d表示以分离模型运行docker (detached),然后-p 是表示将容器的 80 端口开放给宿主机，然后容器名就叫 static_web,使用了我们上次构建的 static_web 镜像，后面的是让 nginx 在前台运行

    可以看到返回了个容器 id，但是具体情况没出现，也没连上去，那我们想看看怎么访问在 Dockerfile 里写的静态页面，我们来看下docker 进程

    发现为我们随机分配了一个宿主机的端口，32768，去服务器的防火墙把这个外网端口开一下，看看是不是符合我们的预期呢

    好像不太对额，应该是 ubuntu 安装的 nginx 的默认工作目录不对，我们来进容器看看，再熟悉下命令docker exec -it 4792455ca2ed /bin/bash
    记得容器 id 换成自己的，进入容器后得找找 nginx 的配置文件，通常在/etc/nginx,/usr/local/etc等目录下，然后找到我们的目录是在这

    所以把刚才的内容复制过去再试试

    目标达成，give me five✌️

    +
    docker run -d -p 80 --name static_web nicksxs/static_web \
+nginx -g "daemon off;"
    +

    这里的-d表示以分离模型运行docker (detached),然后-p 是表示将容器的 80 端口开放给宿主机，然后容器名就叫 static_web,使用了我们上次构建的 static_web 镜像，后面的是让 nginx 在前台运行

    可以看到返回了个容器 id，但是具体情况没出现，也没连上去，那我们想看看怎么访问在 Dockerfile 里写的静态页面，我们来看下docker 进程

    发现为我们随机分配了一个宿主机的端口，32768，去服务器的防火墙把这个外网端口开一下，看看是不是符合我们的预期呢

    好像不太对额，应该是 ubuntu 安装的 nginx 的默认工作目录不对，我们来进容器看看，再熟悉下命令docker exec -it 4792455ca2ed /bin/bash
    记得容器 id 换成自己的，进入容器后得找找 nginx 的配置文件，通常在/etc/nginx,/usr/local/etc等目录下，然后找到我们的目录是在这

    所以把刚才的内容复制过去再试试

    目标达成，give me five✌️

    第二个 Dockerfile

    然后就想来动态一点的，毕竟写过 PHP，就来试试 PHP
    再建一个目录叫 dynamic_web，里面创建 src 目录，放一个 index.php
    内容是

    -
    1
    2
    <?php
    echo "Hello World!";
    +
    <?php
+echo "Hello World!";

    然后在 dynamic_web 目录下创建 Dockerfile，

    -
    1
    2
    3
    FROM trafex/alpine-nginx-php7:latest
    COPY src/ /var/www/html
    EXPOSE 80
    +
    FROM trafex/alpine-nginx-php7:latest
+COPY src/ /var/www/html
+EXPOSE 80

    Dockerfile 虽然只有三行，不过要着重说明下，这个底包其实不是docker 官方的，有两点考虑，一点是官方的基本都是 php apache 的镜像，还有就是 alpine这个，截取一段中文介绍

    -

    Alpine 操作系统是一个面向安全的轻型 Linux 发行版。它不同于通常 Linux 发行版，Alpine 采用了 musl libc 和 busybox 以减小系统的体积和运行时资源消耗，但功能上比 busybox 又完善的多，因此得到开源社区越来越多的青睐。在保持瘦身的同时，Alpine 还提供了自己的包管理工具 apk，可以通过 https://pkgs.alpinelinux.org/packages 网站上查询包信息，也可以直接通过 apk 命令直接查询和安装各种软件。
    Alpine 由非商业组织维护的，支持广泛场景的 Linux发行版，它特别为资深/重度Linux用户而优化，关注安全，性能和资源效能。Alpine 镜像可以适用于更多常用场景，并且是一个优秀的可以适用于生产的基础系统/环境。

    +

    Alpine 操作系统是一个面向安全的轻型 Linux 发行版。它不同于通常 Linux 发行版，Alpine 采用了 musl libc 和 busybox 以减小系统的体积和运行时资源消耗，但功能上比 busybox 又完善的多，因此得到开源社区越来越多的青睐。在保持瘦身的同时，Alpine 还提供了自己的包管理工具 apk，可以通过 https://pkgs.alpinelinux.org/packages 网站上查询包信息，也可以直接通过 apk 命令直接查询和安装各种软件。
    Alpine 由非商业组织维护的，支持广泛场景的 Linux发行版，它特别为资深/重度Linux用户而优化，关注安全，性能和资源效能。Alpine 镜像可以适用于更多常用场景，并且是一个优秀的可以适用于生产的基础系统/环境。

    Alpine Docker 镜像也继承了 Alpine Linux 发行版的这些优势。相比于其他 Docker 镜像，它的容量非常小，仅仅只有 5 MB 左右（对比 Ubuntu 系列镜像接近 200 MB），且拥有非常友好的包管理机制。官方镜像来自 docker-alpine 项目。

    @@ -314,7 +313,7 @@

    目前 Docker 官方已开始推荐使用 Alpine 替代之前的 Ubuntu 做为基础镜像环境。这样会带来多个好处。包括镜像下载速度加快，镜像安全性提高，主机之间的切换更方便，占用更少磁盘空间等。

    -

    一方面在没有镜像的情况下，拉取 docker 镜像还是比较费力的，第二个就是也能节省硬盘空间，所以目前有大部分的 docker 镜像都将 alpine 作为基础镜像了
    然后再来构建下

    这里还有个点，就是上面的那个镜像我们也是 EXPOSE 80端口，然后外部宿主机会随机映射一个端口，为了偷个懒，我们就直接指定外部端口了
    docker run -d -p 80:80 dynamic_web打开浏览器发现访问不了，咋回事呢
    因为我们没看trafex/alpine-nginx-php7:latest这个镜像说明,它内部的服务是 8080 端口的，所以我们映射的暴露端口应该是 8080，再用docker run -d -p 80:8080 dynamic_web这个启动，

    +

    一方面在没有镜像的情况下，拉取 docker 镜像还是比较费力的，第二个就是也能节省硬盘空间，所以目前有大部分的 docker 镜像都将 alpine 作为基础镜像了
    然后再来构建下

    这里还有个点，就是上面的那个镜像我们也是 EXPOSE 80端口，然后外部宿主机会随机映射一个端口，为了偷个懒，我们就直接指定外部端口了
    docker run -d -p 80:80 dynamic_web打开浏览器发现访问不了，咋回事呢
    因为我们没看trafex/alpine-nginx-php7:latest这个镜像说明,它内部的服务是 8080 端口的，所以我们映射的暴露端口应该是 8080，再用 docker run -d -p 80:8080 dynamic_web这个启动，

    @@ -458,7 +457,7 @@
    -
    1. 1. 运行第一个 Dockerfile
    2. 2. 第二个 Dockerfile
    +
    1. 1. 运行第一个 Dockerfile
    2. 2. 第二个 Dockerfile
    diff --git a/2020/03/29/echo命令的一个小技巧/index.html b/2020/03/29/echo命令的一个小技巧/index.html index afd297377b..4376caed4a 100644 --- a/2020/03/29/echo命令的一个小技巧/index.html +++ b/2020/03/29/echo命令的一个小技巧/index.html @@ -4,7 +4,7 @@ - + @@ -32,18 +32,16 @@ + + - - - - @@ -248,11 +246,11 @@ , - + , - + , @@ -303,7 +301,7 @@
    -

    最近做 docker 系列，会经常进到 docker 内部，如上一篇介绍的，这些镜像一般都有用 ubuntu 或者alpine 这样的 Linux 系统作为底包，如果构建镜像的时候没有替换源的话，因为你懂的原因，在内部想编辑下东西要安装 vim 就会很慢很慢，thousand years later~
    而且如果在容器内部想改源配置的话也要编辑器，就陷入了一个鸡生蛋，跟蛋生鸡的问题中，对于 linux 大神来说应该有一万种方法解决这个问题，对于我这个渣渣来说可能只想到了这个土方法，先 cp backup 一下 sources.list, 再 echo “xxx” > sources.list, 这里就碰到了一个问题，这个 sources.list 一般不止一行，直接 echo 的话就解析不了了，不过 echo 可以支持”\n”转义，就是加-e
    看一下解释和示例

    还有一点也是在这个时候要安装 vim 之类的，得知道是什么镜像底包，如果是用 uname 指令，其实看到的是宿主机的系统，得用cat /etc/issue

    这里稍稍记一下

    +

    最近做 docker 系列，会经常进到 docker 内部，如上一篇介绍的，这些镜像一般都有用 ubuntu 或者alpine 这样的 Linux 系统作为底包，如果构建镜像的时候没有替换源的话，因为你懂的原因，在内部想编辑下东西要安装 vim 就会很慢很慢，thousand years later~
    而且如果在容器内部想改源配置的话也要编辑器，就陷入了一个鸡生蛋，跟蛋生鸡的问题中，对于 linux 大神来说应该有一万种方法解决这个问题，对于我这个渣渣来说可能只想到了这个土方法，先 cp backup 一下 sources.list, 再 echo “xxx” > sources.list, 这里就碰到了一个问题，这个 sources.list 一般不止一行，直接 echo 的话就解析不了了，不过 echo 可以支持”\n”转义，就是加-e
    看一下解释和示例

    还有一点也是在这个时候要安装 vim 之类的，得知道是什么镜像底包，如果是用 uname 指令，其实看到的是宿主机的系统，得用cat /etc/issue

    这里稍稍记一下

    @@ -320,10 +318,10 @@
    聊聊 Linux 下的 top 命令
  • -
    docker比一般多一点的初学者介绍三
    +
    docker比一般多一点的初学者介绍
  • -
    docker比一般多一点的初学者介绍
    +
    docker比一般多一点的初学者介绍三
  • docker比一般多一点的初学者介绍二
    diff --git a/2020/04/05/Comparator使用小记/index.html b/2020/04/05/Comparator使用小记/index.html index 722f355999..cb27551e4c 100644 --- a/2020/04/05/Comparator使用小记/index.html +++ b/2020/04/05/Comparator使用小记/index.html @@ -4,7 +4,7 @@ - + @@ -26,24 +26,23 @@ var CONFIG = {"hostname":"nicksxs.me","root":"/","scheme":"Pisces","version":"7.8.0","exturl":false,"sidebar":{"position":"left","display":"post","padding":18,"offset":12,"onmobile":false},"copycode":{"enable":true,"show_result":false,"style":null},"back2top":{"enable":true,"sidebar":false,"scrollpercent":false},"bookmark":{"enable":false,"color":"#222","save":"auto"},"fancybox":true,"mediumzoom":false,"lazyload":true,"pangu":false,"comments":{"style":"tabs","active":null,"storage":true,"lazyload":false,"nav":null},"algolia":{"hits":{"per_page":10},"labels":{"input_placeholder":"Search for Posts","hits_empty":"We didn't find any results for the search: ${query}","hits_stats":"${hits} results found in ${time} ms"}},"localsearch":{"enable":false,"trigger":"auto","top_n_per_article":1,"unescape":false,"preload":false},"motion":{"enable":true,"async":false,"transition":{"post_block":"fadeIn","post_header":"slideDownIn","post_body":"slideDownIn","coll_header":"slideLeftIn","sidebar":"slideUpIn"}}}; - + - + + - + - - - - - - + + + + @@ -234,9 +233,8 @@ Posted on - - + @@ -294,18 +292,85 @@

    在Java8的stream之前，将对象进行排序的时候，可能需要对象实现Comparable接口，或者自己实现一个Comparator，

    比如这样子

    我的对象是Entity

    -
    1
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    public class Entity {

        private Long id;

        private Long sortValue;

        public Long getId() {
            return id;
        }

        public void setId(Long id) {
            this.id = id;
        }

        public Long getSortValue() {
            return sortValue;
        }

        public void setSortValue(Long sortValue) {
            this.sortValue = sortValue;
        }
    }
    +
    public class Entity {
+
+    private Long id;
+
+    private Long sortValue;
+
+    public Long getId() {
+        return id;
+    }
+
+    public void setId(Long id) {
+        this.id = id;
+    }
+
+    public Long getSortValue() {
+        return sortValue;
+    }
+
+    public void setSortValue(Long sortValue) {
+        this.sortValue = sortValue;
+    }
+}

    Comparator

    -
    1
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    3
    4
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    6
    7
    8
    9
    10
    11
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    13
    14
    public class MyComparator implements Comparator {
        @Override
        public int compare(Object o1, Object o2) {
            Entity e1 = (Entity) o1;
            Entity e2 = (Entity) o2;
            if (e1.getSortValue() < e2.getSortValue()) {
                return -1;
            } else if (e1.getSortValue().equals(e2.getSortValue())) {
                return 0;
            } else {
                return 1;
            }
        }
    }
    +
    public class MyComparator implements Comparator {
+    @Override
+    public int compare(Object o1, Object o2) {
+        Entity e1 = (Entity) o1;
+        Entity e2 = (Entity) o2;
+        if (e1.getSortValue() < e2.getSortValue()) {
+            return -1;
+        } else if (e1.getSortValue().equals(e2.getSortValue())) {
+            return 0;
+        } else {
+            return 1;
+        }
+    }
+}

    比较代码

    -
    1
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    4
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    6
    7
    8
    9
    10
    11
    12
    13
    private static MyComparator myComparator = new MyComparator();

        public static void main(String[] args) {
            List<Entity> list = new ArrayList<Entity>();
            Entity e1 = new Entity();
            e1.setId(1L);
            e1.setSortValue(1L);
            list.add(e1);
            Entity e2 = new Entity();
            e2.setId(2L);
            e2.setSortValue(null);
            list.add(e2);
            Collections.sort(list, myComparator);
    +
    private static MyComparator myComparator = new MyComparator();
+
+    public static void main(String[] args) {
+        List<Entity> list = new ArrayList<Entity>();
+        Entity e1 = new Entity();
+        e1.setId(1L);
+        e1.setSortValue(1L);
+        list.add(e1);
+        Entity e2 = new Entity();
+        e2.setId(2L);
+        e2.setSortValue(null);
+        list.add(e2);
+        Collections.sort(list, myComparator);

    看到这里的e2的排序值是null，在Comparator中如果要正常运行的话，就得判空之类的，这里有两点需要，一个是不想写这个MyComparator，然后也没那么好排除掉list里排序值，那么有什么办法能解决这种问题呢，应该说java的这方面真的是很强大

    -

    +

    看一下nullsFirst的实现

    -
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    final static class NullComparator<T> implements Comparator<T>, Serializable {
            private static final long serialVersionUID = -7569533591570686392L;
            private final boolean nullFirst;
            // if null, non-null Ts are considered equal
            private final Comparator<T> real;

            @SuppressWarnings("unchecked")
            NullComparator(boolean nullFirst, Comparator<? super T> real) {
                this.nullFirst = nullFirst;
                this.real = (Comparator<T>) real;
            }

            @Override
            public int compare(T a, T b) {
                if (a == null) {
                    return (b == null) ? 0 : (nullFirst ? -1 : 1);
                } else if (b == null) {
                    return nullFirst ? 1: -1;
                } else {
                    return (real == null) ? 0 : real.compare(a, b);
                }
            }
    +
    final static class NullComparator<T> implements Comparator<T>, Serializable {
+        private static final long serialVersionUID = -7569533591570686392L;
+        private final boolean nullFirst;
+        // if null, non-null Ts are considered equal
+        private final Comparator<T> real;
+
+        @SuppressWarnings("unchecked")
+        NullComparator(boolean nullFirst, Comparator<? super T> real) {
+            this.nullFirst = nullFirst;
+            this.real = (Comparator<T>) real;
+        }
+
+        @Override
+        public int compare(T a, T b) {
+            if (a == null) {
+                return (b == null) ? 0 : (nullFirst ? -1 : 1);
+            } else if (b == null) {
+                return nullFirst ? 1: -1;
+            } else {
+                return (real == null) ? 0 : real.compare(a, b);
+            }
+        }

    核心代码就是下面这段，其实就是帮我们把前面要做的事情做掉了，是不是挺方便的，小记一下哈

    @@ -318,7 +383,7 @@
    Related Posts
    diff --git a/2020/04/12/redis系列介绍七/index.html b/2020/04/12/redis系列介绍七/index.html index c701b86a2a..668fc9781a 100644 --- a/2020/04/12/redis系列介绍七/index.html +++ b/2020/04/12/redis系列介绍七/index.html @@ -4,7 +4,7 @@ - + @@ -32,16 +32,13 @@ + - + - - + - - - @@ -231,9 +228,8 @@     Posted on - - +     @@ -302,13 +298,415 @@

    这一篇不再是数据结构介绍了，大致的数据结构基本都介绍了，这一篇主要是查漏补缺，或者说讲一些重要且基本的概念，也可能是经常被忽略的，很多讲 redis 的系列文章可能都会忽略，学习 redis 的时候也会，因为觉得源码学习就是讲主要的数据结构和“算法”学习了就好了。
    redis 的主要应用就是拿来作为高性能的缓存，那么缓存一般有些啥需要注意的，首先是访问速度，如果取得跟数据库一样快，那就没什么存在的意义，第二个是缓存的字面意思，我只是为了让数据读取快一些，通常大部分的场景这个是需要更新过期的，这里就把我要讲的第一点引出来了（真累，

    redis过期策略

    redis 是如何过期缓存的，可以猜测下，最无脑的就是每个设置了过期时间的 key 都设个定时器，过期了就删除，这种显然消耗太大，清理地最及时，还有的就是 redis 正在采用的懒汉清理策略和定期清理
    懒汉策略就是在使用的时候去检查缓存是否过期，比如 get 操作时，先判断下这个 key 是否已经过期了，如果过期了就删掉，并且返回空，如果没过期则正常返回
    主要代码是

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    /* This function is called when we are going to perform some operation
     * in a given key, but such key may be already logically expired even if
     * it still exists in the database. The main way this function is called
     * is via lookupKey*() family of functions.
     *
     * The behavior of the function depends on the replication role of the
     * instance, because slave instances do not expire keys, they wait
     * for DELs from the master for consistency matters. However even
     * slaves will try to have a coherent return value for the function,
     * so that read commands executed in the slave side will be able to
     * behave like if the key is expired even if still present (because the
     * master has yet to propagate the DEL).
     *
     * In masters as a side effect of finding a key which is expired, such
     * key will be evicted from the database. Also this may trigger the
     * propagation of a DEL/UNLINK command in AOF / replication stream.
     *
     * The return value of the function is 0 if the key is still valid,
     * otherwise the function returns 1 if the key is expired. */
    int expireIfNeeded(redisDb *db, robj *key) {
        if (!keyIsExpired(db,key)) return 0;

        /* If we are running in the context of a slave, instead of
         * evicting the expired key from the database, we return ASAP:
         * the slave key expiration is controlled by the master that will
         * send us synthesized DEL operations for expired keys.
         *
         * Still we try to return the right information to the caller,
         * that is, 0 if we think the key should be still valid, 1 if
         * we think the key is expired at this time. */
        if (server.masterhost != NULL) return 1;

        /* Delete the key */
        server.stat_expiredkeys++;
        propagateExpire(db,key,server.lazyfree_lazy_expire);
        notifyKeyspaceEvent(NOTIFY_EXPIRED,
            "expired",key,db->id);
        return server.lazyfree_lazy_expire ? dbAsyncDelete(db,key) :
                                             dbSyncDelete(db,key);
    }

    /* Check if the key is expired. */
    int keyIsExpired(redisDb *db, robj *key) {
        mstime_t when = getExpire(db,key);
        mstime_t now;

        if (when < 0) return 0; /* No expire for this key */

        /* Don't expire anything while loading. It will be done later. */
        if (server.loading) return 0;

        /* If we are in the context of a Lua script, we pretend that time is
         * blocked to when the Lua script started. This way a key can expire
         * only the first time it is accessed and not in the middle of the
         * script execution, making propagation to slaves / AOF consistent.
         * See issue #1525 on Github for more information. */
        if (server.lua_caller) {
            now = server.lua_time_start;
        }
        /* If we are in the middle of a command execution, we still want to use
         * a reference time that does not change: in that case we just use the
         * cached time, that we update before each call in the call() function.
         * This way we avoid that commands such as RPOPLPUSH or similar, that
         * may re-open the same key multiple times, can invalidate an already
         * open object in a next call, if the next call will see the key expired,
         * while the first did not. */
        else if (server.fixed_time_expire > 0) {
            now = server.mstime;
        }
        /* For the other cases, we want to use the most fresh time we have. */
        else {
            now = mstime();
        }

        /* The key expired if the current (virtual or real) time is greater
         * than the expire time of the key. */
        return now > when;
    }
    /* Return the expire time of the specified key, or -1 if no expire
     * is associated with this key (i.e. the key is non volatile) */
    long long getExpire(redisDb *db, robj *key) {
        dictEntry *de;

        /* No expire? return ASAP */
        if (dictSize(db->expires) == 0 ||
           (de = dictFind(db->expires,key->ptr)) == NULL) return -1;

        /* The entry was found in the expire dict, this means it should also
         * be present in the main dict (safety check). */
        serverAssertWithInfo(NULL,key,dictFind(db->dict,key->ptr) != NULL);
        return dictGetSignedIntegerVal(de);
    }
    +
    /* This function is called when we are going to perform some operation
+ * in a given key, but such key may be already logically expired even if
+ * it still exists in the database. The main way this function is called
+ * is via lookupKey*() family of functions.
+ *
+ * The behavior of the function depends on the replication role of the
+ * instance, because slave instances do not expire keys, they wait
+ * for DELs from the master for consistency matters. However even
+ * slaves will try to have a coherent return value for the function,
+ * so that read commands executed in the slave side will be able to
+ * behave like if the key is expired even if still present (because the
+ * master has yet to propagate the DEL).
+ *
+ * In masters as a side effect of finding a key which is expired, such
+ * key will be evicted from the database. Also this may trigger the
+ * propagation of a DEL/UNLINK command in AOF / replication stream.
+ *
+ * The return value of the function is 0 if the key is still valid,
+ * otherwise the function returns 1 if the key is expired. */
+int expireIfNeeded(redisDb *db, robj *key) {
+    if (!keyIsExpired(db,key)) return 0;
+
+    /* If we are running in the context of a slave, instead of
+     * evicting the expired key from the database, we return ASAP:
+     * the slave key expiration is controlled by the master that will
+     * send us synthesized DEL operations for expired keys.
+     *
+     * Still we try to return the right information to the caller,
+     * that is, 0 if we think the key should be still valid, 1 if
+     * we think the key is expired at this time. */
+    if (server.masterhost != NULL) return 1;
+
+    /* Delete the key */
+    server.stat_expiredkeys++;
+    propagateExpire(db,key,server.lazyfree_lazy_expire);
+    notifyKeyspaceEvent(NOTIFY_EXPIRED,
+        "expired",key,db->id);
+    return server.lazyfree_lazy_expire ? dbAsyncDelete(db,key) :
+                                         dbSyncDelete(db,key);
+}
+
+/* Check if the key is expired. */
+int keyIsExpired(redisDb *db, robj *key) {
+    mstime_t when = getExpire(db,key);
+    mstime_t now;
+
+    if (when < 0) return 0; /* No expire for this key */
+
+    /* Don't expire anything while loading. It will be done later. */
+    if (server.loading) return 0;
+
+    /* If we are in the context of a Lua script, we pretend that time is
+     * blocked to when the Lua script started. This way a key can expire
+     * only the first time it is accessed and not in the middle of the
+     * script execution, making propagation to slaves / AOF consistent.
+     * See issue #1525 on Github for more information. */
+    if (server.lua_caller) {
+        now = server.lua_time_start;
+    }
+    /* If we are in the middle of a command execution, we still want to use
+     * a reference time that does not change: in that case we just use the
+     * cached time, that we update before each call in the call() function.
+     * This way we avoid that commands such as RPOPLPUSH or similar, that
+     * may re-open the same key multiple times, can invalidate an already
+     * open object in a next call, if the next call will see the key expired,
+     * while the first did not. */
+    else if (server.fixed_time_expire > 0) {
+        now = server.mstime;
+    }
+    /* For the other cases, we want to use the most fresh time we have. */
+    else {
+        now = mstime();
+    }
+
+    /* The key expired if the current (virtual or real) time is greater
+     * than the expire time of the key. */
+    return now > when;
+}
+/* Return the expire time of the specified key, or -1 if no expire
+ * is associated with this key (i.e. the key is non volatile) */
+long long getExpire(redisDb *db, robj *key) {
+    dictEntry *de;
+
+    /* No expire? return ASAP */
+    if (dictSize(db->expires) == 0 ||
+       (de = dictFind(db->expires,key->ptr)) == NULL) return -1;
+
+    /* The entry was found in the expire dict, this means it should also
+     * be present in the main dict (safety check). */
+    serverAssertWithInfo(NULL,key,dictFind(db->dict,key->ptr) != NULL);
+    return dictGetSignedIntegerVal(de);
+}

    这里有几点要注意的，第一是当惰性删除时会根据lazyfree_lazy_expire这个参数去判断是执行同步删除还是异步删除，另外一点是对于 slave，是不需要执行的，因为会在 master 过期时向 slave 发送 del 指令。
    光采用这个策略会有什么问题呢，假如一些key 一直未被访问，那这些 key 就不会过期了，导致一直被占用着内存，所以 redis 采取了懒汉式过期加定期过期策略，定期策略是怎么执行的呢

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    /* This function handles 'background' operations we are required to do
     * incrementally in Redis databases, such as active key expiring, resizing,
     * rehashing. */
    void databasesCron(void) {
        /* Expire keys by random sampling. Not required for slaves
         * as master will synthesize DELs for us. */
        if (server.active_expire_enabled) {
            if (server.masterhost == NULL) {
                activeExpireCycle(ACTIVE_EXPIRE_CYCLE_SLOW);
            } else {
                expireSlaveKeys();
            }
        }

        /* Defrag keys gradually. */
        activeDefragCycle();

        /* Perform hash tables rehashing if needed, but only if there are no
         * other processes saving the DB on disk. Otherwise rehashing is bad
         * as will cause a lot of copy-on-write of memory pages. */
        if (!hasActiveChildProcess()) {
            /* We use global counters so if we stop the computation at a given
             * DB we'll be able to start from the successive in the next
             * cron loop iteration. */
            static unsigned int resize_db = 0;
            static unsigned int rehash_db = 0;
            int dbs_per_call = CRON_DBS_PER_CALL;
            int j;

            /* Don't test more DBs than we have. */
            if (dbs_per_call > server.dbnum) dbs_per_call = server.dbnum;

            /* Resize */
            for (j = 0; j < dbs_per_call; j++) {
                tryResizeHashTables(resize_db % server.dbnum);
                resize_db++;
            }

            /* Rehash */
            if (server.activerehashing) {
                for (j = 0; j < dbs_per_call; j++) {
                    int work_done = incrementallyRehash(rehash_db);
                    if (work_done) {
                        /* If the function did some work, stop here, we'll do
                         * more at the next cron loop. */
                        break;
                    } else {
                        /* If this db didn't need rehash, we'll try the next one. */
                        rehash_db++;
                        rehash_db %= server.dbnum;
                    }
                }
            }
        }
    }
    /* Try to expire a few timed out keys. The algorithm used is adaptive and
     * will use few CPU cycles if there are few expiring keys, otherwise
     * it will get more aggressive to avoid that too much memory is used by
     * keys that can be removed from the keyspace.
     *
     * Every expire cycle tests multiple databases: the next call will start
     * again from the next db, with the exception of exists for time limit: in that
     * case we restart again from the last database we were processing. Anyway
     * no more than CRON_DBS_PER_CALL databases are tested at every iteration.
     *
     * The function can perform more or less work, depending on the "type"
     * argument. It can execute a "fast cycle" or a "slow cycle". The slow
     * cycle is the main way we collect expired cycles: this happens with
     * the "server.hz" frequency (usually 10 hertz).
     *
     * However the slow cycle can exit for timeout, since it used too much time.
     * For this reason the function is also invoked to perform a fast cycle
     * at every event loop cycle, in the beforeSleep() function. The fast cycle
     * will try to perform less work, but will do it much more often.
     *
     * The following are the details of the two expire cycles and their stop
     * conditions:
     *
     * If type is ACTIVE_EXPIRE_CYCLE_FAST the function will try to run a
     * "fast" expire cycle that takes no longer than EXPIRE_FAST_CYCLE_DURATION
     * microseconds, and is not repeated again before the same amount of time.
     * The cycle will also refuse to run at all if the latest slow cycle did not
     * terminate because of a time limit condition.
     *
     * If type is ACTIVE_EXPIRE_CYCLE_SLOW, that normal expire cycle is
     * executed, where the time limit is a percentage of the REDIS_HZ period
     * as specified by the ACTIVE_EXPIRE_CYCLE_SLOW_TIME_PERC define. In the
     * fast cycle, the check of every database is interrupted once the number
     * of already expired keys in the database is estimated to be lower than
     * a given percentage, in order to avoid doing too much work to gain too
     * little memory.
     *
     * The configured expire "effort" will modify the baseline parameters in
     * order to do more work in both the fast and slow expire cycles.
     */

    #define ACTIVE_EXPIRE_CYCLE_KEYS_PER_LOOP 20 /* Keys for each DB loop. */
    #define ACTIVE_EXPIRE_CYCLE_FAST_DURATION 1000 /* Microseconds. */
    #define ACTIVE_EXPIRE_CYCLE_SLOW_TIME_PERC 25 /* Max % of CPU to use. */
    #define ACTIVE_EXPIRE_CYCLE_ACCEPTABLE_STALE 10 /* % of stale keys after which
                                                       we do extra efforts. */
    void activeExpireCycle(int type) {
        /* Adjust the running parameters according to the configured expire
         * effort. The default effort is 1, and the maximum configurable effort
         * is 10. */
        unsigned long
        effort = server.active_expire_effort-1, /* Rescale from 0 to 9. */
        config_keys_per_loop = ACTIVE_EXPIRE_CYCLE_KEYS_PER_LOOP +
                               ACTIVE_EXPIRE_CYCLE_KEYS_PER_LOOP/4*effort,
        config_cycle_fast_duration = ACTIVE_EXPIRE_CYCLE_FAST_DURATION +
                                     ACTIVE_EXPIRE_CYCLE_FAST_DURATION/4*effort,
        config_cycle_slow_time_perc = ACTIVE_EXPIRE_CYCLE_SLOW_TIME_PERC +
                                      2*effort,
        config_cycle_acceptable_stale = ACTIVE_EXPIRE_CYCLE_ACCEPTABLE_STALE-
                                        effort;

        /* This function has some global state in order to continue the work
         * incrementally across calls. */
        static unsigned int current_db = 0; /* Last DB tested. */
        static int timelimit_exit = 0;      /* Time limit hit in previous call? */
        static long long last_fast_cycle = 0; /* When last fast cycle ran. */

        int j, iteration = 0;
        int dbs_per_call = CRON_DBS_PER_CALL;
        long long start = ustime(), timelimit, elapsed;

        /* When clients are paused the dataset should be static not just from the
         * POV of clients not being able to write, but also from the POV of
         * expires and evictions of keys not being performed. */
        if (clientsArePaused()) return;

        if (type == ACTIVE_EXPIRE_CYCLE_FAST) {
            /* Don't start a fast cycle if the previous cycle did not exit
             * for time limit, unless the percentage of estimated stale keys is
             * too high. Also never repeat a fast cycle for the same period
             * as the fast cycle total duration itself. */
            if (!timelimit_exit &&
                server.stat_expired_stale_perc < config_cycle_acceptable_stale)
                return;

            if (start < last_fast_cycle + (long long)config_cycle_fast_duration*2)
                return;

            last_fast_cycle = start;
        }

        /* We usually should test CRON_DBS_PER_CALL per iteration, with
         * two exceptions:
         *
         * 1) Don't test more DBs than we have.
         * 2) If last time we hit the time limit, we want to scan all DBs
         * in this iteration, as there is work to do in some DB and we don't want
         * expired keys to use memory for too much time. */
        if (dbs_per_call > server.dbnum || timelimit_exit)
            dbs_per_call = server.dbnum;

        /* We can use at max 'config_cycle_slow_time_perc' percentage of CPU
         * time per iteration. Since this function gets called with a frequency of
         * server.hz times per second, the following is the max amount of
         * microseconds we can spend in this function. */
        timelimit = config_cycle_slow_time_perc*1000000/server.hz/100;
        timelimit_exit = 0;
        if (timelimit <= 0) timelimit = 1;

        if (type == ACTIVE_EXPIRE_CYCLE_FAST)
            timelimit = config_cycle_fast_duration; /* in microseconds. */

        /* Accumulate some global stats as we expire keys, to have some idea
         * about the number of keys that are already logically expired, but still
         * existing inside the database. */
        long total_sampled = 0;
        long total_expired = 0;

        for (j = 0; j < dbs_per_call && timelimit_exit == 0; j++) {
            /* Expired and checked in a single loop. */
            unsigned long expired, sampled;

            redisDb *db = server.db+(current_db % server.dbnum);

            /* Increment the DB now so we are sure if we run out of time
             * in the current DB we'll restart from the next. This allows to
             * distribute the time evenly across DBs. */
            current_db++;

            /* Continue to expire if at the end of the cycle more than 25%
             * of the keys were expired. */
            do {
                unsigned long num, slots;
                long long now, ttl_sum;
                int ttl_samples;
                iteration++;

                /* If there is nothing to expire try next DB ASAP. */
                if ((num = dictSize(db->expires)) == 0) {
                    db->avg_ttl = 0;
                    break;
                }
                slots = dictSlots(db->expires);
                now = mstime();

                /* When there are less than 1% filled slots, sampling the key
                 * space is expensive, so stop here waiting for better times...
                 * The dictionary will be resized asap. */
                if (num && slots > DICT_HT_INITIAL_SIZE &&
                    (num*100/slots < 1)) break;

                /* The main collection cycle. Sample random keys among keys
                 * with an expire set, checking for expired ones. */
                expired = 0;
                sampled = 0;
                ttl_sum = 0;
                ttl_samples = 0;

                if (num > config_keys_per_loop)
                    num = config_keys_per_loop;

                /* Here we access the low level representation of the hash table
                 * for speed concerns: this makes this code coupled with dict.c,
                 * but it hardly changed in ten years.
                 *
                 * Note that certain places of the hash table may be empty,
                 * so we want also a stop condition about the number of
                 * buckets that we scanned. However scanning for free buckets
                 * is very fast: we are in the cache line scanning a sequential
                 * array of NULL pointers, so we can scan a lot more buckets
                 * than keys in the same time. */
                long max_buckets = num*20;
                long checked_buckets = 0;

                while (sampled < num && checked_buckets < max_buckets) {
                    for (int table = 0; table < 2; table++) {
                        if (table == 1 && !dictIsRehashing(db->expires)) break;

                        unsigned long idx = db->expires_cursor;
                        idx &= db->expires->ht[table].sizemask;
                        dictEntry *de = db->expires->ht[table].table[idx];
                        long long ttl;

                        /* Scan the current bucket of the current table. */
                        checked_buckets++;
                        while(de) {
                            /* Get the next entry now since this entry may get
                             * deleted. */
                            dictEntry *e = de;
                            de = de->next;

                            ttl = dictGetSignedIntegerVal(e)-now;
                            if (activeExpireCycleTryExpire(db,e,now)) expired++;
                            if (ttl > 0) {
                                /* We want the average TTL of keys yet
                                 * not expired. */
                                ttl_sum += ttl;
                                ttl_samples++;
                            }
                            sampled++;
                        }
                    }
                    db->expires_cursor++;
                }
                total_expired += expired;
                total_sampled += sampled;

                /* Update the average TTL stats for this database. */
                if (ttl_samples) {
                    long long avg_ttl = ttl_sum/ttl_samples;

                    /* Do a simple running average with a few samples.
                     * We just use the current estimate with a weight of 2%
                     * and the previous estimate with a weight of 98%. */
                    if (db->avg_ttl == 0) db->avg_ttl = avg_ttl;
                    db->avg_ttl = (db->avg_ttl/50)*49 + (avg_ttl/50);
                }

                /* We can't block forever here even if there are many keys to
                 * expire. So after a given amount of milliseconds return to the
                 * caller waiting for the other active expire cycle. */
                if ((iteration & 0xf) == 0) { /* check once every 16 iterations. */
                    elapsed = ustime()-start;
                    if (elapsed > timelimit) {
                        timelimit_exit = 1;
                        server.stat_expired_time_cap_reached_count++;
                        break;
                    }
                }
                /* We don't repeat the cycle for the current database if there are
                 * an acceptable amount of stale keys (logically expired but yet
                 * not reclained). */
            } while ((expired*100/sampled) > config_cycle_acceptable_stale);
        }

        elapsed = ustime()-start;
        server.stat_expire_cycle_time_used += elapsed;
        latencyAddSampleIfNeeded("expire-cycle",elapsed/1000);

        /* Update our estimate of keys existing but yet to be expired.
         * Running average with this sample accounting for 5%. */
        double current_perc;
        if (total_sampled) {
            current_perc = (double)total_expired/total_sampled;
        } else
            current_perc = 0;
        server.stat_expired_stale_perc = (current_perc*0.05)+
                                         (server.stat_expired_stale_perc*0.95);
    }
    +
    /* This function handles 'background' operations we are required to do
+ * incrementally in Redis databases, such as active key expiring, resizing,
+ * rehashing. */
+void databasesCron(void) {
+    /* Expire keys by random sampling. Not required for slaves
+     * as master will synthesize DELs for us. */
+    if (server.active_expire_enabled) {
+        if (server.masterhost == NULL) {
+            activeExpireCycle(ACTIVE_EXPIRE_CYCLE_SLOW);
+        } else {
+            expireSlaveKeys();
+        }
+    }
+
+    /* Defrag keys gradually. */
+    activeDefragCycle();
+
+    /* Perform hash tables rehashing if needed, but only if there are no
+     * other processes saving the DB on disk. Otherwise rehashing is bad
+     * as will cause a lot of copy-on-write of memory pages. */
+    if (!hasActiveChildProcess()) {
+        /* We use global counters so if we stop the computation at a given
+         * DB we'll be able to start from the successive in the next
+         * cron loop iteration. */
+        static unsigned int resize_db = 0;
+        static unsigned int rehash_db = 0;
+        int dbs_per_call = CRON_DBS_PER_CALL;
+        int j;
+
+        /* Don't test more DBs than we have. */
+        if (dbs_per_call > server.dbnum) dbs_per_call = server.dbnum;
+
+        /* Resize */
+        for (j = 0; j < dbs_per_call; j++) {
+            tryResizeHashTables(resize_db % server.dbnum);
+            resize_db++;
+        }
+
+        /* Rehash */
+        if (server.activerehashing) {
+            for (j = 0; j < dbs_per_call; j++) {
+                int work_done = incrementallyRehash(rehash_db);
+                if (work_done) {
+                    /* If the function did some work, stop here, we'll do
+                     * more at the next cron loop. */
+                    break;
+                } else {
+                    /* If this db didn't need rehash, we'll try the next one. */
+                    rehash_db++;
+                    rehash_db %= server.dbnum;
+                }
+            }
+        }
+    }
+}
+/* Try to expire a few timed out keys. The algorithm used is adaptive and
+ * will use few CPU cycles if there are few expiring keys, otherwise
+ * it will get more aggressive to avoid that too much memory is used by
+ * keys that can be removed from the keyspace.
+ *
+ * Every expire cycle tests multiple databases: the next call will start
+ * again from the next db, with the exception of exists for time limit: in that
+ * case we restart again from the last database we were processing. Anyway
+ * no more than CRON_DBS_PER_CALL databases are tested at every iteration.
+ *
+ * The function can perform more or less work, depending on the "type"
+ * argument. It can execute a "fast cycle" or a "slow cycle". The slow
+ * cycle is the main way we collect expired cycles: this happens with
+ * the "server.hz" frequency (usually 10 hertz).
+ *
+ * However the slow cycle can exit for timeout, since it used too much time.
+ * For this reason the function is also invoked to perform a fast cycle
+ * at every event loop cycle, in the beforeSleep() function. The fast cycle
+ * will try to perform less work, but will do it much more often.
+ *
+ * The following are the details of the two expire cycles and their stop
+ * conditions:
+ *
+ * If type is ACTIVE_EXPIRE_CYCLE_FAST the function will try to run a
+ * "fast" expire cycle that takes no longer than EXPIRE_FAST_CYCLE_DURATION
+ * microseconds, and is not repeated again before the same amount of time.
+ * The cycle will also refuse to run at all if the latest slow cycle did not
+ * terminate because of a time limit condition.
+ *
+ * If type is ACTIVE_EXPIRE_CYCLE_SLOW, that normal expire cycle is
+ * executed, where the time limit is a percentage of the REDIS_HZ period
+ * as specified by the ACTIVE_EXPIRE_CYCLE_SLOW_TIME_PERC define. In the
+ * fast cycle, the check of every database is interrupted once the number
+ * of already expired keys in the database is estimated to be lower than
+ * a given percentage, in order to avoid doing too much work to gain too
+ * little memory.
+ *
+ * The configured expire "effort" will modify the baseline parameters in
+ * order to do more work in both the fast and slow expire cycles.
+ */
+
+#define ACTIVE_EXPIRE_CYCLE_KEYS_PER_LOOP 20 /* Keys for each DB loop. */
+#define ACTIVE_EXPIRE_CYCLE_FAST_DURATION 1000 /* Microseconds. */
+#define ACTIVE_EXPIRE_CYCLE_SLOW_TIME_PERC 25 /* Max % of CPU to use. */
+#define ACTIVE_EXPIRE_CYCLE_ACCEPTABLE_STALE 10 /* % of stale keys after which
+                                                   we do extra efforts. */
+void activeExpireCycle(int type) {
+    /* Adjust the running parameters according to the configured expire
+     * effort. The default effort is 1, and the maximum configurable effort
+     * is 10. */
+    unsigned long
+    effort = server.active_expire_effort-1, /* Rescale from 0 to 9. */
+    config_keys_per_loop = ACTIVE_EXPIRE_CYCLE_KEYS_PER_LOOP +
+                           ACTIVE_EXPIRE_CYCLE_KEYS_PER_LOOP/4*effort,
+    config_cycle_fast_duration = ACTIVE_EXPIRE_CYCLE_FAST_DURATION +
+                                 ACTIVE_EXPIRE_CYCLE_FAST_DURATION/4*effort,
+    config_cycle_slow_time_perc = ACTIVE_EXPIRE_CYCLE_SLOW_TIME_PERC +
+                                  2*effort,
+    config_cycle_acceptable_stale = ACTIVE_EXPIRE_CYCLE_ACCEPTABLE_STALE-
+                                    effort;
+
+    /* This function has some global state in order to continue the work
+     * incrementally across calls. */
+    static unsigned int current_db = 0; /* Last DB tested. */
+    static int timelimit_exit = 0;      /* Time limit hit in previous call? */
+    static long long last_fast_cycle = 0; /* When last fast cycle ran. */
+
+    int j, iteration = 0;
+    int dbs_per_call = CRON_DBS_PER_CALL;
+    long long start = ustime(), timelimit, elapsed;
+
+    /* When clients are paused the dataset should be static not just from the
+     * POV of clients not being able to write, but also from the POV of
+     * expires and evictions of keys not being performed. */
+    if (clientsArePaused()) return;
+
+    if (type == ACTIVE_EXPIRE_CYCLE_FAST) {
+        /* Don't start a fast cycle if the previous cycle did not exit
+         * for time limit, unless the percentage of estimated stale keys is
+         * too high. Also never repeat a fast cycle for the same period
+         * as the fast cycle total duration itself. */
+        if (!timelimit_exit &&
+            server.stat_expired_stale_perc < config_cycle_acceptable_stale)
+            return;
+
+        if (start < last_fast_cycle + (long long)config_cycle_fast_duration*2)
+            return;
+
+        last_fast_cycle = start;
+    }
+
+    /* We usually should test CRON_DBS_PER_CALL per iteration, with
+     * two exceptions:
+     *
+     * 1) Don't test more DBs than we have.
+     * 2) If last time we hit the time limit, we want to scan all DBs
+     * in this iteration, as there is work to do in some DB and we don't want
+     * expired keys to use memory for too much time. */
+    if (dbs_per_call > server.dbnum || timelimit_exit)
+        dbs_per_call = server.dbnum;
+
+    /* We can use at max 'config_cycle_slow_time_perc' percentage of CPU
+     * time per iteration. Since this function gets called with a frequency of
+     * server.hz times per second, the following is the max amount of
+     * microseconds we can spend in this function. */
+    timelimit = config_cycle_slow_time_perc*1000000/server.hz/100;
+    timelimit_exit = 0;
+    if (timelimit <= 0) timelimit = 1;
+
+    if (type == ACTIVE_EXPIRE_CYCLE_FAST)
+        timelimit = config_cycle_fast_duration; /* in microseconds. */
+
+    /* Accumulate some global stats as we expire keys, to have some idea
+     * about the number of keys that are already logically expired, but still
+     * existing inside the database. */
+    long total_sampled = 0;
+    long total_expired = 0;
+
+    for (j = 0; j < dbs_per_call && timelimit_exit == 0; j++) {
+        /* Expired and checked in a single loop. */
+        unsigned long expired, sampled;
+
+        redisDb *db = server.db+(current_db % server.dbnum);
+
+        /* Increment the DB now so we are sure if we run out of time
+         * in the current DB we'll restart from the next. This allows to
+         * distribute the time evenly across DBs. */
+        current_db++;
+
+        /* Continue to expire if at the end of the cycle more than 25%
+         * of the keys were expired. */
+        do {
+            unsigned long num, slots;
+            long long now, ttl_sum;
+            int ttl_samples;
+            iteration++;
+
+            /* If there is nothing to expire try next DB ASAP. */
+            if ((num = dictSize(db->expires)) == 0) {
+                db->avg_ttl = 0;
+                break;
+            }
+            slots = dictSlots(db->expires);
+            now = mstime();
+
+            /* When there are less than 1% filled slots, sampling the key
+             * space is expensive, so stop here waiting for better times...
+             * The dictionary will be resized asap. */
+            if (num && slots > DICT_HT_INITIAL_SIZE &&
+                (num*100/slots < 1)) break;
+
+            /* The main collection cycle. Sample random keys among keys
+             * with an expire set, checking for expired ones. */
+            expired = 0;
+            sampled = 0;
+            ttl_sum = 0;
+            ttl_samples = 0;
+
+            if (num > config_keys_per_loop)
+                num = config_keys_per_loop;
+
+            /* Here we access the low level representation of the hash table
+             * for speed concerns: this makes this code coupled with dict.c,
+             * but it hardly changed in ten years.
+             *
+             * Note that certain places of the hash table may be empty,
+             * so we want also a stop condition about the number of
+             * buckets that we scanned. However scanning for free buckets
+             * is very fast: we are in the cache line scanning a sequential
+             * array of NULL pointers, so we can scan a lot more buckets
+             * than keys in the same time. */
+            long max_buckets = num*20;
+            long checked_buckets = 0;
+
+            while (sampled < num && checked_buckets < max_buckets) {
+                for (int table = 0; table < 2; table++) {
+                    if (table == 1 && !dictIsRehashing(db->expires)) break;
+
+                    unsigned long idx = db->expires_cursor;
+                    idx &= db->expires->ht[table].sizemask;
+                    dictEntry *de = db->expires->ht[table].table[idx];
+                    long long ttl;
+
+                    /* Scan the current bucket of the current table. */
+                    checked_buckets++;
+                    while(de) {
+                        /* Get the next entry now since this entry may get
+                         * deleted. */
+                        dictEntry *e = de;
+                        de = de->next;
+
+                        ttl = dictGetSignedIntegerVal(e)-now;
+                        if (activeExpireCycleTryExpire(db,e,now)) expired++;
+                        if (ttl > 0) {
+                            /* We want the average TTL of keys yet
+                             * not expired. */
+                            ttl_sum += ttl;
+                            ttl_samples++;
+                        }
+                        sampled++;
+                    }
+                }
+                db->expires_cursor++;
+            }
+            total_expired += expired;
+            total_sampled += sampled;
+
+            /* Update the average TTL stats for this database. */
+            if (ttl_samples) {
+                long long avg_ttl = ttl_sum/ttl_samples;
+
+                /* Do a simple running average with a few samples.
+                 * We just use the current estimate with a weight of 2%
+                 * and the previous estimate with a weight of 98%. */
+                if (db->avg_ttl == 0) db->avg_ttl = avg_ttl;
+                db->avg_ttl = (db->avg_ttl/50)*49 + (avg_ttl/50);
+            }
+
+            /* We can't block forever here even if there are many keys to
+             * expire. So after a given amount of milliseconds return to the
+             * caller waiting for the other active expire cycle. */
+            if ((iteration & 0xf) == 0) { /* check once every 16 iterations. */
+                elapsed = ustime()-start;
+                if (elapsed > timelimit) {
+                    timelimit_exit = 1;
+                    server.stat_expired_time_cap_reached_count++;
+                    break;
+                }
+            }
+            /* We don't repeat the cycle for the current database if there are
+             * an acceptable amount of stale keys (logically expired but yet
+             * not reclained). */
+        } while ((expired*100/sampled) > config_cycle_acceptable_stale);
+    }
+
+    elapsed = ustime()-start;
+    server.stat_expire_cycle_time_used += elapsed;
+    latencyAddSampleIfNeeded("expire-cycle",elapsed/1000);
+
+    /* Update our estimate of keys existing but yet to be expired.
+     * Running average with this sample accounting for 5%. */
+    double current_perc;
+    if (total_sampled) {
+        current_perc = (double)total_expired/total_sampled;
+    } else
+        current_perc = 0;
+    server.stat_expired_stale_perc = (current_perc*0.05)+
+                                     (server.stat_expired_stale_perc*0.95);
+}

    执行定期清除分成两种类型，快和慢，分别由beforeSleep和databasesCron调用，快版有两个限制，一个是执行时长由ACTIVE_EXPIRE_CYCLE_FAST_DURATION限制，另一个是执行间隔是 2 倍的ACTIVE_EXPIRE_CYCLE_FAST_DURATION，另外这还可以由配置的server.active_expire_effort参数来控制，默认是 1，最大是 10

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    onfig_cycle_fast_duration = ACTIVE_EXPIRE_CYCLE_FAST_DURATION +
                                     ACTIVE_EXPIRE_CYCLE_FAST_DURATION/4*effort
    +
    onfig_cycle_fast_duration = ACTIVE_EXPIRE_CYCLE_FAST_DURATION +
+                                 ACTIVE_EXPIRE_CYCLE_FAST_DURATION/4*effort

    然后会从一定数量的 db 中找出一定数量的带过期时间的 key（保存在 expires中），这里的数量是由

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    config_keys_per_loop = ACTIVE_EXPIRE_CYCLE_KEYS_PER_LOOP +
                               ACTIVE_EXPIRE_CYCLE_KEYS_PER_LOOP/4*effort
    ```                                 
    控制，慢速的执行时长是
    ```C
    config_cycle_slow_time_perc = ACTIVE_EXPIRE_CYCLE_SLOW_TIME_PERC +
                                      2*effort
    timelimit = config_cycle_slow_time_perc*1000000/server.hz/100;
    +
    config_keys_per_loop = ACTIVE_EXPIRE_CYCLE_KEYS_PER_LOOP +
+                           ACTIVE_EXPIRE_CYCLE_KEYS_PER_LOOP/4*effort
+```                                 
+控制，慢速的执行时长是
+```C
+config_cycle_slow_time_perc = ACTIVE_EXPIRE_CYCLE_SLOW_TIME_PERC +
+                                  2*effort
+timelimit = config_cycle_slow_time_perc*1000000/server.hz/100;

    这里还有一个额外的退出条件，如果当前数据库的抽样结果已经达到我们所允许的过期 key 百分比，则下次不再处理当前 db，继续处理下个 db

    @@ -319,6 +717,9 @@
    Related Posts
    @@ -459,7 +857,7 @@
    -
    1. 1. redis过期策略
    +
    1. 1. redis过期策略
    diff --git a/2020/04/18/redis系列介绍八/index.html b/2020/04/18/redis系列介绍八/index.html index 06d9a02008..b61e890d82 100644 --- a/2020/04/18/redis系列介绍八/index.html +++ b/2020/04/18/redis系列介绍八/index.html @@ -4,7 +4,7 @@ - + @@ -32,20 +32,15 @@ + - + - - + - - - - - @@ -239,13 +234,6 @@     - - - - - Edited on - - @@ -311,35 +299,516 @@
    -

    LRU

    说完了过期策略再说下淘汰策略，redis 使用的策略是近似的 lru 策略，为什么是近似的呢，先来看下什么是 lru，看下 wiki 的介绍
    ，图中一共有四个槽的存储空间，依次访问顺序是 A B C D E D F，
    当第一次访问 D 时刚好占满了坑，并且值是 4，这个值越小代表越先被淘汰，当 E 进来时，看了下已经存在的四个里 A 是最小的，代表是最早存在并且最早被访问的，那就先淘汰它了，E 占领了 A 的位置，并设置值为 4，然后又访问 D 了，D 已经存在了，不过又被访问到了，得更新值为 5，然后是 F 进来了，这时 B 是最老的且最近未被访问，所以就淘汰它了。以上是一个 lru 的简要说明，但是 redis 没有严格按照这个去执行，理由跟前面过期策略一致，最严格的过期策略应该是每个 key 都有对应的定时器，当超时时马上就能清除，但是问题是这样的cpu 消耗太大，所换来的内存效率不太值得，淘汰策略也是这样，类似于上图，要维护所有 key 的一个有序 lru 值，并且遍历将最小的淘汰，redis 采用的是抽样的形式，最初的实现方式是随机从 dict 抽取 5 个 key，淘汰一个 lru 最小的，这样子勉强能达到淘汰的目的，但是效果不是特别好，后面在 redis 3.0开始，将随机抽取改成了维护一个 pool，pool 的大小默认是 16，每次放入的都是按lru 值有序排列好，每一次放入的必须是 lru小于 pool 中最小的 lru 才允许放入，直到放满，后面再有新的就会将大的踢出。
    redis 针对这个策略的改进做了一个实验，这里借用下图

    首先背景是这图中的所有点都对应一个 redis 的 key，灰色部分加入后被顺序访问过一遍，然后又加入了绿色部分，那么按照理论的 lru 算法，应该是图左上中，浅灰色部分全都被淘汰，那么对比来看看图右上，左下和右下，左下表示 2.8 版本就是随机抽样 5 个 key，淘汰其中 lru 最小的一个，发现是灰色和浅灰色的都有被淘汰的，右下的 3.0 版本抽样数量不变的情况下，稍好一些，当 3.0 版本的抽样数量调整成 10 后，已经较为接近理论上的 lru 策略了，通过代码来简要分析下

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    typedef struct redisObject {
        unsigned type:4;
        unsigned encoding:4;
        unsigned lru:LRU_BITS; /* LRU time (relative to global lru_clock) or
                                * LFU data (least significant 8 bits frequency
                                * and most significant 16 bits access time). */
        int refcount;
        void *ptr;
    } robj;
    -

    对于 lru 策略来说，lru 字段记录的就是redisObj 的LRU time，
    redis 在访问数据时，都会调用lookupKey方法

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    /* Low level key lookup API, not actually called directly from commands
     * implementations that should instead rely on lookupKeyRead(),
     * lookupKeyWrite() and lookupKeyReadWithFlags(). */
    robj *lookupKey(redisDb *db, robj *key, int flags) {
        dictEntry *de = dictFind(db->dict,key->ptr);
        if (de) {
            robj *val = dictGetVal(de);

            /* Update the access time for the ageing algorithm.
             * Don't do it if we have a saving child, as this will trigger
             * a copy on write madness. */
            if (!hasActiveChildProcess() && !(flags & LOOKUP_NOTOUCH)){
                if (server.maxmemory_policy & MAXMEMORY_FLAG_LFU) {
                    // 这个是后面一节的内容
                    updateLFU(val);
                } else {
                    //  对于这个分支，访问时就会去更新 lru 值
                    val->lru = LRU_CLOCK();
                }
            }
            return val;
        } else {
            return NULL;
        }
    }
    /* This function is used to obtain the current LRU clock.
     * If the current resolution is lower than the frequency we refresh the
     * LRU clock (as it should be in production servers) we return the
     * precomputed value, otherwise we need to resort to a system call. */
    unsigned int LRU_CLOCK(void) {
        unsigned int lruclock;
        if (1000/server.hz <= LRU_CLOCK_RESOLUTION) {
            // 如果服务器的频率server.hz大于 1 时就是用系统预设的 lruclock
            lruclock = server.lruclock;
        } else {
            lruclock = getLRUClock();
        }
        return lruclock;
    }
    /* Return the LRU clock, based on the clock resolution. This is a time
     * in a reduced-bits format that can be used to set and check the
     * object->lru field of redisObject structures. */
    unsigned int getLRUClock(void) {
        return (mstime()/LRU_CLOCK_RESOLUTION) & LRU_CLOCK_MAX;
    }
    -

    redis 处理命令是在这里processCommand

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    /* If this function gets called we already read a whole
     * command, arguments are in the client argv/argc fields.
     * processCommand() execute the command or prepare the
     * server for a bulk read from the client.
     *
     * If C_OK is returned the client is still alive and valid and
     * other operations can be performed by the caller. Otherwise
     * if C_ERR is returned the client was destroyed (i.e. after QUIT). */
    int processCommand(client *c) {
        moduleCallCommandFilters(c);

        

        /* Handle the maxmemory directive.
         *
         * Note that we do not want to reclaim memory if we are here re-entering
         * the event loop since there is a busy Lua script running in timeout
         * condition, to avoid mixing the propagation of scripts with the
         * propagation of DELs due to eviction. */
        if (server.maxmemory && !server.lua_timedout) {
            int out_of_memory = freeMemoryIfNeededAndSafe() == C_ERR;
            /* freeMemoryIfNeeded may flush slave output buffers. This may result
             * into a slave, that may be the active client, to be freed. */
            if (server.current_client == NULL) return C_ERR;

            /* It was impossible to free enough memory, and the command the client
             * is trying to execute is denied during OOM conditions or the client
             * is in MULTI/EXEC context? Error. */
            if (out_of_memory &&
                (c->cmd->flags & CMD_DENYOOM ||
                 (c->flags & CLIENT_MULTI &&
                  c->cmd->proc != execCommand &&
                  c->cmd->proc != discardCommand)))
            {
                flagTransaction(c);
                addReply(c, shared.oomerr);
                return C_OK;
            }
        }
    }
    -

    这里只摘了部分，当需要清理内存时就会调用, 然后调用了freeMemoryIfNeededAndSafe

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    /* This is a wrapper for freeMemoryIfNeeded() that only really calls the
     * function if right now there are the conditions to do so safely:
     *
     * - There must be no script in timeout condition.
     * - Nor we are loading data right now.
     *
     */
    int freeMemoryIfNeededAndSafe(void) {
        if (server.lua_timedout || server.loading) return C_OK;
        return freeMemoryIfNeeded();
    }
    /* This function is periodically called to see if there is memory to free
     * according to the current "maxmemory" settings. In case we are over the
     * memory limit, the function will try to free some memory to return back
     * under the limit.
     *
     * The function returns C_OK if we are under the memory limit or if we
     * were over the limit, but the attempt to free memory was successful.
     * Otehrwise if we are over the memory limit, but not enough memory
     * was freed to return back under the limit, the function returns C_ERR. */
    int freeMemoryIfNeeded(void) {
        int keys_freed = 0;
        /* By default replicas should ignore maxmemory
         * and just be masters exact copies. */
        if (server.masterhost && server.repl_slave_ignore_maxmemory) return C_OK;

        size_t mem_reported, mem_tofree, mem_freed;
        mstime_t latency, eviction_latency;
        long long delta;
        int slaves = listLength(server.slaves);

        /* When clients are paused the dataset should be static not just from the
         * POV of clients not being able to write, but also from the POV of
         * expires and evictions of keys not being performed. */
        if (clientsArePaused()) return C_OK;
        if (getMaxmemoryState(&mem_reported,NULL,&mem_tofree,NULL) == C_OK)
            return C_OK;

        mem_freed = 0;

        if (server.maxmemory_policy == MAXMEMORY_NO_EVICTION)
            goto cant_free; /* We need to free memory, but policy forbids. */

        latencyStartMonitor(latency);
        while (mem_freed < mem_tofree) {
            int j, k, i;
            static unsigned int next_db = 0;
            sds bestkey = NULL;
            int bestdbid;
            redisDb *db;
            dict *dict;
            dictEntry *de;

            if (server.maxmemory_policy & (MAXMEMORY_FLAG_LRU|MAXMEMORY_FLAG_LFU) ||
                server.maxmemory_policy == MAXMEMORY_VOLATILE_TTL)
            {
                struct evictionPoolEntry *pool = EvictionPoolLRU;

                while(bestkey == NULL) {
                    unsigned long total_keys = 0, keys;

                    /* We don't want to make local-db choices when expiring keys,
                     * so to start populate the eviction pool sampling keys from
                     * every DB. */
                    for (i = 0; i < server.dbnum; i++) {
                        db = server.db+i;
                        dict = (server.maxmemory_policy & MAXMEMORY_FLAG_ALLKEYS) ?
                                db->dict : db->expires;
                        if ((keys = dictSize(dict)) != 0) {
                            evictionPoolPopulate(i, dict, db->dict, pool);
                            total_keys += keys;
                        }
                    }
                    if (!total_keys) break; /* No keys to evict. */

                    /* Go backward from best to worst element to evict. */
                    for (k = EVPOOL_SIZE-1; k >= 0; k--) {
                        if (pool[k].key == NULL) continue;
                        bestdbid = pool[k].dbid;

                        if (server.maxmemory_policy & MAXMEMORY_FLAG_ALLKEYS) {
                            de = dictFind(server.db[pool[k].dbid].dict,
                                pool[k].key);
                        } else {
                            de = dictFind(server.db[pool[k].dbid].expires,
                                pool[k].key);
                        }

                        /* Remove the entry from the pool. */
                        if (pool[k].key != pool[k].cached)
                            sdsfree(pool[k].key);
                        pool[k].key = NULL;
                        pool[k].idle = 0;

                        /* If the key exists, is our pick. Otherwise it is
                         * a ghost and we need to try the next element. */
                        if (de) {
                            bestkey = dictGetKey(de);
                            break;
                        } else {
                            /* Ghost... Iterate again. */
                        }
                    }
                }
            }

            /* volatile-random and allkeys-random policy */
            else if (server.maxmemory_policy == MAXMEMORY_ALLKEYS_RANDOM ||
                     server.maxmemory_policy == MAXMEMORY_VOLATILE_RANDOM)
            {
                /* When evicting a random key, we try to evict a key for
                 * each DB, so we use the static 'next_db' variable to
                 * incrementally visit all DBs. */
                for (i = 0; i < server.dbnum; i++) {
                    j = (++next_db) % server.dbnum;
                    db = server.db+j;
                    dict = (server.maxmemory_policy == MAXMEMORY_ALLKEYS_RANDOM) ?
                            db->dict : db->expires;
                    if (dictSize(dict) != 0) {
                        de = dictGetRandomKey(dict);
                        bestkey = dictGetKey(de);
                        bestdbid = j;
                        break;
                    }
                }
            }

            /* Finally remove the selected key. */
            if (bestkey) {
                db = server.db+bestdbid;
                robj *keyobj = createStringObject(bestkey,sdslen(bestkey));
                propagateExpire(db,keyobj,server.lazyfree_lazy_eviction);
                /* We compute the amount of memory freed by db*Delete() alone.
                 * It is possible that actually the memory needed to propagate
                 * the DEL in AOF and replication link is greater than the one
                 * we are freeing removing the key, but we can't account for
                 * that otherwise we would never exit the loop.
                 *
                 * AOF and Output buffer memory will be freed eventually so
                 * we only care about memory used by the key space. */
                delta = (long long) zmalloc_used_memory();
                latencyStartMonitor(eviction_latency);
                if (server.lazyfree_lazy_eviction)
                    dbAsyncDelete(db,keyobj);
                else
                    dbSyncDelete(db,keyobj);
                latencyEndMonitor(eviction_latency);
                latencyAddSampleIfNeeded("eviction-del",eviction_latency);
                latencyRemoveNestedEvent(latency,eviction_latency);
                delta -= (long long) zmalloc_used_memory();
                mem_freed += delta;
                server.stat_evictedkeys++;
                notifyKeyspaceEvent(NOTIFY_EVICTED, "evicted",
                    keyobj, db->id);
                decrRefCount(keyobj);
                keys_freed++;

                /* When the memory to free starts to be big enough, we may
                 * start spending so much time here that is impossible to
                 * deliver data to the slaves fast enough, so we force the
                 * transmission here inside the loop. */
                if (slaves) flushSlavesOutputBuffers();

                /* Normally our stop condition is the ability to release
                 * a fixed, pre-computed amount of memory. However when we
                 * are deleting objects in another thread, it's better to
                 * check, from time to time, if we already reached our target
                 * memory, since the "mem_freed" amount is computed only
                 * across the dbAsyncDelete() call, while the thread can
                 * release the memory all the time. */
                if (server.lazyfree_lazy_eviction && !(keys_freed % 16)) {
                    if (getMaxmemoryState(NULL,NULL,NULL,NULL) == C_OK) {
                        /* Let's satisfy our stop condition. */
                        mem_freed = mem_tofree;
                    }
                }
            } else {
                latencyEndMonitor(latency);
                latencyAddSampleIfNeeded("eviction-cycle",latency);
                goto cant_free; /* nothing to free... */
            }
        }
        latencyEndMonitor(latency);
        latencyAddSampleIfNeeded("eviction-cycle",latency);
        return C_OK;

    cant_free:
        /* We are here if we are not able to reclaim memory. There is only one
         * last thing we can try: check if the lazyfree thread has jobs in queue
         * and wait... */
        while(bioPendingJobsOfType(BIO_LAZY_FREE)) {
            if (((mem_reported - zmalloc_used_memory()) + mem_freed) >= mem_tofree)
                break;
            usleep(1000);
        }
        return C_ERR;
    }
    -

    这里就是根据具体策略去淘汰 key，首先是要往 pool 更新 key，更新key 的方法是evictionPoolPopulate

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    void evictionPoolPopulate(int dbid, dict *sampledict, dict *keydict, struct evictionPoolEntry *pool) {
        int j, k, count;
        dictEntry *samples[server.maxmemory_samples];

        count = dictGetSomeKeys(sampledict,samples,server.maxmemory_samples);
        for (j = 0; j < count; j++) {
            unsigned long long idle;
            sds key;
            robj *o;
            dictEntry *de;

            de = samples[j];
            key = dictGetKey(de);

            /* If the dictionary we are sampling from is not the main
             * dictionary (but the expires one) we need to lookup the key
             * again in the key dictionary to obtain the value object. */
            if (server.maxmemory_policy != MAXMEMORY_VOLATILE_TTL) {
                if (sampledict != keydict) de = dictFind(keydict, key);
                o = dictGetVal(de);
            }

            /* Calculate the idle time according to the policy. This is called
             * idle just because the code initially handled LRU, but is in fact
             * just a score where an higher score means better candidate. */
            if (server.maxmemory_policy & MAXMEMORY_FLAG_LRU) {
                idle = estimateObjectIdleTime(o);
            } else if (server.maxmemory_policy & MAXMEMORY_FLAG_LFU) {
                /* When we use an LRU policy, we sort the keys by idle time
                 * so that we expire keys starting from greater idle time.
                 * However when the policy is an LFU one, we have a frequency
                 * estimation, and we want to evict keys with lower frequency
                 * first. So inside the pool we put objects using the inverted
                 * frequency subtracting the actual frequency to the maximum
                 * frequency of 255. */
                idle = 255-LFUDecrAndReturn(o);
            } else if (server.maxmemory_policy == MAXMEMORY_VOLATILE_TTL) {
                /* In this case the sooner the expire the better. */
                idle = ULLONG_MAX - (long)dictGetVal(de);
            } else {
                serverPanic("Unknown eviction policy in evictionPoolPopulate()");
            }

            /* Insert the element inside the pool.
             * First, find the first empty bucket or the first populated
             * bucket that has an idle time smaller than our idle time. */
            k = 0;
            while (k < EVPOOL_SIZE &&
                   pool[k].key &&
                   pool[k].idle < idle) k++;
            if (k == 0 && pool[EVPOOL_SIZE-1].key != NULL) {
                /* Can't insert if the element is < the worst element we have
                 * and there are no empty buckets. */
                continue;
            } else if (k < EVPOOL_SIZE && pool[k].key == NULL) {
                /* Inserting into empty position. No setup needed before insert. */
            } else {
                /* Inserting in the middle. Now k points to the first element
                 * greater than the element to insert.  */
                if (pool[EVPOOL_SIZE-1].key == NULL) {
                    /* Free space on the right? Insert at k shifting
                     * all the elements from k to end to the right. */

                    /* Save SDS before overwriting. */
                    sds cached = pool[EVPOOL_SIZE-1].cached;
                    memmove(pool+k+1,pool+k,
                        sizeof(pool[0])*(EVPOOL_SIZE-k-1));
                    pool[k].cached = cached;
                } else {
                    /* No free space on right? Insert at k-1 */
                    k--;
                    /* Shift all elements on the left of k (included) to the
                     * left, so we discard the element with smaller idle time. */
                    sds cached = pool[0].cached; /* Save SDS before overwriting. */
                    if (pool[0].key != pool[0].cached) sdsfree(pool[0].key);
                    memmove(pool,pool+1,sizeof(pool[0])*k);
                    pool[k].cached = cached;
                }
            }

            /* Try to reuse the cached SDS string allocated in the pool entry,
             * because allocating and deallocating this object is costly
             * (according to the profiler, not my fantasy. Remember:
             * premature optimizbla bla bla bla. */
            int klen = sdslen(key);
            if (klen > EVPOOL_CACHED_SDS_SIZE) {
                pool[k].key = sdsdup(key);
            } else {
                memcpy(pool[k].cached,key,klen+1);
                sdssetlen(pool[k].cached,klen);
                pool[k].key = pool[k].cached;
            }
            pool[k].idle = idle;
            pool[k].dbid = dbid;
        }
    }
    +

    LRU

    说完了过期策略再说下淘汰策略，redis 使用的策略是近似的 lru 策略，为什么是近似的呢，先来看下什么是 lru，看下 wiki 的介绍
    ，图中一共有四个槽的存储空间，依次访问顺序是 A B C D E D F，
    当第一次访问 D 时刚好占满了坑，并且值是 4，这个值越小代表越先被淘汰，当 E 进来时，看了下已经存在的四个里 A 是最小的，代表是最早存在并且最早被访问的，那就先淘汰它了，E 占领了 A 的位置，并设置值为 4，然后又访问 D 了，D 已经存在了，不过又被访问到了，得更新值为 5，然后是 F 进来了，这时 B 是最老的且最近未被访问，所以就淘汰它了。以上是一个 lru 的简要说明，但是 redis 没有严格按照这个去执行，理由跟前面过期策略一致，最严格的过期策略应该是每个 key 都有对应的定时器，当超时时马上就能清除，但是问题是这样的cpu 消耗太大，所换来的内存效率不太值得，淘汰策略也是这样，类似于上图，要维护所有 key 的一个有序 lru 值，并且遍历将最小的淘汰，redis 采用的是抽样的形式，最初的实现方式是随机从 dict 抽取 5 个 key，淘汰一个 lru 最小的，这样子勉强能达到淘汰的目的，但是效果不是特别好，后面在 redis 3.0开始，将随机抽取改成了维护一个 pool，pool 的大小默认是 16，每次放入的都是按lru 值有序排列好，每一次放入的必须是 lru小于 pool 中最小的 lru 才允许放入，直到放满，后面再有新的就会将大的踢出。
    redis 针对这个策略的改进做了一个实验，这里借用下图

    首先背景是这图中的所有点都对应一个 redis 的 key，灰色部分加入后被顺序访问过一遍，然后又加入了绿色部分，那么按照理论的 lru 算法，应该是图左上中，浅灰色部分全都被淘汰，那么对比来看看图右上，左下和右下，左下表示 2.8 版本就是随机抽样 5 个 key，淘汰其中 lru 最小的一个，发现是灰色和浅灰色的都有被淘汰的，右下的 3.0 版本抽样数量不变的情况下，稍好一些，当 3.0 版本的抽样数量调整成 10 后，已经较为接近理论上的 lru 策略了，通过代码来简要分析下

    +
    typedef struct redisObject {
+    unsigned type:4;
+    unsigned encoding:4;
+    unsigned lru:LRU_BITS; /* LRU time (relative to global lru_clock) or
+                            * LFU data (least significant 8 bits frequency
+                            * and most significant 16 bits access time). */
+    int refcount;
+    void *ptr;
+} robj;
    +

    对于 lru 策略来说，lru 字段记录的就是redisObj 的LRU time，
    redis 在访问数据时，都会调用lookupKey方法

    +
    /* Low level key lookup API, not actually called directly from commands
+ * implementations that should instead rely on lookupKeyRead(),
+ * lookupKeyWrite() and lookupKeyReadWithFlags(). */
+robj *lookupKey(redisDb *db, robj *key, int flags) {
+    dictEntry *de = dictFind(db->dict,key->ptr);
+    if (de) {
+        robj *val = dictGetVal(de);
+
+        /* Update the access time for the ageing algorithm.
+         * Don't do it if we have a saving child, as this will trigger
+         * a copy on write madness. */
+        if (!hasActiveChildProcess() && !(flags & LOOKUP_NOTOUCH)){
+            if (server.maxmemory_policy & MAXMEMORY_FLAG_LFU) {
+                // 这个是后面一节的内容
+                updateLFU(val);
+            } else {
+                //  对于这个分支，访问时就会去更新 lru 值
+                val->lru = LRU_CLOCK();
+            }
+        }
+        return val;
+    } else {
+        return NULL;
+    }
+}
+/* This function is used to obtain the current LRU clock.
+ * If the current resolution is lower than the frequency we refresh the
+ * LRU clock (as it should be in production servers) we return the
+ * precomputed value, otherwise we need to resort to a system call. */
+unsigned int LRU_CLOCK(void) {
+    unsigned int lruclock;
+    if (1000/server.hz <= LRU_CLOCK_RESOLUTION) {
+        // 如果服务器的频率server.hz大于 1 时就是用系统预设的 lruclock
+        lruclock = server.lruclock;
+    } else {
+        lruclock = getLRUClock();
+    }
+    return lruclock;
+}
+/* Return the LRU clock, based on the clock resolution. This is a time
+ * in a reduced-bits format that can be used to set and check the
+ * object->lru field of redisObject structures. */
+unsigned int getLRUClock(void) {
+    return (mstime()/LRU_CLOCK_RESOLUTION) & LRU_CLOCK_MAX;
+}
    +

    redis 处理命令是在这里processCommand

    +
    /* If this function gets called we already read a whole
+ * command, arguments are in the client argv/argc fields.
+ * processCommand() execute the command or prepare the
+ * server for a bulk read from the client.
+ *
+ * If C_OK is returned the client is still alive and valid and
+ * other operations can be performed by the caller. Otherwise
+ * if C_ERR is returned the client was destroyed (i.e. after QUIT). */
+int processCommand(client *c) {
+    moduleCallCommandFilters(c);
+
+    
+
+    /* Handle the maxmemory directive.
+     *
+     * Note that we do not want to reclaim memory if we are here re-entering
+     * the event loop since there is a busy Lua script running in timeout
+     * condition, to avoid mixing the propagation of scripts with the
+     * propagation of DELs due to eviction. */
+    if (server.maxmemory && !server.lua_timedout) {
+        int out_of_memory = freeMemoryIfNeededAndSafe() == C_ERR;
+        /* freeMemoryIfNeeded may flush slave output buffers. This may result
+         * into a slave, that may be the active client, to be freed. */
+        if (server.current_client == NULL) return C_ERR;
+
+        /* It was impossible to free enough memory, and the command the client
+         * is trying to execute is denied during OOM conditions or the client
+         * is in MULTI/EXEC context? Error. */
+        if (out_of_memory &&
+            (c->cmd->flags & CMD_DENYOOM ||
+             (c->flags & CLIENT_MULTI &&
+              c->cmd->proc != execCommand &&
+              c->cmd->proc != discardCommand)))
+        {
+            flagTransaction(c);
+            addReply(c, shared.oomerr);
+            return C_OK;
+        }
+    }
+}
    +

    这里只摘了部分，当需要清理内存时就会调用, 然后调用了freeMemoryIfNeededAndSafe

    +
    /* This is a wrapper for freeMemoryIfNeeded() that only really calls the
+ * function if right now there are the conditions to do so safely:
+ *
+ * - There must be no script in timeout condition.
+ * - Nor we are loading data right now.
+ *
+ */
+int freeMemoryIfNeededAndSafe(void) {
+    if (server.lua_timedout || server.loading) return C_OK;
+    return freeMemoryIfNeeded();
+}
+/* This function is periodically called to see if there is memory to free
+ * according to the current "maxmemory" settings. In case we are over the
+ * memory limit, the function will try to free some memory to return back
+ * under the limit.
+ *
+ * The function returns C_OK if we are under the memory limit or if we
+ * were over the limit, but the attempt to free memory was successful.
+ * Otehrwise if we are over the memory limit, but not enough memory
+ * was freed to return back under the limit, the function returns C_ERR. */
+int freeMemoryIfNeeded(void) {
+    int keys_freed = 0;
+    /* By default replicas should ignore maxmemory
+     * and just be masters exact copies. */
+    if (server.masterhost && server.repl_slave_ignore_maxmemory) return C_OK;
+
+    size_t mem_reported, mem_tofree, mem_freed;
+    mstime_t latency, eviction_latency;
+    long long delta;
+    int slaves = listLength(server.slaves);
+
+    /* When clients are paused the dataset should be static not just from the
+     * POV of clients not being able to write, but also from the POV of
+     * expires and evictions of keys not being performed. */
+    if (clientsArePaused()) return C_OK;
+    if (getMaxmemoryState(&mem_reported,NULL,&mem_tofree,NULL) == C_OK)
+        return C_OK;
+
+    mem_freed = 0;
+
+    if (server.maxmemory_policy == MAXMEMORY_NO_EVICTION)
+        goto cant_free; /* We need to free memory, but policy forbids. */
+
+    latencyStartMonitor(latency);
+    while (mem_freed < mem_tofree) {
+        int j, k, i;
+        static unsigned int next_db = 0;
+        sds bestkey = NULL;
+        int bestdbid;
+        redisDb *db;
+        dict *dict;
+        dictEntry *de;
+
+        if (server.maxmemory_policy & (MAXMEMORY_FLAG_LRU|MAXMEMORY_FLAG_LFU) ||
+            server.maxmemory_policy == MAXMEMORY_VOLATILE_TTL)
+        {
+            struct evictionPoolEntry *pool = EvictionPoolLRU;
+
+            while(bestkey == NULL) {
+                unsigned long total_keys = 0, keys;
+
+                /* We don't want to make local-db choices when expiring keys,
+                 * so to start populate the eviction pool sampling keys from
+                 * every DB. */
+                for (i = 0; i < server.dbnum; i++) {
+                    db = server.db+i;
+                    dict = (server.maxmemory_policy & MAXMEMORY_FLAG_ALLKEYS) ?
+                            db->dict : db->expires;
+                    if ((keys = dictSize(dict)) != 0) {
+                        evictionPoolPopulate(i, dict, db->dict, pool);
+                        total_keys += keys;
+                    }
+                }
+                if (!total_keys) break; /* No keys to evict. */
+
+                /* Go backward from best to worst element to evict. */
+                for (k = EVPOOL_SIZE-1; k >= 0; k--) {
+                    if (pool[k].key == NULL) continue;
+                    bestdbid = pool[k].dbid;
+
+                    if (server.maxmemory_policy & MAXMEMORY_FLAG_ALLKEYS) {
+                        de = dictFind(server.db[pool[k].dbid].dict,
+                            pool[k].key);
+                    } else {
+                        de = dictFind(server.db[pool[k].dbid].expires,
+                            pool[k].key);
+                    }
+
+                    /* Remove the entry from the pool. */
+                    if (pool[k].key != pool[k].cached)
+                        sdsfree(pool[k].key);
+                    pool[k].key = NULL;
+                    pool[k].idle = 0;
+
+                    /* If the key exists, is our pick. Otherwise it is
+                     * a ghost and we need to try the next element. */
+                    if (de) {
+                        bestkey = dictGetKey(de);
+                        break;
+                    } else {
+                        /* Ghost... Iterate again. */
+                    }
+                }
+            }
+        }
+
+        /* volatile-random and allkeys-random policy */
+        else if (server.maxmemory_policy == MAXMEMORY_ALLKEYS_RANDOM ||
+                 server.maxmemory_policy == MAXMEMORY_VOLATILE_RANDOM)
+        {
+            /* When evicting a random key, we try to evict a key for
+             * each DB, so we use the static 'next_db' variable to
+             * incrementally visit all DBs. */
+            for (i = 0; i < server.dbnum; i++) {
+                j = (++next_db) % server.dbnum;
+                db = server.db+j;
+                dict = (server.maxmemory_policy == MAXMEMORY_ALLKEYS_RANDOM) ?
+                        db->dict : db->expires;
+                if (dictSize(dict) != 0) {
+                    de = dictGetRandomKey(dict);
+                    bestkey = dictGetKey(de);
+                    bestdbid = j;
+                    break;
+                }
+            }
+        }
+
+        /* Finally remove the selected key. */
+        if (bestkey) {
+            db = server.db+bestdbid;
+            robj *keyobj = createStringObject(bestkey,sdslen(bestkey));
+            propagateExpire(db,keyobj,server.lazyfree_lazy_eviction);
+            /* We compute the amount of memory freed by db*Delete() alone.
+             * It is possible that actually the memory needed to propagate
+             * the DEL in AOF and replication link is greater than the one
+             * we are freeing removing the key, but we can't account for
+             * that otherwise we would never exit the loop.
+             *
+             * AOF and Output buffer memory will be freed eventually so
+             * we only care about memory used by the key space. */
+            delta = (long long) zmalloc_used_memory();
+            latencyStartMonitor(eviction_latency);
+            if (server.lazyfree_lazy_eviction)
+                dbAsyncDelete(db,keyobj);
+            else
+                dbSyncDelete(db,keyobj);
+            latencyEndMonitor(eviction_latency);
+            latencyAddSampleIfNeeded("eviction-del",eviction_latency);
+            latencyRemoveNestedEvent(latency,eviction_latency);
+            delta -= (long long) zmalloc_used_memory();
+            mem_freed += delta;
+            server.stat_evictedkeys++;
+            notifyKeyspaceEvent(NOTIFY_EVICTED, "evicted",
+                keyobj, db->id);
+            decrRefCount(keyobj);
+            keys_freed++;
+
+            /* When the memory to free starts to be big enough, we may
+             * start spending so much time here that is impossible to
+             * deliver data to the slaves fast enough, so we force the
+             * transmission here inside the loop. */
+            if (slaves) flushSlavesOutputBuffers();
+
+            /* Normally our stop condition is the ability to release
+             * a fixed, pre-computed amount of memory. However when we
+             * are deleting objects in another thread, it's better to
+             * check, from time to time, if we already reached our target
+             * memory, since the "mem_freed" amount is computed only
+             * across the dbAsyncDelete() call, while the thread can
+             * release the memory all the time. */
+            if (server.lazyfree_lazy_eviction && !(keys_freed % 16)) {
+                if (getMaxmemoryState(NULL,NULL,NULL,NULL) == C_OK) {
+                    /* Let's satisfy our stop condition. */
+                    mem_freed = mem_tofree;
+                }
+            }
+        } else {
+            latencyEndMonitor(latency);
+            latencyAddSampleIfNeeded("eviction-cycle",latency);
+            goto cant_free; /* nothing to free... */
+        }
+    }
+    latencyEndMonitor(latency);
+    latencyAddSampleIfNeeded("eviction-cycle",latency);
+    return C_OK;
+
+cant_free:
+    /* We are here if we are not able to reclaim memory. There is only one
+     * last thing we can try: check if the lazyfree thread has jobs in queue
+     * and wait... */
+    while(bioPendingJobsOfType(BIO_LAZY_FREE)) {
+        if (((mem_reported - zmalloc_used_memory()) + mem_freed) >= mem_tofree)
+            break;
+        usleep(1000);
+    }
+    return C_ERR;
+}
    +

    这里就是根据具体策略去淘汰 key，首先是要往 pool 更新 key，更新key 的方法是evictionPoolPopulate

    +
    void evictionPoolPopulate(int dbid, dict *sampledict, dict *keydict, struct evictionPoolEntry *pool) {
+    int j, k, count;
+    dictEntry *samples[server.maxmemory_samples];
+
+    count = dictGetSomeKeys(sampledict,samples,server.maxmemory_samples);
+    for (j = 0; j < count; j++) {
+        unsigned long long idle;
+        sds key;
+        robj *o;
+        dictEntry *de;
+
+        de = samples[j];
+        key = dictGetKey(de);
+
+        /* If the dictionary we are sampling from is not the main
+         * dictionary (but the expires one) we need to lookup the key
+         * again in the key dictionary to obtain the value object. */
+        if (server.maxmemory_policy != MAXMEMORY_VOLATILE_TTL) {
+            if (sampledict != keydict) de = dictFind(keydict, key);
+            o = dictGetVal(de);
+        }
+
+        /* Calculate the idle time according to the policy. This is called
+         * idle just because the code initially handled LRU, but is in fact
+         * just a score where an higher score means better candidate. */
+        if (server.maxmemory_policy & MAXMEMORY_FLAG_LRU) {
+            idle = estimateObjectIdleTime(o);
+        } else if (server.maxmemory_policy & MAXMEMORY_FLAG_LFU) {
+            /* When we use an LRU policy, we sort the keys by idle time
+             * so that we expire keys starting from greater idle time.
+             * However when the policy is an LFU one, we have a frequency
+             * estimation, and we want to evict keys with lower frequency
+             * first. So inside the pool we put objects using the inverted
+             * frequency subtracting the actual frequency to the maximum
+             * frequency of 255. */
+            idle = 255-LFUDecrAndReturn(o);
+        } else if (server.maxmemory_policy == MAXMEMORY_VOLATILE_TTL) {
+            /* In this case the sooner the expire the better. */
+            idle = ULLONG_MAX - (long)dictGetVal(de);
+        } else {
+            serverPanic("Unknown eviction policy in evictionPoolPopulate()");
+        }
+
+        /* Insert the element inside the pool.
+         * First, find the first empty bucket or the first populated
+         * bucket that has an idle time smaller than our idle time. */
+        k = 0;
+        while (k < EVPOOL_SIZE &&
+               pool[k].key &&
+               pool[k].idle < idle) k++;
+        if (k == 0 && pool[EVPOOL_SIZE-1].key != NULL) {
+            /* Can't insert if the element is < the worst element we have
+             * and there are no empty buckets. */
+            continue;
+        } else if (k < EVPOOL_SIZE && pool[k].key == NULL) {
+            /* Inserting into empty position. No setup needed before insert. */
+        } else {
+            /* Inserting in the middle. Now k points to the first element
+             * greater than the element to insert.  */
+            if (pool[EVPOOL_SIZE-1].key == NULL) {
+                /* Free space on the right? Insert at k shifting
+                 * all the elements from k to end to the right. */
+
+                /* Save SDS before overwriting. */
+                sds cached = pool[EVPOOL_SIZE-1].cached;
+                memmove(pool+k+1,pool+k,
+                    sizeof(pool[0])*(EVPOOL_SIZE-k-1));
+                pool[k].cached = cached;
+            } else {
+                /* No free space on right? Insert at k-1 */
+                k--;
+                /* Shift all elements on the left of k (included) to the
+                 * left, so we discard the element with smaller idle time. */
+                sds cached = pool[0].cached; /* Save SDS before overwriting. */
+                if (pool[0].key != pool[0].cached) sdsfree(pool[0].key);
+                memmove(pool,pool+1,sizeof(pool[0])*k);
+                pool[k].cached = cached;
+            }
+        }
+
+        /* Try to reuse the cached SDS string allocated in the pool entry,
+         * because allocating and deallocating this object is costly
+         * (according to the profiler, not my fantasy. Remember:
+         * premature optimizbla bla bla bla. */
+        int klen = sdslen(key);
+        if (klen > EVPOOL_CACHED_SDS_SIZE) {
+            pool[k].key = sdsdup(key);
+        } else {
+            memcpy(pool[k].cached,key,klen+1);
+            sdssetlen(pool[k].cached,klen);
+            pool[k].key = pool[k].cached;
+        }
+        pool[k].idle = idle;
+        pool[k].dbid = dbid;
+    }
+}

    Redis随机选择maxmemory_samples数量的key，然后计算这些key的空闲时间idle time，当满足条件时(比pool中的某些键的空闲时间还大)就可以进pool。pool更新之后，就淘汰pool中空闲时间最大的键。

    -

    estimateObjectIdleTime用来计算Redis对象的空闲时间：

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    /* Given an object returns the min number of milliseconds the object was never
     * requested, using an approximated LRU algorithm. */
    unsigned long long estimateObjectIdleTime(robj *o) {
        unsigned long long lruclock = LRU_CLOCK();
        if (lruclock >= o->lru) {
            return (lruclock - o->lru) * LRU_CLOCK_RESOLUTION;
        } else {
            return (lruclock + (LRU_CLOCK_MAX - o->lru)) *
                        LRU_CLOCK_RESOLUTION;
        }
    }
    +

    estimateObjectIdleTime用来计算Redis对象的空闲时间：

    +
    /* Given an object returns the min number of milliseconds the object was never
+ * requested, using an approximated LRU algorithm. */
+unsigned long long estimateObjectIdleTime(robj *o) {
+    unsigned long long lruclock = LRU_CLOCK();
+    if (lruclock >= o->lru) {
+        return (lruclock - o->lru) * LRU_CLOCK_RESOLUTION;
+    } else {
+        return (lruclock + (LRU_CLOCK_MAX - o->lru)) *
+                    LRU_CLOCK_RESOLUTION;
+    }
+}

    空闲时间第一种是 lurclock 大于对象的 lru，那么就是减一下乘以精度，因为 lruclock 有可能是已经预生成的，所以会可能走下面这个

    LFU

    上面介绍了LRU 的算法，但是考虑一种场景

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    ~~~~~A~~~~~A~~~~~A~~~~A~~~~~A~~~~~A~~|
    ~~B~~B~~B~~B~~B~~B~~B~~B~~B~~B~~B~~B~|
    ~~~~~~~~~~C~~~~~~~~~C~~~~~~~~~C~~~~~~|
    ~~~~~D~~~~~~~~~~D~~~~~~~~~D~~~~~~~~~D|
    +
    ~~~~~A~~~~~A~~~~~A~~~~A~~~~~A~~~~~A~~|
+~~B~~B~~B~~B~~B~~B~~B~~B~~B~~B~~B~~B~|
+~~~~~~~~~~C~~~~~~~~~C~~~~~~~~~C~~~~~~|
+~~~~~D~~~~~~~~~~D~~~~~~~~~D~~~~~~~~~D|

    可以发现，当采用 lru 的淘汰策略的时候，D 是最新的，会被认为是最值得保留的，但是事实上还不如 A 跟 B，然后 antirez 大神就想到了LFU (Least Frequently Used) 这个算法, 显然对于上面的四个 key 的访问频率，保留优先级应该是 B > A > C = D
    那要怎么来实现这个 LFU 算法呢，其实像LRU，理想的情况就是维护个链表，把最新访问的放到头上去，但是这个会影响访问速度，注意到前面代码的应该可以看到，redisObject 的 lru 字段其实是两用的，当策略是 LFU 时，这个字段就另作他用了，它的 24 位长度被分成两部分

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          16 bits      8 bits
    +----------------+--------+
    + Last decr time | LOG_C  |
    +----------------+--------+
    +
          16 bits      8 bits
++----------------+--------+
++ Last decr time | LOG_C  |
++----------------+--------+

    前16位字段是最后一次递减时间，因此Redis知道 上一次计数器递减，后8位是 计数器 counter。
    LFU 的主体策略就是当这个 key 被访问的次数越多频率越高他就越容易被保留下来，并且是最近被访问的频率越高。这其实有两个事情要做，一个是在访问的时候增加计数值，在一定长时间不访问时进行衰减，所以这里用了两个值，前 16 位记录上一次衰减的时间，后 8 位记录具体的计数值。
    Redis4.0之后为maxmemory_policy淘汰策略添加了两个LFU模式：

    volatile-lfu：对有过期时间的key采用LFU淘汰策略
    allkeys-lfu：对全部key采用LFU淘汰策略
    还有2个配置可以调整LFU算法：

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    lfu-log-factor 10
    lfu-decay-time 1
    ```  
    `lfu-log-factor` 可以调整计数器counter的增长速度，lfu-log-factor越大，counter增长的越慢。

    `lfu-decay-time`是一个以分钟为单位的数值，可以调整counter的减少速度
    这里有个问题是 8 位大小够计么，访问一次加 1 的话的确不够，不过大神就是大神，才不会这么简单的加一。往下看代码
    ```C
    /* Low level key lookup API, not actually called directly from commands
     * implementations that should instead rely on lookupKeyRead(),
     * lookupKeyWrite() and lookupKeyReadWithFlags(). */
    robj *lookupKey(redisDb *db, robj *key, int flags) {
        dictEntry *de = dictFind(db->dict,key->ptr);
        if (de) {
            robj *val = dictGetVal(de);

            /* Update the access time for the ageing algorithm.
             * Don't do it if we have a saving child, as this will trigger
             * a copy on write madness. */
            if (!hasActiveChildProcess() && !(flags & LOOKUP_NOTOUCH)){
                if (server.maxmemory_policy & MAXMEMORY_FLAG_LFU) {
                    // 当淘汰策略是 LFU 时，就会调用这个updateLFU
                    updateLFU(val);
                } else {
                    val->lru = LRU_CLOCK();
                }
            }
            return val;
        } else {
            return NULL;
        }
    }
    -

    updateLFU 这个其实个入口，调用了两个重要的方法

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    /* Update LFU when an object is accessed.
     * Firstly, decrement the counter if the decrement time is reached.
     * Then logarithmically increment the counter, and update the access time. */
    void updateLFU(robj *val) {
        unsigned long counter = LFUDecrAndReturn(val);
        counter = LFULogIncr(counter);
        val->lru = (LFUGetTimeInMinutes()<<8) | counter;
    }
    -

    首先来看看LFUDecrAndReturn，这个方法的作用是根据上一次衰减时间和系统配置的 lfu-decay-time 参数来确定需要将 counter 减去多少

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    /* If the object decrement time is reached decrement the LFU counter but
     * do not update LFU fields of the object, we update the access time
     * and counter in an explicit way when the object is really accessed.
     * And we will times halve the counter according to the times of
     * elapsed time than server.lfu_decay_time.
     * Return the object frequency counter.
     *
     * This function is used in order to scan the dataset for the best object
     * to fit: as we check for the candidate, we incrementally decrement the
     * counter of the scanned objects if needed. */
    unsigned long LFUDecrAndReturn(robj *o) {
        // 右移 8 位，拿到上次衰减时间
        unsigned long ldt = o->lru >> 8;
        // 对 255 做与操作，拿到 counter 值
        unsigned long counter = o->lru & 255;
        // 根据lfu_decay_time来算出过了多少个衰减周期
        unsigned long num_periods = server.lfu_decay_time ? LFUTimeElapsed(ldt) / server.lfu_decay_time : 0;
        if (num_periods)
            counter = (num_periods > counter) ? 0 : counter - num_periods;
        return counter;
    }
    -

    然后是加，调用了LFULogIncr

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    /* Logarithmically increment a counter. The greater is the current counter value
     * the less likely is that it gets really implemented. Saturate it at 255. */
    uint8_t LFULogIncr(uint8_t counter) {
        // 最大值就是 255，到顶了就不加了
        if (counter == 255) return 255;
        // 生成个随机小数
        double r = (double)rand()/RAND_MAX;
        // 减去个基础值，LFU_INIT_VAL = 5，防止刚进来就被逐出
        double baseval = counter - LFU_INIT_VAL;
        // 如果是小于 0，
        if (baseval < 0) baseval = 0;
        // 如果 baseval 是 0，那么 p 就是 1了，后面 counter 直接加一，如果不是的话，得看系统参数lfu_log_factor，这个越大，除出来的 p 越小，那么 counter++的可能性也越小，这样子就把前面的疑问给解决了，不是直接+1 的
        double p = 1.0/(baseval*server.lfu_log_factor+1);
        if (r < p) counter++;
        return counter;
    }
    +
    lfu-log-factor 10
+lfu-decay-time 1
+```  
+`lfu-log-factor` 可以调整计数器counter的增长速度，lfu-log-factor越大，counter增长的越慢。
+
+`lfu-decay-time`是一个以分钟为单位的数值，可以调整counter的减少速度
+这里有个问题是 8 位大小够计么，访问一次加 1 的话的确不够，不过大神就是大神，才不会这么简单的加一。往下看代码
+```C
+/* Low level key lookup API, not actually called directly from commands
+ * implementations that should instead rely on lookupKeyRead(),
+ * lookupKeyWrite() and lookupKeyReadWithFlags(). */
+robj *lookupKey(redisDb *db, robj *key, int flags) {
+    dictEntry *de = dictFind(db->dict,key->ptr);
+    if (de) {
+        robj *val = dictGetVal(de);
+
+        /* Update the access time for the ageing algorithm.
+         * Don't do it if we have a saving child, as this will trigger
+         * a copy on write madness. */
+        if (!hasActiveChildProcess() && !(flags & LOOKUP_NOTOUCH)){
+            if (server.maxmemory_policy & MAXMEMORY_FLAG_LFU) {
+                // 当淘汰策略是 LFU 时，就会调用这个updateLFU
+                updateLFU(val);
+            } else {
+                val->lru = LRU_CLOCK();
+            }
+        }
+        return val;
+    } else {
+        return NULL;
+    }
+}
    +

    updateLFU 这个其实个入口，调用了两个重要的方法

    +
    /* Update LFU when an object is accessed.
+ * Firstly, decrement the counter if the decrement time is reached.
+ * Then logarithmically increment the counter, and update the access time. */
+void updateLFU(robj *val) {
+    unsigned long counter = LFUDecrAndReturn(val);
+    counter = LFULogIncr(counter);
+    val->lru = (LFUGetTimeInMinutes()<<8) | counter;
+}
    +

    首先来看看LFUDecrAndReturn，这个方法的作用是根据上一次衰减时间和系统配置的 lfu-decay-time 参数来确定需要将 counter 减去多少

    +
    /* If the object decrement time is reached decrement the LFU counter but
+ * do not update LFU fields of the object, we update the access time
+ * and counter in an explicit way when the object is really accessed.
+ * And we will times halve the counter according to the times of
+ * elapsed time than server.lfu_decay_time.
+ * Return the object frequency counter.
+ *
+ * This function is used in order to scan the dataset for the best object
+ * to fit: as we check for the candidate, we incrementally decrement the
+ * counter of the scanned objects if needed. */
+unsigned long LFUDecrAndReturn(robj *o) {
+    // 右移 8 位，拿到上次衰减时间
+    unsigned long ldt = o->lru >> 8;
+    // 对 255 做与操作，拿到 counter 值
+    unsigned long counter = o->lru & 255;
+    // 根据lfu_decay_time来算出过了多少个衰减周期
+    unsigned long num_periods = server.lfu_decay_time ? LFUTimeElapsed(ldt) / server.lfu_decay_time : 0;
+    if (num_periods)
+        counter = (num_periods > counter) ? 0 : counter - num_periods;
+    return counter;
+}
    +

    然后是加，调用了LFULogIncr

    +
    /* Logarithmically increment a counter. The greater is the current counter value
+ * the less likely is that it gets really implemented. Saturate it at 255. */
+uint8_t LFULogIncr(uint8_t counter) {
+    // 最大值就是 255，到顶了就不加了
+    if (counter == 255) return 255;
+    // 生成个随机小数
+    double r = (double)rand()/RAND_MAX;
+    // 减去个基础值，LFU_INIT_VAL = 5，防止刚进来就被逐出
+    double baseval = counter - LFU_INIT_VAL;
+    // 如果是小于 0，
+    if (baseval < 0) baseval = 0;
+    // 如果 baseval 是 0，那么 p 就是 1了，后面 counter 直接加一，如果不是的话，得看系统参数lfu_log_factor，这个越大，除出来的 p 越小，那么 counter++的可能性也越小，这样子就把前面的疑问给解决了，不是直接+1 的
+    double p = 1.0/(baseval*server.lfu_log_factor+1);
+    if (r < p) counter++;
+    return counter;
+}

    大概的变化速度可以参考

    -
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    +--------+------------+------------+------------+------------+------------+
    | factor | 100 hits   | 1000 hits  | 100K hits  | 1M hits    | 10M hits   |
    +--------+------------+------------+------------+------------+------------+
    | 0      | 104        | 255        | 255        | 255        | 255        |
    +--------+------------+------------+------------+------------+------------+
    | 1      | 18         | 49         | 255        | 255        | 255        |
    +--------+------------+------------+------------+------------+------------+
    | 10     | 10         | 18         | 142        | 255        | 255        |
    +--------+------------+------------+------------+------------+------------+
    | 100    | 8          | 11         | 49         | 143        | 255        |
    +--------+------------+------------+------------+------------+------------+
    +
    +--------+------------+------------+------------+------------+------------+
+| factor | 100 hits   | 1000 hits  | 100K hits  | 1M hits    | 10M hits   |
++--------+------------+------------+------------+------------+------------+
+| 0      | 104        | 255        | 255        | 255        | 255        |
++--------+------------+------------+------------+------------+------------+
+| 1      | 18         | 49         | 255        | 255        | 255        |
++--------+------------+------------+------------+------------+------------+
+| 10     | 10         | 18         | 142        | 255        | 255        |
++--------+------------+------------+------------+------------+------------+
+| 100    | 8          | 11         | 49         | 143        | 255        |
++--------+------------+------------+------------+------------+------------+

    简而言之就是 lfu_log_factor 越大变化的越慢

    总结

    总结一下，redis 实现了近似的 lru 淘汰策略，通过增加了淘汰 key 的池子(pool)，并且增大每次抽样的 key 的数量来将淘汰效果更进一步地接近于 lru，这是 lru 策略，但是对于前面举的一个例子，其实 lru 并不能保证 key 的淘汰就如我们预期，所以在后期又引入了 lfu 的策略，lfu的策略比较巧妙，复用了 redis 对象的 lru 字段，并且使用了factor 参数来控制计数器递增的速度，防止 8 位的计数器太早溢出。

    @@ -351,6 +820,9 @@
    Related Posts
    @@ -491,7 +960,7 @@
    -
    1. 1. LRU
    2. 2. LFU
    3. 3. 总结
    +
    1. 1. LRU
    2. 2. LFU
    3. 3. 总结
    diff --git a/2020/04/26/聊聊-mysql-的-MVCC/index.html b/2020/04/26/聊聊-mysql-的-MVCC/index.html index 60200f01fc..f686db7f61 100644 --- a/2020/04/26/聊聊-mysql-的-MVCC/index.html +++ b/2020/04/26/聊聊-mysql-的-MVCC/index.html @@ -4,7 +4,7 @@ - + @@ -32,16 +32,14 @@ + - + - - + - - - + @@ -235,13 +233,6 @@ - - - - - Edited on - - @@ -307,10 +298,26 @@
    -

    很久以前，有位面试官问到，你知道 mysql 的事务隔离级别吗，“额 O__O …，不太清楚”，完了之后我就去网上找相关的文章，找到了这篇MySQL 四种事务隔离级的说明, 文章写得特别好，看了这个就懂了各个事务隔离级别都是啥，不过看了这个之后多思考一下的话还是会发现问题，这么神奇的事务隔离级别是怎么实现的呢

    -

    其中 innodb 的事务隔离用到了标题里说到的 mvcc，Multiversion concurrency control, 直译过来就是多版本并发控制，先不讲这个究竟是个啥，考虑下如果纯猜测，这个事务隔离级别应该会是怎么样实现呢，愚钝的我想了下，可以在事务开始的时候拷贝一个表，这个可以支持 RR 级别，RC 级别就不支持了，而且要是个非常大的表，想想就不可行

    -

    腆着脸说虽然这个不可行，但是思路是对的，具体实行起来需要做一系列（肥肠多）的改动，首先根据我的理解，其实这个拷贝一个表是变成拷贝一条记录，但是如果有多个事务，那就得拷贝多次，这个问题其实可以借助版本管理系统来解释，在用版本管理系统，git 之类的之前，很原始的可能是开发完一个功能后，就打个压缩包用时间等信息命名，然后如果后面要找回这个就直接用这个压缩包的就行了，后来有了 svn，git 中心式和分布式的版本管理系统，它的一个特点是粒度可以控制到文件和代码行级别，对应的我们的 mysql 事务是不是也可以从一开始预想的表级别细化到行的级别，可能之前很多人都了解过，数据库的一行记录除了我们用户自定义的字段，还有一些额外的字段，去源码data0type.h里捞一下

    -
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    /* Precise data types for system columns and the length of those columns;
    NOTE: the values must run from 0 up in the order given! All codes must
    be less than 256 */
    #define DATA_ROW_ID 0     /* row id: a 48-bit integer */
    #define DATA_ROW_ID_LEN 6 /* stored length for row id */

    /** Transaction id: 6 bytes */
    constexpr size_t DATA_TRX_ID = 1;

    /** Transaction ID type size in bytes. */
    constexpr size_t DATA_TRX_ID_LEN = 6;

    /** Rollback data pointer: 7 bytes */
    constexpr size_t DATA_ROLL_PTR = 2;

    /** Rollback data pointer type size in bytes. */
    constexpr size_t DATA_ROLL_PTR_LEN = 7;
    +

    很久以前，有位面试官问到，你知道 mysql 的事务隔离级别吗，“额 O__O …，不太清楚”，完了之后我就去网上找相关的文章，找到了这篇MySQL 四种事务隔离级的说明, 文章写得特别好，看了这个就懂了各个事务隔离级别都是啥，不过看了这个之后多思考一下的话还是会发现问题，这么神奇的事务隔离级别是怎么实现的呢

    +

    其中 innodb 的事务隔离用到了标题里说到的 mvcc，Multiversion concurrency control, 直译过来就是多版本并发控制，先不讲这个究竟是个啥，考虑下如果纯猜测，这个事务隔离级别应该会是怎么样实现呢，愚钝的我想了下，可以在事务开始的时候拷贝一个表，这个可以支持 RR 级别，RC 级别就不支持了，而且要是个非常大的表，想想就不可行

    +

    腆着脸说虽然这个不可行，但是思路是对的，具体实行起来需要做一系列（肥肠多）的改动，首先根据我的理解，其实这个拷贝一个表是变成拷贝一条记录，但是如果有多个事务，那就得拷贝多次，这个问题其实可以借助版本管理系统来解释，在用版本管理系统，git 之类的之前，很原始的可能是开发完一个功能后，就打个压缩包用时间等信息命名，然后如果后面要找回这个就直接用这个压缩包的就行了，后来有了 svn，git 中心式和分布式的版本管理系统，它的一个特点是粒度可以控制到文件和代码行级别，对应的我们的 mysql 事务是不是也可以从一开始预想的表级别细化到行的级别，可能之前很多人都了解过，数据库的一行记录除了我们用户自定义的字段，还有一些额外的字段，去源码data0type.h里捞一下

    +
    /* Precise data types for system columns and the length of those columns;
+NOTE: the values must run from 0 up in the order given! All codes must
+be less than 256 */
+#define DATA_ROW_ID 0     /* row id: a 48-bit integer */
+#define DATA_ROW_ID_LEN 6 /* stored length for row id */
+
+/** Transaction id: 6 bytes */
+constexpr size_t DATA_TRX_ID = 1;
+
+/** Transaction ID type size in bytes. */
+constexpr size_t DATA_TRX_ID_LEN = 6;
+
+/** Rollback data pointer: 7 bytes */
+constexpr size_t DATA_ROLL_PTR = 2;
+
+/** Rollback data pointer type size in bytes. */
+constexpr size_t DATA_ROLL_PTR_LEN = 7;

    一个是 DATA_ROW_ID，这个是在数据没指定主键的时候会生成一个隐藏的，如果用户有指定主键就是主键了

    一个是 DATA_TRX_ID，这个表示这条记录的事务 ID

    @@ -325,7 +332,31 @@
  • 当记录的事务 id 小于最小活跃事务 id，说明是可见的，
  • 如果记录的事务 id 等于当前事务 id，说明是自己的更改，可见
  • 如果记录的事务 id 大于最大的活跃事务 id, 不可见
    • -
  • 如果记录的事务 id 介于 m_low_limit_id 和 m_up_limit_id 之间，则要判断它是否在 m_ids 中，如果在，不可见，如果不在，表示已提交，可见
    具体的代码捞一下看看
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    /** Check whether the changes by id are visible.
      @param[in]	id	transaction id to check against the view
      @param[in]	name	table name
      @return whether the view sees the modifications of id. */
      bool changes_visible(trx_id_t id, const table_name_t &name) const
          MY_ATTRIBUTE((warn_unused_result)) {
        ut_ad(id > 0);

        if (id < m_up_limit_id || id == m_creator_trx_id) {
          return (true);
        }

        check_trx_id_sanity(id, name);

        if (id >= m_low_limit_id) {
          return (false);

        } else if (m_ids.empty()) {
          return (true);
        }

        const ids_t::value_type *p = m_ids.data();

        return (!std::binary_search(p, p + m_ids.size(), id));
      }
    +
  • 如果记录的事务 id 介于 m_low_limit_id 和 m_up_limit_id 之间，则要判断它是否在 m_ids 中，如果在，不可见，如果不在，表示已提交，可见
    具体的代码捞一下看看
    /** Check whether the changes by id are visible.
+  @param[in]	id	transaction id to check against the view
+  @param[in]	name	table name
+  @return whether the view sees the modifications of id. */
+  bool changes_visible(trx_id_t id, const table_name_t &name) const
+      MY_ATTRIBUTE((warn_unused_result)) {
+    ut_ad(id > 0);
+
+    if (id < m_up_limit_id || id == m_creator_trx_id) {
+      return (true);
+    }
+
+    check_trx_id_sanity(id, name);
+
+    if (id >= m_low_limit_id) {
+      return (false);
+
+    } else if (m_ids.empty()) {
+      return (true);
+    }
+
+    const ids_t::value_type *p = m_ids.data();
+
+    return (!std::binary_search(p, p + m_ids.size(), id));
+  }
    剩下来一点是啥呢，就是 Read Committed 和 Repeated Read 也不一样，那前面说的 read view 都能支持吗，又是怎么支持呢，假如这个 read view 是在事务一开始就创建，那好像能支持的只是 RR 事务隔离级别，其实呢，这是通过创建 read view的时机，对于 RR 级别，就是在事务的第一个 select 语句是创建，对于 RC 级别，是在每个 select 语句执行前都是创建一次，那样就可以保证能读到所有已提交的数据
    • @@ -344,13 +375,13 @@
    聊聊 mysql 的 MVCC 续篇
  • -
    redis数据结构介绍五-第五部分 对象
    +
    redis数据结构介绍二-第二部分 跳表
  • redis系列介绍七-过期策略
  • -
    redis数据结构介绍三-第三部分 整数集合
    +
    redis数据结构介绍-第一部分 SDS，链表，字典
    • diff --git a/2020/05/02/聊聊-mysql-的-MVCC-续篇/index.html b/2020/05/02/聊聊-mysql-的-MVCC-续篇/index.html index 1511c3f557..790fb123e7 100644 --- a/2020/05/02/聊聊-mysql-的-MVCC-续篇/index.html +++ b/2020/05/02/聊聊-mysql-的-MVCC-续篇/index.html @@ -4,7 +4,7 @@ - + @@ -26,28 +26,24 @@ var CONFIG = {"hostname":"nicksxs.me","root":"/","scheme":"Pisces","version":"7.8.0","exturl":false,"sidebar":{"position":"left","display":"post","padding":18,"offset":12,"onmobile":false},"copycode":{"enable":true,"show_result":false,"style":null},"back2top":{"enable":true,"sidebar":false,"scrollpercent":false},"bookmark":{"enable":false,"color":"#222","save":"auto"},"fancybox":true,"mediumzoom":false,"lazyload":true,"pangu":false,"comments":{"style":"tabs","active":null,"storage":true,"lazyload":false,"nav":null},"algolia":{"hits":{"per_page":10},"labels":{"input_placeholder":"Search for Posts","hits_empty":"We didn't find any results for the search: ${query}","hits_stats":"${hits} results found in ${time} ms"}},"localsearch":{"enable":false,"trigger":"auto","top_n_per_article":1,"unescape":false,"preload":false},"motion":{"enable":true,"async":false,"transition":{"post_block":"fadeIn","post_header":"slideDownIn","post_body":"slideDownIn","coll_header":"slideLeftIn","sidebar":"slideUpIn"}}}; - + - + + - + - - + - - - + - - @@ -240,13 +236,6 @@     - - - - - Edited on - - @@ -313,7 +302,17 @@

    上一篇聊了mysql 的 innodb 引擎基于 read view 实现的 mvcc 和事务隔离级别，可能有些细心的小伙伴会发现一些问题，第一个是在 RC 级别下的事务提交后的可见性，这里涉及到了三个参数，m_low_limit_id，m_up_limit_id，m_ids，之前看到知乎的一篇写的非常不错的文章，但是就在这一点上似乎有点疑惑，这里基于源码和注释来解释下这个问题

    -
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    /**
    Opens a read view where exactly the transactions serialized before this
    point in time are seen in the view.
    @param id		Creator transaction id */

    void ReadView::prepare(trx_id_t id) {
      ut_ad(mutex_own(&trx_sys->mutex));

      m_creator_trx_id = id;

      m_low_limit_no = m_low_limit_id = m_up_limit_id = trx_sys->max_trx_id;
    +
    /**
+Opens a read view where exactly the transactions serialized before this
+point in time are seen in the view.
+@param id		Creator transaction id */
+
+void ReadView::prepare(trx_id_t id) {
+  ut_ad(mutex_own(&trx_sys->mutex));
+
+  m_creator_trx_id = id;
+
+  m_low_limit_no = m_low_limit_id = m_up_limit_id = trx_sys->max_trx_id;

    m_low_limit_id赋的值是trx_sys->max_trx_id，代表的是当前系统最小的未分配的事务 id，所以呢，举个例子，当前有三个活跃事务，事务 id 分别是 100，200，300，而 m_up_limit_id = 100, m_low_limit_id = 301，当事务 id 是 200 的提交之后，它的更新就是可以被 100 和 300 看到，而不是说 m_ids 里没了 200，并且 200 比 100 大就应该不可见了

    幻读

    还有一个问题是幻读的问题，这貌似也是个高频面试题，啥意思呢，或者说跟它最常拿来比较的脏读，脏读是指读到了别的事务未提交的数据，因为未提交，严格意义上来讲，不一定是会被最后落到库里，可能会回滚，也就是在 read uncommitted 级别下会出现的问题，但是幻读不太一样，幻读是指两次查询的结果数量不一样，比如我查了第一次是 select * from table1 where id < 10 for update,查出来了一条结果 id 是 5，然后再查一下发现出来了一条 id 是 5，一条 id 是 7，那是不是有点尴尬了，其实呢这个点我觉得脏读跟幻读也比较是从原理层面来命名，如果第一次接触的同学发觉有点不理解也比较正常，因为从逻辑上讲总之都是数据不符合预期，但是基于源码层面其实是不同的情况，幻读是在原先的 read view 无法完全解决的，怎么解决呢，简单的来说就是锁咯，我们知道innodb 是基于 record lock 行锁的，但是貌似没有办法解决这种问题，那么 innodb 就引入了 gap lock 间隙锁，比如上面说的情况下，id 小于 10 的情况下，是都应该锁住的，gap lock 其实是基于索引结构来锁的，因为索引树除了树形结构之外，还有一个next record 的指针，gap lock 也是基于这个来锁的
    看一下 mysql 的文档

    @@ -336,13 +335,13 @@
    聊聊 mysql 的 MVCC
  • -
    redis数据结构介绍五-第五部分 对象
    +
    redis数据结构介绍二-第二部分 跳表
  • redis系列介绍七-过期策略
  • -
    redis数据结构介绍三-第三部分 整数集合
    +
    redis数据结构介绍-第一部分 SDS，链表，字典
    • @@ -474,7 +473,7 @@
    -
    1. 1. 幻读
    +
    1. 1. 幻读
    diff --git a/2020/05/10/聊聊-mysql-的-MVCC-续续篇之加锁分析/index.html b/2020/05/10/聊聊-mysql-的-MVCC-续续篇之加锁分析/index.html index ff72ad52de..4a20e41325 100644 --- a/2020/05/10/聊聊-mysql-的-MVCC-续续篇之加锁分析/index.html +++ b/2020/05/10/聊聊-mysql-的-MVCC-续续篇之加锁分析/index.html @@ -4,7 +4,7 @@ - + @@ -32,23 +32,19 @@ + - + - - + - - - + - - @@ -239,9 +235,8 @@ Posted on - - + @@ -320,7 +315,7 @@
  • update table set ? where ?;
  • delete from table where ?;
    • -

    除了第一条是 S 锁之外，其他都是 X 排他锁，这边在顺带下，S 锁表示共享锁， X 表示独占锁，同为 S 锁之间不冲突，S 与 X，X 与 S，X 与 X 之间都冲突，也就是加了前者，后者就加不上了
    我们知道对于 RC 级别会出现幻读现象，对于 RR 级别不会出现，主要的区别是 RR 级别下对于以上的加锁读取都根据情况加上了 gap 锁，那么是不是 RR 级别下以上所有的都是要加 gap 锁呢，当然不是
    举个例子，RR 事务隔离级别下，table1 有个主键id 字段
    select * from table1 where id = 10 for update
    这条语句要加 gap 锁吗？
    答案是不需要，这里其实算是我看了这么久的一点自己的理解，啥时候要加 gap 锁，判断的条件是根据我查询的数据是否会因为不加 gap 锁而出现数量的不一致，我上面这条查询语句，在什么情况下会出现查询结果数量不一致呢，只要在这条记录被更新或者删除的时候，有没有可能我第一次查出来一条，第二次变成两条了呢，不可能，因为是主键索引。
    再变更下这个题的条件，当 id 不是主键，但是是唯一索引，这样需要怎么加锁，注意问题是怎么加锁，不是需不需要加 gap 锁，这里呢就是稍微延伸一下，把聚簇索引（主键索引）和二级索引带一下，当 id 不是主键，说明是个二级索引，但是它是唯一索引，体会下，首先对于 id = 10这个二级索引肯定要加锁，要不要锁 gap 呢，不用，因为是唯一索引，id = 10 只可能有这一条记录，然后呢，这样是不是就好了，还不行，因为啥，因为它是二级索引，对应的主键索引的记录才是真正的数据，万一被更新掉了咋办，所以在 id = 10 对应的主键索引上也需要加上锁（默认都是 record lock行锁），那主键索引上要不要加 gap 呢，也不用，也是精确定位到这一条记录
    最后呢，当 id 不是主键，也不是唯一索引，只是个普通的索引，这里就需要大名鼎鼎的 gap 锁了，
    是时候画个图了

    其实核心的目的还是不让这个 id=10 的记录不会出现幻读，那么就需要在 id 这个索引上加上三个 gap 锁，主键索引上就不用了，在 id 索引上已经控制住了id = 10 不会出现幻读，主键索引上这两条对应的记录已经锁了，所以就这样 OK 了

    +

    除了第一条是 S 锁之外，其他都是 X 排他锁，这边在顺带下，S 锁表示共享锁， X 表示独占锁，同为 S 锁之间不冲突，S 与 X，X 与 S，X 与 X 之间都冲突，也就是加了前者，后者就加不上了
    我们知道对于 RC 级别会出现幻读现象，对于 RR 级别不会出现，主要的区别是 RR 级别下对于以上的加锁读取都根据情况加上了 gap 锁，那么是不是 RR 级别下以上所有的都是要加 gap 锁呢，当然不是
    举个例子，RR 事务隔离级别下，table1 有个主键id 字段
    select * from table1 where id = 10 for update
    这条语句要加 gap 锁吗？
    答案是不需要，这里其实算是我看了这么久的一点自己的理解，啥时候要加 gap 锁，判断的条件是根据我查询的数据是否会因为不加 gap 锁而出现数量的不一致，我上面这条查询语句，在什么情况下会出现查询结果数量不一致呢，只要在这条记录被更新或者删除的时候，有没有可能我第一次查出来一条，第二次变成两条了呢，不可能，因为是主键索引。
    再变更下这个题的条件，当 id 不是主键，但是是唯一索引，这样需要怎么加锁，注意问题是怎么加锁，不是需不需要加 gap 锁，这里呢就是稍微延伸一下，把聚簇索引（主键索引）和二级索引带一下，当 id 不是主键，说明是个二级索引，但是它是唯一索引，体会下，首先对于 id = 10这个二级索引肯定要加锁，要不要锁 gap 呢，不用，因为是唯一索引，id = 10 只可能有这一条记录，然后呢，这样是不是就好了，还不行，因为啥，因为它是二级索引，对应的主键索引的记录才是真正的数据，万一被更新掉了咋办，所以在 id = 10 对应的主键索引上也需要加上锁（默认都是 record lock行锁），那主键索引上要不要加 gap 呢，也不用，也是精确定位到这一条记录
    最后呢，当 id 不是主键，也不是唯一索引，只是个普通的索引，这里就需要大名鼎鼎的 gap 锁了，
    是时候画个图了

    其实核心的目的还是不让这个 id=10 的记录不会出现幻读，那么就需要在 id 这个索引上加上三个 gap 锁，主键索引上就不用了，在 id 索引上已经控制住了id = 10 不会出现幻读，主键索引上这两条对应的记录已经锁了，所以就这样 OK 了

    @@ -337,13 +332,13 @@
    聊聊 mysql 的 MVCC
  • -
    redis数据结构介绍五-第五部分 对象
    +
    redis数据结构介绍二-第二部分 跳表
  • redis系列介绍七-过期策略
  • -
    redis数据结构介绍三-第三部分 整数集合
    +
    redis数据结构介绍-第一部分 SDS，链表，字典
    • diff --git a/2020/05/17/聊聊我理解的分布式事务/index.html b/2020/05/17/聊聊我理解的分布式事务/index.html index 93c8918351..6dd035d2a9 100644 --- a/2020/05/17/聊聊我理解的分布式事务/index.html +++ b/2020/05/17/聊聊我理解的分布式事务/index.html @@ -4,7 +4,7 @@ - + @@ -32,9 +32,10 @@ + - + @@ -234,13 +235,6 @@     - - - - - Edited on - - @@ -300,25 +294,25 @@

    前面说了mysql数据库的事务相关的，那事务是用来干嘛的，这里得补一下ACID，

    -

    ACID，是指数据库管理系统（DBMS）在写入或更新资料的过程中，为保证事务（transaction）是正确可靠的，所必须具备的四个特性：原子性（atomicity，或称不可分割性）、一致性（consistency）、隔离性（isolation，又称独立性）、持久性（durability）。

    +

    ACID，是指数据库管理系统（DBMS）在写入或更新资料的过程中，为保证事务（transaction）是正确可靠的，所必须具备的四个特性：原子性（atomicity，或称不可分割性）、一致性（consistency）、隔离性（isolation，又称独立性）、持久性（durability）。

      -

    • Atomicity（原子性）：一个事务（transaction）中的所有操作，或者全部完成，或者全部不完成，不会结束在中间某个环节。事务在执行过程中发生错误，会被回滚（Rollback）到事务开始前的状态，就像这个事务从来没有执行过一样。即，事务不可分割、不可约简。[1]

      +

    • Atomicity（原子性）：一个事务（transaction）中的所有操作，或者全部完成，或者全部不完成，不会结束在中间某个环节。事务在执行过程中发生错误，会被回滚（Rollback）到事务开始前的状态，就像这个事务从来没有执行过一样。即，事务不可分割、不可约简。[1]

      • -

    • Consistency（一致性）：在事务开始之前和事务结束以后，数据库的完整性没有被破坏。这表示写入的资料必须完全符合所有的预设约束、触发器、级联回滚等。[1]

      +

    • Consistency（一致性）：在事务开始之前和事务结束以后，数据库的完整性没有被破坏。这表示写入的资料必须完全符合所有的预设约束、触发器、级联回滚等。[1]

      • -

    • Isolation（隔离性）：数据库允许多个并发事务同时对其数据进行读写和修改的能力，隔离性可以防止多个事务并发执行时由于交叉执行而导致数据的不一致。事务隔离分为不同级别，包括未提交读（Read uncommitted）、提交读（read committed）、可重复读（repeatable read）和串行化（Serializable）。[1]

      +

    • Isolation（隔离性）：数据库允许多个并发事务同时对其数据进行读写和修改的能力，隔离性可以防止多个事务并发执行时由于交叉执行而导致数据的不一致。事务隔离分为不同级别，包括未提交读（Read uncommitted）、提交读（read committed）、可重复读（repeatable read）和串行化（Serializable）。[1]

      • -

    • Durability（持久性）：事务处理结束后，对数据的修改就是永久的，即便系统故障也不会丢失。[1]

      +

    • Durability（持久性）：事务处理结束后，对数据的修改就是永久的，即便系统故障也不会丢失。[1]

    在mysql中，借助于MVCC，各种级别的锁，日志等特性来实现了事务的ACID，但是这个我们通常是对于一个数据库服务的定义，常见的情况下我们的数据库随着业务发展也会从单实例变成多实例，组成主从Master-Slave架构，这个时候其实会有一些问题随之出现，比如说主从同步延迟，假如在业务代码中做了读写分离，对于一些敏感度较低的数据其实问题不是很大，只要主从延迟不到特别夸张的地步一般都是可以忍受的，但是对于一些核心的业务数据，比如订单之类的，不能忍受数据不一致，下了单了，付了款了，一刷订单列表，发现这个订单还没支付，甚至订单都没在，这对于用户来讲是恨不能容忍的错误，那么这里就需要一些措施，要不就不读写分离，要不就在 redis 这类缓存下订单，或者支付后加个延时等，这些都是一些补偿措施，并且这也是一个不太切当的例子，比较合适的例子也可以用这个下单来说，一般在电商平台下单会有挺多要做的事情，比如像下面这个图

    -

    -

    下单的是后要冻结核销优惠券，如果账户里有钱要冻结扣除账户里的钱，如果使用了J 豆也一样，可能还有 E 卡，忽略我借用的平台，因为目前一般后台服务化之后，可能每一项都是对应的一个后台服务，我们期望的执行过程是要不全成功，要不就全保持执行前状态，不能是部分扣减核销成功了，部分还不行，所以我们处理这种情况会引入一些通用的方案，第一种叫二阶段提交,

    +

    +

    下单的是后要冻结核销优惠券，如果账户里有钱要冻结扣除账户里的钱，如果使用了J 豆也一样，可能还有 E 卡，忽略我借用的平台，因为目前一般后台服务化之后，可能每一项都是对应的一个后台服务，我们期望的执行过程是要不全成功，要不就全保持执行前状态，不能是部分扣减核销成功了，部分还不行，所以我们处理这种情况会引入一些通用的方案，第一种叫二阶段提交,

    -

    二阶段提交（英语：Two-phase Commit）是指在计算机网络以及数据库领域内，为了使基于分布式系统架构下的所有节点在进行事务提交时保持一致性而设计的一种算法。通常，二阶段提交也被称为是一种协议（Protocol）。在分布式系统中，每个节点虽然可以知晓自己的操作时成功或者失败，却无法知道其他节点的操作的成功或失败。当一个事务跨越多个节点时，为了保持事务的ACID特性，需要引入一个作为协调者的组件来统一掌控所有节点（称作参与者）的操作结果并最终指示这些节点是否要把操作结果进行真正的提交（比如将更新后的数据写入磁盘等等）。因此，二阶段提交的算法思路可以概括为： 参与者将操作成败通知协调者，再由协调者根据所有参与者的反馈情报决定各参与者是否要提交操作还是中止操作。

    +

    二阶段提交（英语：Two-phase Commit）是指在计算机网络以及数据库领域内，为了使基于分布式系统架构下的所有节点在进行事务提交时保持一致性而设计的一种算法。通常，二阶段提交也被称为是一种协议（Protocol）。在分布式系统中，每个节点虽然可以知晓自己的操作时成功或者失败，却无法知道其他节点的操作的成功或失败。当一个事务跨越多个节点时，为了保持事务的ACID特性，需要引入一个作为协调者的组件来统一掌控所有节点（称作参与者）的操作结果并最终指示这些节点是否要把操作结果进行真正的提交（比如将更新后的数据写入磁盘等等）。因此，二阶段提交的算法思路可以概括为： 参与者将操作成败通知协调者，再由协调者根据所有参与者的反馈情报决定各参与者是否要提交操作还是中止操作。

    -

    对于上面的例子，我们将整个过程分成两个阶段，首先是提交请求阶段，这个阶段大概需要做的是确定资源存在，锁定资源，可能还要做好失败后回滚的准备，如果这些都 ok 了那么就响应成功，这里其实用到了一个叫事务的协调者的角色，类似于裁判员，每个节点都反馈第一阶段成功后，开始执行第二阶段，也就是实际执行操作，这里也是需要所有节点都反馈成功后才是执行成功，要不就是失败回滚。其实常用的分布式事务的解决方案主要也是基于此方案的改进，比如后面介绍的三阶段提交，有三阶段提交就是因为二阶段提交比较尴尬的几个点，

    +

    对于上面的例子，我们将整个过程分成两个阶段，首先是提交请求阶段，这个阶段大概需要做的是确定资源存在，锁定资源，可能还要做好失败后回滚的准备，如果这些都 ok 了那么就响应成功，这里其实用到了一个叫事务的协调者的角色，类似于裁判员，每个节点都反馈第一阶段成功后，开始执行第二阶段，也就是实际执行操作，这里也是需要所有节点都反馈成功后才是执行成功，要不就是失败回滚。其实常用的分布式事务的解决方案主要也是基于此方案的改进，比如后面介绍的三阶段提交，有三阶段提交就是因为二阶段提交比较尴尬的几个点，

    • 第一是对于两阶段提交，其中默认只有协调者有超时时间，当一个参与者进入卡死状态时只能依赖协调者的超时来结束任务，这中间的时间参与者都是锁定着资源
    • 第二是协调者的单点问题，万一挂了，参与者就会在那傻等着
      • diff --git a/2020/05/22/聊聊我刚学会的应用诊断方法/index.html b/2020/05/22/聊聊我刚学会的应用诊断方法/index.html index d59a4de7fa..3d56a1fe46 100644 --- a/2020/05/22/聊聊我刚学会的应用诊断方法/index.html +++ b/2020/05/22/聊聊我刚学会的应用诊断方法/index.html @@ -4,7 +4,7 @@ - + @@ -32,17 +32,13 @@ + - + - - - - - @@ -236,13 +232,6 @@ - - - - - Edited on - - @@ -304,8 +293,14 @@
      -

      因为传说中的出身问题，我以前写的是PHP，在使用 swoole 之前，基本的应用调试手段就是简单粗暴的 var_dump，exit，对于单进程模型的 PHP 也是简单有效，技术栈换成 Java 之后，就变得没那么容易，一方面是需要编译，另一方面是一般都是基于 spring 的项目，如果问题定位比较模糊，那框架层的是很难靠简单的 System.out.println 或者打 log 解决，(PS：我觉得可能我写的东西比较适合从 PHP 这种弱类型语言转到 Java 的小白同学)这个时候一方面因为是 Java，有了非常好用的 idea IDE 的支持，可以各种花式调试，条件断点尤其牛叉，但是又因为有 Spring+Java 的双重原因，有些情况下单步调试可以把手按废掉，这也是我之前一直比较困惑苦逼的点，后来随着慢慢精（jiang）进（you）之后，比如对于一个 oom 的情况，我们可以通过启动参数加上-XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=xx/xx 来配置溢出时的堆dump 日志，获取到这个文件后，我们可以通过像 Memory Analyzer (MAT)[https://www.eclipse.org/mat/] (The Eclipse Memory Analyzer is a fast and feature-rich Java heap analyzer that helps you find memory leaks and reduce memory consumption.)来查看诊断问题所在，之前用到的时候是因为有个死循环一直往链表里塞数据，属于比较简单的，后来一次是由于运维进行应用迁移时按默认的统一配置了堆内存大小，导致内存的确不够用，所以溢出了，
      今天想说的其实主要是我们的 thread dump，这也是我最近才真正用的一个方法，可能真的很小白了，用过 ide 的单步调试其实都知道会有一个一层层的玩意，比如函数从 A，调用了 B，再从 B 调用了 C，一直往下(因为是 Java，所以还有很多🤦‍♂️)，这个其实也是大部分语言的调用模型，利用了栈这个数据结构，通过这个结构我们可以知道代码的调用链路，由于对于一个 spring 应用，在本身框架代码量非常庞大的情况下，外加如果应用代码也是非常多的时候，有时候通过单步调试真的很难短时间定位到问题，需要非常大的耐心和仔细观察，当然不是说完全不行，举个例子当我的应用经常启动需要非常长的时间，因为本身应用有非常多个 bean，比较难说究竟是 bean 的加载的确很慢还是有什么异常原因，这种时候就可以使用 thread dump 了，具体怎么操作呢

      如果在idea 中运行或者调试时，可以直接点击这个照相机一样的按钮，右边就会出现了左边会显示所有的线程，右边会显示线程栈，

      -
      1
      2
      3
      4
      5
      6
      7
      "main@1" prio=5 tid=0x1 nid=NA runnable
        java.lang.Thread.State: RUNNABLE
      	  at TreeDistance.treeDist(TreeDistance.java:64)
      	  at TreeDistance.treeDist(TreeDistance.java:65)
      	  at TreeDistance.treeDist(TreeDistance.java:65)
      	  at TreeDistance.treeDist(TreeDistance.java:65)
      	  at TreeDistance.main(TreeDistance.java:45)
      +

      因为传说中的出身问题，我以前写的是PHP，在使用 swoole 之前，基本的应用调试手段就是简单粗暴的 var_dump，exit，对于单进程模型的 PHP 也是简单有效，技术栈换成 Java 之后，就变得没那么容易，一方面是需要编译，另一方面是一般都是基于 spring 的项目，如果问题定位比较模糊，那框架层的是很难靠简单的 System.out.println 或者打 log 解决，(PS：我觉得可能我写的东西比较适合从 PHP 这种弱类型语言转到 Java 的小白同学)这个时候一方面因为是 Java，有了非常好用的 idea IDE 的支持，可以各种花式调试，条件断点尤其牛叉，但是又因为有 Spring+Java 的双重原因，有些情况下单步调试可以把手按废掉，这也是我之前一直比较困惑苦逼的点，后来随着慢慢精（jiang）进（you）之后，比如对于一个 oom 的情况，我们可以通过启动参数加上-XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=xx/xx 来配置溢出时的堆dump 日志，获取到这个文件后，我们可以通过像 Memory Analyzer (MAT)[https://www.eclipse.org/mat/] (The Eclipse Memory Analyzer is a fast and feature-rich Java heap analyzer that helps you find memory leaks and reduce memory consumption.)来查看诊断问题所在，之前用到的时候是因为有个死循环一直往链表里塞数据，属于比较简单的，后来一次是由于运维进行应用迁移时按默认的统一配置了堆内存大小，导致内存的确不够用，所以溢出了，
      今天想说的其实主要是我们的 thread dump，这也是我最近才真正用的一个方法，可能真的很小白了，用过 ide 的单步调试其实都知道会有一个一层层的玩意，比如函数从 A，调用了 B，再从 B 调用了 C，一直往下(因为是 Java，所以还有很多🤦‍♂️)，这个其实也是大部分语言的调用模型，利用了栈这个数据结构，通过这个结构我们可以知道代码的调用链路，由于对于一个 spring 应用，在本身框架代码量非常庞大的情况下，外加如果应用代码也是非常多的时候，有时候通过单步调试真的很难短时间定位到问题，需要非常大的耐心和仔细观察，当然不是说完全不行，举个例子当我的应用经常启动需要非常长的时间，因为本身应用有非常多个 bean，比较难说究竟是 bean 的加载的确很慢还是有什么异常原因，这种时候就可以使用 thread dump 了，具体怎么操作呢

      如果在idea 中运行或者调试时，可以直接点击这个照相机一样的按钮，右边就会出现了左边会显示所有的线程，右边会显示线程栈，

      +
      "main@1" prio=5 tid=0x1 nid=NA runnable
+  java.lang.Thread.State: RUNNABLE
+	  at TreeDistance.treeDist(TreeDistance.java:64)
+	  at TreeDistance.treeDist(TreeDistance.java:65)
+	  at TreeDistance.treeDist(TreeDistance.java:65)
+	  at TreeDistance.treeDist(TreeDistance.java:65)
+	  at TreeDistance.main(TreeDistance.java:45)

      这就是我们主线程的堆栈信息了，main 表示这个线程名，prio表示优先级，默认是 5，tid 表示线程 id，nid 表示对应的系统线程，后面的runnable 表示目前线程状态，因为是被我打了断点，所以是就许状态，然后下面就是对应的线程栈内容了，在TreeDistance类的 treeDist方法中，对应的文件行数是 64 行。
      这里使用 thread dump一般也不会是上面我截图代码里的这种代码量很少的，一般是大型项目，有时候跑着跑着没反应，又不知道跑到哪了，特别是一些刚接触的大项目或者需要定位一个大项目的一个疑难问题，一时没思路时，可以使用这个方法，个人觉得非常有帮助。

      diff --git a/2020/05/31/聊聊-Dubbo-的-SPI/index.html b/2020/05/31/聊聊-Dubbo-的-SPI/index.html index 808ab2a22c..b98b9275c5 100644 --- a/2020/05/31/聊聊-Dubbo-的-SPI/index.html +++ b/2020/05/31/聊聊-Dubbo-的-SPI/index.html @@ -4,7 +4,7 @@ - + @@ -32,15 +32,16 @@ + - + + - @@ -232,9 +233,8 @@       Posted on - - +       @@ -304,11 +304,76 @@

      简单介绍了 Java的 SPI，再来说说 dubbo 的，dubbo 中为啥要用 SPI 呢，主要是为了框架的可扩展性和性能方面的考虑，比如协议层 dubbo 默认使用 dubbo 协议，同时也支持很多其他协议，也支持用户自己实现协议，那么跟 Java 的 SPI 会有什么区别呢，我们也来看个文件

      bqxWMp

      是不是看着很想，又有点不一样，在 Java 的 SPI 配置文件里每一行只有一个实现类的全限定名，在 Dubbo的 SPI配置文件中是 key=value 的形式，我们只需要对应的 key 就能加载对应的实现，

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      /**
           * 返回指定名字的扩展。如果指定名字的扩展不存在，则抛异常 {@link IllegalStateException}.
           *
           * @param name
           * @return
           */
      	@SuppressWarnings("unchecked")
      	public T getExtension(String name) {
      		if (name == null || name.length() == 0)
      		    throw new IllegalArgumentException("Extension name == null");
      		if ("true".equals(name)) {
      		    return getDefaultExtension();
      		}
      		Holder<Object> holder = cachedInstances.get(name);
      		if (holder == null) {
      		    cachedInstances.putIfAbsent(name, new Holder<Object>());
      		    holder = cachedInstances.get(name);
      		}
      		Object instance = holder.get();
      		if (instance == null) {
      		    synchronized (holder) {
      	            instance = holder.get();
      	            if (instance == null) {
      	                instance = createExtension(name);
      	                holder.set(instance);
      	            }
      	        }
      		}
      		return (T) instance;
      	}
      +
      /**
+     * 返回指定名字的扩展。如果指定名字的扩展不存在，则抛异常 {@link IllegalStateException}.
+     *
+     * @param name
+     * @return
+     */
+	@SuppressWarnings("unchecked")
+	public T getExtension(String name) {
+		if (name == null || name.length() == 0)
+		    throw new IllegalArgumentException("Extension name == null");
+		if ("true".equals(name)) {
+		    return getDefaultExtension();
+		}
+		Holder<Object> holder = cachedInstances.get(name);
+		if (holder == null) {
+		    cachedInstances.putIfAbsent(name, new Holder<Object>());
+		    holder = cachedInstances.get(name);
+		}
+		Object instance = holder.get();
+		if (instance == null) {
+		    synchronized (holder) {
+	            instance = holder.get();
+	            if (instance == null) {
+	                instance = createExtension(name);
+	                holder.set(instance);
+	            }
+	        }
+		}
+		return (T) instance;
+	}

      这里其实就可以看出来第二个不同点了，就是这个cachedInstances，第一个是不用像 Java 原生的 SPI 那样去遍历加载对应的服务类，只需要通过 key 去寻找，并且寻找的时候会先从缓存的对象里去取，还有就是注意下这里的 DCL(double check lock)

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      @SuppressWarnings("unchecked")
          private T createExtension(String name) {
              Class<?> clazz = getExtensionClasses().get(name);
              if (clazz == null) {
                  throw findException(name);
              }
              try {
                  T instance = (T) EXTENSION_INSTANCES.get(clazz);
                  if (instance == null) {
                      EXTENSION_INSTANCES.putIfAbsent(clazz, (T) clazz.newInstance());
                      instance = (T) EXTENSION_INSTANCES.get(clazz);
                  }
                  injectExtension(instance);
                  Set<Class<?>> wrapperClasses = cachedWrapperClasses;
                  if (wrapperClasses != null && wrapperClasses.size() > 0) {
                      for (Class<?> wrapperClass : wrapperClasses) {
                          instance = injectExtension((T) wrapperClass.getConstructor(type).newInstance(instance));
                      }
                  }
                  return instance;
              } catch (Throwable t) {
                  throw new IllegalStateException("Extension instance(name: " + name + ", class: " +
                          type + ")  could not be instantiated: " + t.getMessage(), t);
              }
          }
      +
      @SuppressWarnings("unchecked")
+    private T createExtension(String name) {
+        Class<?> clazz = getExtensionClasses().get(name);
+        if (clazz == null) {
+            throw findException(name);
+        }
+        try {
+            T instance = (T) EXTENSION_INSTANCES.get(clazz);
+            if (instance == null) {
+                EXTENSION_INSTANCES.putIfAbsent(clazz, (T) clazz.newInstance());
+                instance = (T) EXTENSION_INSTANCES.get(clazz);
+            }
+            injectExtension(instance);
+            Set<Class<?>> wrapperClasses = cachedWrapperClasses;
+            if (wrapperClasses != null && wrapperClasses.size() > 0) {
+                for (Class<?> wrapperClass : wrapperClasses) {
+                    instance = injectExtension((T) wrapperClass.getConstructor(type).newInstance(instance));
+                }
+            }
+            return instance;
+        } catch (Throwable t) {
+            throw new IllegalStateException("Extension instance(name: " + name + ", class: " +
+                    type + ")  could not be instantiated: " + t.getMessage(), t);
+        }
+    }

      然后就是创建扩展了，这里如果 wrapperClasses 就会遍历生成wrapper实例，并做 setter 依赖注入，但是这里cachedWrapperClasses的来源还是有点搞不清楚，得再看下 com.alibaba.dubbo.common.extension.ExtensionLoader#loadFile的具体逻辑
      又看了遍新的代码，这个函数被抽出来了

      -
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      /**
          * test if clazz is a wrapper class
          * <p>
          * which has Constructor with given class type as its only argument
          */
         private boolean isWrapperClass(Class<?> clazz) {
             try {
                 clazz.getConstructor(type);
                 return true;
             } catch (NoSuchMethodException e) {
                 return false;
             }
         }
      +
      /**
+    * test if clazz is a wrapper class
+    * <p>
+    * which has Constructor with given class type as its only argument
+    */
+   private boolean isWrapperClass(Class<?> clazz) {
+       try {
+           clazz.getConstructor(type);
+           return true;
+       } catch (NoSuchMethodException e) {
+           return false;
+       }
+   }

      是否是 wrapperClass 其实就看构造函数的。

      @@ -329,7 +394,7 @@
      聊聊 dubbo 的线程池
    • -
      聊聊我刚学会的应用诊断方法
      +
      Maven实用小技巧
    • mybatis 的 $ 和 # 是有啥区别
      diff --git a/2020/06/06/聊聊-Dubbo-的-SPI-续之自适应拓展/index.html b/2020/06/06/聊聊-Dubbo-的-SPI-续之自适应拓展/index.html index 546bf8b752..c22451d1cf 100644 --- a/2020/06/06/聊聊-Dubbo-的-SPI-续之自适应拓展/index.html +++ b/2020/06/06/聊聊-Dubbo-的-SPI-续之自适应拓展/index.html @@ -4,7 +4,7 @@ - + @@ -32,13 +32,14 @@ + - + + - @@ -232,9 +233,8 @@ Posted on - - + @@ -301,18 +301,132 @@
      -

      Adaptive

      这个应该是 Dubbo SPI 里最玄妙的东西了，一开始没懂，自适应扩展点加载，
      dubbo://123.123.123.123:1234/com.nicksxs.demo.service.HelloWorldService?anyhost=true&application=demo&default.loadbalance=random&default.service.filter=LoggerFilter&dubbo=2.5.3&interface=com.nicksxs.demo.service.HelloWorldService&logger=slf4j&methods=method1,method2,method3,method4&pid=4292&retries=0&side=provider&threadpool=fixed&threads=200&timeout=2000&timestamp=1590647155886
      那我从比较能理解的角度或者说思路去讲讲我的理解，因为直接将原理如果脱离了使用，对于我这样的理解能力比较差的可能会比较吃力，从使用场景开始讲可能会比较舒服了，这里可以看到参数里有蛮多的，举个例子，比如这个 threadpool = fixed，说明线程池使用的是 fixed 对应的实现，也就是下图的这个

      这样子似乎没啥问题了，反正就是用dubbo 的 spi 加载嘛，好像没啥问题，其实问题还是存在的，或者说不太优雅，比如要先判断我这个 fixed 对应的实现类是哪个，这里可能就有个 if-else 判断了，但是 dubbo 的开发人员似乎不太想这么做这个事情，

      +

      Adaptive

      这个应该是 Dubbo SPI 里最玄妙的东西了，一开始没懂，自适应扩展点加载，
      dubbo://123.123.123.123:1234/com.nicksxs.demo.service.HelloWorldService?anyhost=true&application=demo&default.loadbalance=random&default.service.filter=LoggerFilter&dubbo=2.5.3&interface=com.nicksxs.demo.service.HelloWorldService&logger=slf4j&methods=method1,method2,method3,method4&pid=4292&retries=0&side=provider&threadpool=fixed&threads=200&timeout=2000&timestamp=1590647155886
      那我从比较能理解的角度或者说思路去讲讲我的理解，因为直接将原理如果脱离了使用，对于我这样的理解能力比较差的可能会比较吃力，从使用场景开始讲可能会比较舒服了，这里可以看到参数里有蛮多的，举个例子，比如这个 threadpool = fixed，说明线程池使用的是 fixed 对应的实现，也就是下图的这个

      这样子似乎没啥问题了，反正就是用dubbo 的 spi 加载嘛，好像没啥问题，其实问题还是存在的，或者说不太优雅，比如要先判断我这个 fixed 对应的实现类是哪个，这里可能就有个 if-else 判断了，但是 dubbo 的开发人员似乎不太想这么做这个事情，

      譬如我们在引用一个服务时，在ReferenceConfig 中的

      -
      1
      private static final Protocol refprotocol = ExtensionLoader.getExtensionLoader(Protocol.class).getAdaptiveExtension();
      +
      private static final Protocol refprotocol = ExtensionLoader.getExtensionLoader(Protocol.class).getAdaptiveExtension();

      就获取了自适应拓展，

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      public T getAdaptiveExtension() {
              Object instance = cachedAdaptiveInstance.get();
              if (instance == null) {
                  if (createAdaptiveInstanceError == null) {
                      synchronized (cachedAdaptiveInstance) {
                          instance = cachedAdaptiveInstance.get();
                          if (instance == null) {
                              try {
                                  instance = createAdaptiveExtension();
                                  cachedAdaptiveInstance.set(instance);
                              } catch (Throwable t) {
                                  createAdaptiveInstanceError = t;
                                  throw new IllegalStateException("fail to create adaptive instance: " + t.toString(), t);
                              }
                          }
                      }
                  } else {
                      throw new IllegalStateException("fail to create adaptive instance: " + createAdaptiveInstanceError.toString(), createAdaptiveInstanceError);
                  }
              }

              return (T) instance;
          }
      +
      public T getAdaptiveExtension() {
+        Object instance = cachedAdaptiveInstance.get();
+        if (instance == null) {
+            if (createAdaptiveInstanceError == null) {
+                synchronized (cachedAdaptiveInstance) {
+                    instance = cachedAdaptiveInstance.get();
+                    if (instance == null) {
+                        try {
+                            instance = createAdaptiveExtension();
+                            cachedAdaptiveInstance.set(instance);
+                        } catch (Throwable t) {
+                            createAdaptiveInstanceError = t;
+                            throw new IllegalStateException("fail to create adaptive instance: " + t.toString(), t);
+                        }
+                    }
+                }
+            } else {
+                throw new IllegalStateException("fail to create adaptive instance: " + createAdaptiveInstanceError.toString(), createAdaptiveInstanceError);
+            }
+        }
+
+        return (T) instance;
+    }

      这里也使用了 DCL，来锁cachedAdaptiveInstance，当缓存中没有时就去创建自适应拓展

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      private T createAdaptiveExtension() {
              try {
                // 获取自适应拓展类然后实例化
                  return injectExtension((T) getAdaptiveExtensionClass().newInstance());
              } catch (Exception e) {
                  throw new IllegalStateException("Can not create adaptive extension " + type + ", cause: " + e.getMessage(), e);
              }
          }

      private Class<?> getAdaptiveExtensionClass() {
        			// 这里会获取拓展类，如果没有自适应的拓展类，那么就需要调用createAdaptiveExtensionClass
              getExtensionClasses();
              if (cachedAdaptiveClass != null) {
                  return cachedAdaptiveClass;
              }
              return cachedAdaptiveClass = createAdaptiveExtensionClass();
          }
      private Class<?> createAdaptiveExtensionClass() {
        			// 这里去生成了自适应拓展的代码，具体生成逻辑比较复杂先不展开讲
              String code = createAdaptiveExtensionClassCode();
              ClassLoader classLoader = findClassLoader();
              com.alibaba.dubbo.common.compiler.Compiler compiler = ExtensionLoader.getExtensionLoader(com.alibaba.dubbo.common.compiler.Compiler.class).getAdaptiveExtension();
              return compiler.compile(code, classLoader);
          }
      +
      private T createAdaptiveExtension() {
+        try {
+          // 获取自适应拓展类然后实例化
+            return injectExtension((T) getAdaptiveExtensionClass().newInstance());
+        } catch (Exception e) {
+            throw new IllegalStateException("Can not create adaptive extension " + type + ", cause: " + e.getMessage(), e);
+        }
+    }
+
+private Class<?> getAdaptiveExtensionClass() {
+  			// 这里会获取拓展类，如果没有自适应的拓展类，那么就需要调用createAdaptiveExtensionClass
+        getExtensionClasses();
+        if (cachedAdaptiveClass != null) {
+            return cachedAdaptiveClass;
+        }
+        return cachedAdaptiveClass = createAdaptiveExtensionClass();
+    }
+private Class<?> createAdaptiveExtensionClass() {
+  			// 这里去生成了自适应拓展的代码，具体生成逻辑比较复杂先不展开讲
+        String code = createAdaptiveExtensionClassCode();
+        ClassLoader classLoader = findClassLoader();
+        com.alibaba.dubbo.common.compiler.Compiler compiler = ExtensionLoader.getExtensionLoader(com.alibaba.dubbo.common.compiler.Compiler.class).getAdaptiveExtension();
+        return compiler.compile(code, classLoader);
+    }

      生成的代码像这样

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      package com.alibaba.dubbo.rpc;

      import com.alibaba.dubbo.common.extension.ExtensionLoader;


      public class Protocol$Adaptive implements com.alibaba.dubbo.rpc.Protocol {
          public void destroy() {
              throw new UnsupportedOperationException(
                  "method public abstract void com.alibaba.dubbo.rpc.Protocol.destroy() of interface com.alibaba.dubbo.rpc.Protocol is not adaptive method!");
          }

          public int getDefaultPort() {
              throw new UnsupportedOperationException(
                  "method public abstract int com.alibaba.dubbo.rpc.Protocol.getDefaultPort() of interface com.alibaba.dubbo.rpc.Protocol is not adaptive method!");
          }

          public com.alibaba.dubbo.rpc.Exporter export(
              com.alibaba.dubbo.rpc.Invoker arg0)
              throws com.alibaba.dubbo.rpc.RpcException {
              if (arg0 == null) {
                  throw new IllegalArgumentException(
                      "com.alibaba.dubbo.rpc.Invoker argument == null");
              }

              if (arg0.getUrl() == null) {
                  throw new IllegalArgumentException(
                      "com.alibaba.dubbo.rpc.Invoker argument getUrl() == null");
              }

              com.alibaba.dubbo.common.URL url = arg0.getUrl();
              String extName = ((url.getProtocol() == null) ? "dubbo"
                                                            : url.getProtocol());

              if (extName == null) {
                  throw new IllegalStateException(
                      "Fail to get extension(com.alibaba.dubbo.rpc.Protocol) name from url(" +
                      url.toString() + ") use keys([protocol])");
              }

              com.alibaba.dubbo.rpc.Protocol extension = (com.alibaba.dubbo.rpc.Protocol) ExtensionLoader.getExtensionLoader(com.alibaba.dubbo.rpc.Protocol.class)
                                                                                                         .getExtension(extName);

              return extension.export(arg0);
          }

          public com.alibaba.dubbo.rpc.Invoker refer(java.lang.Class arg0,
              com.alibaba.dubbo.common.URL arg1)
              throws com.alibaba.dubbo.rpc.RpcException {
              if (arg1 == null) {
                  throw new IllegalArgumentException("url == null");
              }

              com.alibaba.dubbo.common.URL url = arg1;
            // 其实前面所说的逻辑就在这里呈现了
              String extName = ((url.getProtocol() == null) ? "dubbo"
                                                            : url.getProtocol());

              if (extName == null) {
                  throw new IllegalStateException(
                      "Fail to get extension(com.alibaba.dubbo.rpc.Protocol) name from url(" +
                      url.toString() + ") use keys([protocol])");
              }
      				// 在这就是实际的通过dubbo 的 spi 去加载实际对应的扩展
              com.alibaba.dubbo.rpc.Protocol extension = (com.alibaba.dubbo.rpc.Protocol) ExtensionLoader.getExtensionLoader(com.alibaba.dubbo.rpc.Protocol.class)
                                                                                                         .getExtension(extName);

              return extension.refer(arg0, arg1);
          }
      }
      +
      package com.alibaba.dubbo.rpc;
+
+import com.alibaba.dubbo.common.extension.ExtensionLoader;
+
+
+public class Protocol$Adaptive implements com.alibaba.dubbo.rpc.Protocol {
+    public void destroy() {
+        throw new UnsupportedOperationException(
+            "method public abstract void com.alibaba.dubbo.rpc.Protocol.destroy() of interface com.alibaba.dubbo.rpc.Protocol is not adaptive method!");
+    }
+
+    public int getDefaultPort() {
+        throw new UnsupportedOperationException(
+            "method public abstract int com.alibaba.dubbo.rpc.Protocol.getDefaultPort() of interface com.alibaba.dubbo.rpc.Protocol is not adaptive method!");
+    }
+
+    public com.alibaba.dubbo.rpc.Exporter export(
+        com.alibaba.dubbo.rpc.Invoker arg0)
+        throws com.alibaba.dubbo.rpc.RpcException {
+        if (arg0 == null) {
+            throw new IllegalArgumentException(
+                "com.alibaba.dubbo.rpc.Invoker argument == null");
+        }
+
+        if (arg0.getUrl() == null) {
+            throw new IllegalArgumentException(
+                "com.alibaba.dubbo.rpc.Invoker argument getUrl() == null");
+        }
+
+        com.alibaba.dubbo.common.URL url = arg0.getUrl();
+        String extName = ((url.getProtocol() == null) ? "dubbo"
+                                                      : url.getProtocol());
+
+        if (extName == null) {
+            throw new IllegalStateException(
+                "Fail to get extension(com.alibaba.dubbo.rpc.Protocol) name from url(" +
+                url.toString() + ") use keys([protocol])");
+        }
+
+        com.alibaba.dubbo.rpc.Protocol extension = (com.alibaba.dubbo.rpc.Protocol) ExtensionLoader.getExtensionLoader(com.alibaba.dubbo.rpc.Protocol.class)
+                                                                                                   .getExtension(extName);
+
+        return extension.export(arg0);
+    }
+
+    public com.alibaba.dubbo.rpc.Invoker refer(java.lang.Class arg0,
+        com.alibaba.dubbo.common.URL arg1)
+        throws com.alibaba.dubbo.rpc.RpcException {
+        if (arg1 == null) {
+            throw new IllegalArgumentException("url == null");
+        }
+
+        com.alibaba.dubbo.common.URL url = arg1;
+      // 其实前面所说的逻辑就在这里呈现了
+        String extName = ((url.getProtocol() == null) ? "dubbo"
+                                                      : url.getProtocol());
+
+        if (extName == null) {
+            throw new IllegalStateException(
+                "Fail to get extension(com.alibaba.dubbo.rpc.Protocol) name from url(" +
+                url.toString() + ") use keys([protocol])");
+        }
+				// 在这就是实际的通过dubbo 的 spi 去加载实际对应的扩展
+        com.alibaba.dubbo.rpc.Protocol extension = (com.alibaba.dubbo.rpc.Protocol) ExtensionLoader.getExtensionLoader(com.alibaba.dubbo.rpc.Protocol.class)
+                                                                                                   .getExtension(extName);
+
+        return extension.refer(arg0, arg1);
+    }
+}
+
      @@ -332,7 +446,7 @@
      聊聊 dubbo 的线程池
    • -
      聊聊我刚学会的应用诊断方法
      +
      Maven实用小技巧
    • mybatis 的 $ 和 # 是有啥区别
      diff --git a/2020/06/13/聊聊一次-brew-update-引发的血案/index.html b/2020/06/13/聊聊一次-brew-update-引发的血案/index.html index 54b42ad6ec..8ac639bc50 100644 --- a/2020/06/13/聊聊一次-brew-update-引发的血案/index.html +++ b/2020/06/13/聊聊一次-brew-update-引发的血案/index.html @@ -4,7 +4,7 @@ - + @@ -32,9 +32,10 @@ + - + @@ -231,9 +232,8 @@ Posted on - - + @@ -297,27 +297,38 @@

      熟悉我的人（谁熟悉你啊🙄）知道我以前写过 PHP，虽然现在在工作中没用到了，但是自己的一些小工具还是会用 PHP 来写，但是在 Mac 碰到了一个环境相关的问题，因为我也是个更新狂魔，用了 brew 之后因为 gfw 的原因，如果长时间不更新，有时候要装一个用它装一个软件的话，前置的更新耗时就会让人非常头大，所以我基本会隔天 update 一下，但是这样会带来一个很心烦的问题，就是像这样，因为我是要用一个固定版本的 PHP，如果一直升需要一直配扩展啥的也很麻烦，如果一直升级 PHP 到最新版可能会比较少碰到这个问题

      -
      1
      dyld: Library not loaded: /usr/local/opt/icu4c/lib/libicui18n.64.dylib
      +
      dyld: Library not loaded: /usr/local/opt/icu4c/lib/libicui18n.64.dylib

      这是什么鬼啊，然后我去这个目录下看了下，已经都是libicui18n.67.dylib了，而且它没有把原来的版本保留下来，首先这个是个叫 icu4c是啥玩意，谷歌了一下

      ICU4C是ICU在C/C++平台下的版本, ICU(International Component for Unicode)是基于”IBM公共许可证”的，与开源组织合作研究的, 用于支持软件国际化的开源项目。ICU4C提供了C/C++平台强大的国际化开发能力，软件开发者几乎可以使用ICU4C解决任何国际化的问题，根据各地的风俗和语言习惯，实现对数字、货币、时间、日期、和消息的格式化、解析，对字符串进行大小写转换、整理、搜索和排序等功能，必须一提的是，ICU4C提供了强大的BIDI算法，对阿拉伯语等BIDI语言提供了完善的支持。

      然后首先想到的解决方案就是能不能我使用brew install icu4c@64来重装下原来的版本，发现不行，并木有，之前的做法就只能是去网上把 64 的下载下来，然后放到这个目录，比较麻烦不智能，虽然没抱着希望在谷歌着，不过这次竟然给我找到了一个我认为非常 nice 的解决方案，因为是在 Stack Overflow 找到的，本着写给像我这样的小小白看的，那就稍微翻译一下
      第一步，我们到 brew的目录下

      -
      1
      cd $(brew --prefix)/Homebrew/Library/Taps/homebrew/homebrew-core/Formula
      +
      cd $(brew --prefix)/Homebrew/Library/Taps/homebrew/homebrew-core/Formula

      这个可以理解为是 maven 的 pom 文件，不过有很多不同之处，使用ruby 写的，然后一个文件对应一个组件或者软件，那我们看下有个叫icu4c.rb的文件，
      第二步看看它的提交历史

      -
      1
      git log --follow icu4c.rb
      -

      在 git log 的海洋中寻找，寻找它的(64版本)的身影

      第三步注意这三个红框，Stack Overflow 给出来的答案这一步是找到这个 commit id 直接切出一个新分支

      -
      1
      git checkout -b icu4c-63 e7f0f10dc63b1dc1061d475f1a61d01b70ef2cb7
      +
      git log --follow icu4c.rb
      +

      在 git log 的海洋中寻找，寻找它的(64版本)的身影

      第三步注意这三个红框，Stack Overflow 给出来的答案这一步是找到这个 commit id 直接切出一个新分支

      +
      git checkout -b icu4c-63 e7f0f10dc63b1dc1061d475f1a61d01b70ef2cb7

      其实注意 commit id 旁边的红框，这个是有tag 的，可以直接

      -
      1
      git checkout icu4c-64
      +
      git checkout icu4c-64

      PS: 因为我的问题是出在 64 的问题，Stack Overflow 回答的是 63 的，反正是一样的解决方法
      第四部，切回去之后我们就可以用 brew 提供的基于文件的安装命令来重新装上 64 版本

      -
      1
      brew reinstall ./icu4c.rb
      +
      brew reinstall ./icu4c.rb

      然后就是第五步，切换版本

      -
      1
      brew switch icu4c 64.2
      +
      brew switch icu4c 64.2

      最后把分支切回来

      -
      1
      git checkout master
      +
      git checkout master

      是不是感觉很厉害的解决方法，大佬还提供了一个更牛的，直接写个 zsh 方法

      -
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      # zsh
      function hiicu64() {
        local last_dir=$(pwd)

        cd $(brew --prefix)/Homebrew/Library/Taps/homebrew/homebrew-core/Formula
        git checkout icu4c-4
        brew reinstall ./icu4c.rb
        brew switch icu4c 64.2
        git checkout master

        cd $last_dir
      }
      +
      # zsh
+function hiicu64() {
+  local last_dir=$(pwd)
+
+  cd $(brew --prefix)/Homebrew/Library/Taps/homebrew/homebrew-core/Formula
+  git checkout icu4c-4
+  brew reinstall ./icu4c.rb
+  brew switch icu4c 64.2
+  git checkout master
+
+  cd $last_dir
+}

      对应自己的版本改改版本号就可以了，非常好用。

      diff --git a/2020/06/21/介绍一下-RocketMQ/index.html b/2020/06/21/介绍一下-RocketMQ/index.html index f03d3952a9..b250898eab 100644 --- a/2020/06/21/介绍一下-RocketMQ/index.html +++ b/2020/06/21/介绍一下-RocketMQ/index.html @@ -4,7 +4,7 @@ - + @@ -32,9 +32,10 @@ + - + @@ -231,9 +232,8 @@       Posted on - - +       @@ -304,7 +304,7 @@
      -

      说起消息队列一般Web后端做过一段时间开发的肯定会用过，在前司的时候用的是改良版的 NSQ，有点像 NOSQL 的简写版🙄，其实是个go 语言写的消息队列，nsq 看代码提交感觉最近更新的不是很勤，不过因为前司有专门的中间件团队，所以还是挺好用的，而且中间件团队的大牛也很厉害，一次都没碰到过丢消息之类的错误，然后现在公司用的是 RocketMQ，本着总还是要了解下的，并且消息队列也是服务端开发中一个很重要的中间件，因为不太有不需要用消息队列的后端团队了吧，原来对 nsq 也不是特别了解原理，就打算了解下 RocketMQ。

      +

      说起消息队列一般Web后端做过一段时间开发的肯定会用过，在前司的时候用的是改良版的 NSQ，有点像 NOSQL 的简写版🙄，其实是个go 语言写的消息队列，nsq 看代码提交感觉最近更新的不是很勤，不过因为前司有专门的中间件团队，所以还是挺好用的，而且中间件团队的大牛也很厉害，一次都没碰到过丢消息之类的错误，然后现在公司用的是 RocketMQ，本着总还是要了解下的，并且消息队列也是服务端开发中一个很重要的中间件，因为不太有不需要用消息队列的后端团队了吧，原来对 nsq 也不是特别了解原理，就打算了解下 RocketMQ。

      还是像我这样的小白专属，消息队列用来干啥，很多都是标准答案，用来削峰填谷的，这个完全对，只是我想结合场景说给像我这样的小白同学听，想想一个电商的下单功能，除了 AT 两家之外应该大部分都是接入的支付，那么下单支付完成后一般都是等支付回调，告诉你支付完成了（也有可能是失败了，或者超时了咱们主动去查），然后这个回调里我们自己的业务代码干点啥，首先比如是把订单状态改掉了，然后会有各类的操作，比如把优惠券核销了，把其他金钱相关的也核销了，把购物车里对应的商品给删了，还有更次要的，比如发个客服消息，让用户确认下地址的，给用户加积分的等等等等，想象下如果这些都是回调里一股脑儿做掉了，那可能你的代码健壮性跟相关服务的稳定性还有性能要达到一个非常高的水平才能让业务不出现异常，并且万一流量打起来了，这些重要的不重要的操作都会阻塞着，所以需要用一个消息队列，在接到回调后只处理极少的几个核心操作，完了就把这个消息丢进消息队列里，让各个业务方去消费这个消息，把客服消息发一下，给用户加个积分等等，这样子主要的业务流程需要处理的事情就少了，速度也加快了，这个例子呢不能严格算是削峰填谷的例子，不过也算是消息队列的比较典型的使用场景了，要说真实的削峰填谷的话其实可以这么理解，假如短时间内有 1w 个请求进来，系统能支持的 QPS 才 1000，那么正常情况下服务就挂了，或者被限流了，为了让服务正常，那么可以把这些请求先放进消息队列里，我服务端以拉的模式按我的处理能力来消费，这样就没啥问题了

      扯了这么多来聊聊 RocketMQ 长啥样

      6073827-a998e005dd13967c

      @@ -498,7 +498,7 @@
      -
      1. 1. NameServer
      2. 2. Broker
        1. 2.0.1. Broker的特点
    • 3. Producer
      1. 3.0.1. 生产者端的负载均衡
    • 4. Consumer
      1. 4.0.1. 消费者端的负载均衡
    • 5. 补充一些概念
      • +
      1. 1. NameServer
      2. 2. Broker
        1. 2.0.1. Broker的特点
    • 3. Producer
      1. 3.0.1. 生产者端的负载均衡
    • 4. Consumer
      1. 4.0.1. 消费者端的负载均衡
    • 5. 补充一些概念
      • diff --git a/2020/06/26/聊一下-RocketMQ-的-Consumer/index.html b/2020/06/26/聊一下-RocketMQ-的-Consumer/index.html index 663189e1e6..6b724a7681 100644 --- a/2020/06/26/聊一下-RocketMQ-的-Consumer/index.html +++ b/2020/06/26/聊一下-RocketMQ-的-Consumer/index.html @@ -4,7 +4,7 @@ - + @@ -26,23 +26,24 @@ var CONFIG = {"hostname":"nicksxs.me","root":"/","scheme":"Pisces","version":"7.8.0","exturl":false,"sidebar":{"position":"left","display":"post","padding":18,"offset":12,"onmobile":false},"copycode":{"enable":true,"show_result":false,"style":null},"back2top":{"enable":true,"sidebar":false,"scrollpercent":false},"bookmark":{"enable":false,"color":"#222","save":"auto"},"fancybox":true,"mediumzoom":false,"lazyload":true,"pangu":false,"comments":{"style":"tabs","active":null,"storage":true,"lazyload":false,"nav":null},"algolia":{"hits":{"per_page":10},"labels":{"input_placeholder":"Search for Posts","hits_empty":"We didn't find any results for the search: ${query}","hits_stats":"${hits} results found in ${time} ms"}},"localsearch":{"enable":false,"trigger":"auto","top_n_per_article":1,"unescape":false,"preload":false},"motion":{"enable":true,"async":false,"transition":{"post_block":"fadeIn","post_header":"slideDownIn","post_body":"slideDownIn","coll_header":"slideLeftIn","sidebar":"slideUpIn"}}}; - + - + + - + - + @@ -236,13 +237,6 @@       - - - - - Edited on - - @@ -313,34 +307,773 @@

      首先看下官方的小 demo

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      public static void main(String[] args) throws InterruptedException, MQClientException {

              /*
               * Instantiate with specified consumer group name.
               * 首先是new 一个对象出来，然后指定 Consumer 的 Group
               * 同一类Consumer的集合，这类Consumer通常消费同一类消息且消费逻辑一致。消费者组使得在消息消费方面，实现负载均衡和容错的目标变得非常容易。要注意的是，消费者组的消费者实例必须订阅完全相同的Topic。RocketMQ 支持两种消息模式：集群消费（Clustering）和广播消费（Broadcasting）。
               */
              DefaultMQPushConsumer consumer = new DefaultMQPushConsumer("please_rename_unique_group_name_4");

              /*
               * Specify name server addresses.
               * <p/>
               * 这里可以通知指定环境变量或者设置对象参数的形式指定名字空间服务的地址
               *
               * Alternatively, you may specify name server addresses via exporting environmental variable: NAMESRV_ADDR
               * <pre>
               * {@code
               * consumer.setNamesrvAddr("name-server1-ip:9876;name-server2-ip:9876");
               * }
               * </pre>
               */

              /*
               * Specify where to start in case the specified consumer group is a brand new one.
               * 指定消费起始点
               */
              consumer.setConsumeFromWhere(ConsumeFromWhere.CONSUME_FROM_FIRST_OFFSET);

              /*
               * Subscribe one more more topics to consume.
               * 指定订阅的 topic 跟 tag，注意后面的是个表达式，可以以 tag1 || tag2 || tag3 传入
               */
              consumer.subscribe("TopicTest", "*");

              /*
               *  Register callback to execute on arrival of messages fetched from brokers.
               *  注册具体获得消息后的处理方法
               */
              consumer.registerMessageListener(new MessageListenerConcurrently() {

                  @Override
                  public ConsumeConcurrentlyStatus consumeMessage(List<MessageExt> msgs,
                      ConsumeConcurrentlyContext context) {
                      System.out.printf("%s Receive New Messages: %s %n", Thread.currentThread().getName(), msgs);
                      return ConsumeConcurrentlyStatus.CONSUME_SUCCESS;
                  }
              });

              /*
               *  Launch the consumer instance.
               * 启动消费者
               */
              consumer.start();

              System.out.printf("Consumer Started.%n");
          }
      +
      public static void main(String[] args) throws InterruptedException, MQClientException {
+
+        /*
+         * Instantiate with specified consumer group name.
+         * 首先是new 一个对象出来，然后指定 Consumer 的 Group
+         * 同一类Consumer的集合，这类Consumer通常消费同一类消息且消费逻辑一致。消费者组使得在消息消费方面，实现负载均衡和容错的目标变得非常容易。要注意的是，消费者组的消费者实例必须订阅完全相同的Topic。RocketMQ 支持两种消息模式：集群消费（Clustering）和广播消费（Broadcasting）。
+         */
+        DefaultMQPushConsumer consumer = new DefaultMQPushConsumer("please_rename_unique_group_name_4");
+
+        /*
+         * Specify name server addresses.
+         * <p/>
+         * 这里可以通知指定环境变量或者设置对象参数的形式指定名字空间服务的地址
+         *
+         * Alternatively, you may specify name server addresses via exporting environmental variable: NAMESRV_ADDR
+         * <pre>
+         * {@code
+         * consumer.setNamesrvAddr("name-server1-ip:9876;name-server2-ip:9876");
+         * }
+         * </pre>
+         */
+
+        /*
+         * Specify where to start in case the specified consumer group is a brand new one.
+         * 指定消费起始点
+         */
+        consumer.setConsumeFromWhere(ConsumeFromWhere.CONSUME_FROM_FIRST_OFFSET);
+
+        /*
+         * Subscribe one more more topics to consume.
+         * 指定订阅的 topic 跟 tag，注意后面的是个表达式，可以以 tag1 || tag2 || tag3 传入
+         */
+        consumer.subscribe("TopicTest", "*");
+
+        /*
+         *  Register callback to execute on arrival of messages fetched from brokers.
+         *  注册具体获得消息后的处理方法
+         */
+        consumer.registerMessageListener(new MessageListenerConcurrently() {
+
+            @Override
+            public ConsumeConcurrentlyStatus consumeMessage(List<MessageExt> msgs,
+                ConsumeConcurrentlyContext context) {
+                System.out.printf("%s Receive New Messages: %s %n", Thread.currentThread().getName(), msgs);
+                return ConsumeConcurrentlyStatus.CONSUME_SUCCESS;
+            }
+        });
+
+        /*
+         *  Launch the consumer instance.
+         * 启动消费者
+         */
+        consumer.start();
+
+        System.out.printf("Consumer Started.%n");
+    }

      然后就是看看 start 的过程了

      -
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      /**
           * This method gets internal infrastructure readily to serve. Instances must call this method after configuration.
           *
           * @throws MQClientException if there is any client error.
           */
          @Override
          public void start() throws MQClientException {
              setConsumerGroup(NamespaceUtil.wrapNamespace(this.getNamespace(), this.consumerGroup));
              this.defaultMQPushConsumerImpl.start();
              if (null != traceDispatcher) {
                  try {
                      traceDispatcher.start(this.getNamesrvAddr(), this.getAccessChannel());
                  } catch (MQClientException e) {
                      log.warn("trace dispatcher start failed ", e);
                  }
              }
          }
      +
      /**
+     * This method gets internal infrastructure readily to serve. Instances must call this method after configuration.
+     *
+     * @throws MQClientException if there is any client error.
+     */
+    @Override
+    public void start() throws MQClientException {
+        setConsumerGroup(NamespaceUtil.wrapNamespace(this.getNamespace(), this.consumerGroup));
+        this.defaultMQPushConsumerImpl.start();
+        if (null != traceDispatcher) {
+            try {
+                traceDispatcher.start(this.getNamesrvAddr(), this.getAccessChannel());
+            } catch (MQClientException e) {
+                log.warn("trace dispatcher start failed ", e);
+            }
+        }
+    }

      具体的逻辑在this.defaultMQPushConsumerImpl.start()，这个 defaultMQPushConsumerImpl 就是

      -
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      /**
           * Internal implementation. Most of the functions herein are delegated to it.
           */
          protected final transient DefaultMQPushConsumerImpl defaultMQPushConsumerImpl;
      - -
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      public synchronized void start() throws MQClientException {
              switch (this.serviceState) {
                  case CREATE_JUST:
                      log.info("the consumer [{}] start beginning. messageModel={}, isUnitMode={}", this.defaultMQPushConsumer.getConsumerGroup(),
                          this.defaultMQPushConsumer.getMessageModel(), this.defaultMQPushConsumer.isUnitMode());
                      // 这里比较巧妙，相当于想设立了个屏障，防止并发启动，不过这里并不是悲观锁，也不算个严格的乐观锁
                      this.serviceState = ServiceState.START_FAILED;

                      this.checkConfig();

                      this.copySubscription();

                      if (this.defaultMQPushConsumer.getMessageModel() == MessageModel.CLUSTERING) {
                          this.defaultMQPushConsumer.changeInstanceNameToPID();
                      }

                      // 这个mQClientFactory，负责管理client（consumer、producer），并提供多中功能接口供各个Service（Rebalance、PullMessage等）调用；大部分逻辑均在这个类中完成
                      this.mQClientFactory = MQClientManager.getInstance().getOrCreateMQClientInstance(this.defaultMQPushConsumer, this.rpcHook);

                      // 这个 rebalanceImpl 主要负责决定，当前的consumer应该从哪些Queue中消费消息；
                      this.rebalanceImpl.setConsumerGroup(this.defaultMQPushConsumer.getConsumerGroup());
                      this.rebalanceImpl.setMessageModel(this.defaultMQPushConsumer.getMessageModel());
                      this.rebalanceImpl.setAllocateMessageQueueStrategy(this.defaultMQPushConsumer.getAllocateMessageQueueStrategy());
                      this.rebalanceImpl.setmQClientFactory(this.mQClientFactory);

                      // 长连接，负责从broker处拉取消息，然后利用ConsumeMessageService回调用户的Listener执行消息消费逻辑
                      this.pullAPIWrapper = new PullAPIWrapper(
                          mQClientFactory,
                          this.defaultMQPushConsumer.getConsumerGroup(), isUnitMode());
                      this.pullAPIWrapper.registerFilterMessageHook(filterMessageHookList);

                      if (this.defaultMQPushConsumer.getOffsetStore() != null) {
                          this.offsetStore = this.defaultMQPushConsumer.getOffsetStore();
                      } else {
                          switch (this.defaultMQPushConsumer.getMessageModel()) {
                              case BROADCASTING:
                                  this.offsetStore = new LocalFileOffsetStore(this.mQClientFactory, this.defaultMQPushConsumer.getConsumerGroup());
                                  break;
                              case CLUSTERING:
                                  this.offsetStore = new RemoteBrokerOffsetStore(this.mQClientFactory, this.defaultMQPushConsumer.getConsumerGroup());
                                  break;
                              default:
                                  break;
                          }
                          this.defaultMQPushConsumer.setOffsetStore(this.offsetStore);
                      }
                      // offsetStore 维护当前consumer的消费记录（offset）；有两种实现，Local和Rmote，Local存储在本地磁盘上，适用于BROADCASTING广播消费模式；而Remote则将消费进度存储在Broker上，适用于CLUSTERING集群消费模式；
                      this.offsetStore.load();

                      if (this.getMessageListenerInner() instanceof MessageListenerOrderly) {
                          this.consumeOrderly = true;
                          this.consumeMessageService =
                              new ConsumeMessageOrderlyService(this, (MessageListenerOrderly) this.getMessageListenerInner());
                      } else if (this.getMessageListenerInner() instanceof MessageListenerConcurrently) {
                          this.consumeOrderly = false;
                          this.consumeMessageService =
                              new ConsumeMessageConcurrentlyService(this, (MessageListenerConcurrently) this.getMessageListenerInner());
                      }

                      // 实现所谓的"Push-被动"消费机制；从Broker拉取的消息后，封装成ConsumeRequest提交给ConsumeMessageSerivce，此service负责回调用户的Listener消费消息；
                      this.consumeMessageService.start();

                      boolean registerOK = mQClientFactory.registerConsumer(this.defaultMQPushConsumer.getConsumerGroup(), this);
                      if (!registerOK) {
                          this.serviceState = ServiceState.CREATE_JUST;
                          this.consumeMessageService.shutdown();
                          throw new MQClientException("The consumer group[" + this.defaultMQPushConsumer.getConsumerGroup()
                              + "] has been created before, specify another name please." + FAQUrl.suggestTodo(FAQUrl.GROUP_NAME_DUPLICATE_URL),
                              null);
                      }

                      mQClientFactory.start();
                      log.info("the consumer [{}] start OK.", this.defaultMQPushConsumer.getConsumerGroup());
                      this.serviceState = ServiceState.RUNNING;
                      break;
                  case RUNNING:
                  case START_FAILED:
                  case SHUTDOWN_ALREADY:
                      throw new MQClientException("The PushConsumer service state not OK, maybe started once, "
                          + this.serviceState
                          + FAQUrl.suggestTodo(FAQUrl.CLIENT_SERVICE_NOT_OK),
                          null);
                  default:
                      break;
              }

              this.updateTopicSubscribeInfoWhenSubscriptionChanged();
              this.mQClientFactory.checkClientInBroker();
              this.mQClientFactory.sendHeartbeatToAllBrokerWithLock();
              this.mQClientFactory.rebalanceImmediately();
          }
      +
      /**
+     * Internal implementation. Most of the functions herein are delegated to it.
+     */
+    protected final transient DefaultMQPushConsumerImpl defaultMQPushConsumerImpl;
      + +
      public synchronized void start() throws MQClientException {
+        switch (this.serviceState) {
+            case CREATE_JUST:
+                log.info("the consumer [{}] start beginning. messageModel={}, isUnitMode={}", this.defaultMQPushConsumer.getConsumerGroup(),
+                    this.defaultMQPushConsumer.getMessageModel(), this.defaultMQPushConsumer.isUnitMode());
+                // 这里比较巧妙，相当于想设立了个屏障，防止并发启动，不过这里并不是悲观锁，也不算个严格的乐观锁
+                this.serviceState = ServiceState.START_FAILED;
+
+                this.checkConfig();
+
+                this.copySubscription();
+
+                if (this.defaultMQPushConsumer.getMessageModel() == MessageModel.CLUSTERING) {
+                    this.defaultMQPushConsumer.changeInstanceNameToPID();
+                }
+
+                // 这个mQClientFactory，负责管理client（consumer、producer），并提供多中功能接口供各个Service（Rebalance、PullMessage等）调用；大部分逻辑均在这个类中完成
+                this.mQClientFactory = MQClientManager.getInstance().getOrCreateMQClientInstance(this.defaultMQPushConsumer, this.rpcHook);
+
+                // 这个 rebalanceImpl 主要负责决定，当前的consumer应该从哪些Queue中消费消息；
+                this.rebalanceImpl.setConsumerGroup(this.defaultMQPushConsumer.getConsumerGroup());
+                this.rebalanceImpl.setMessageModel(this.defaultMQPushConsumer.getMessageModel());
+                this.rebalanceImpl.setAllocateMessageQueueStrategy(this.defaultMQPushConsumer.getAllocateMessageQueueStrategy());
+                this.rebalanceImpl.setmQClientFactory(this.mQClientFactory);
+
+                // 长连接，负责从broker处拉取消息，然后利用ConsumeMessageService回调用户的Listener执行消息消费逻辑
+                this.pullAPIWrapper = new PullAPIWrapper(
+                    mQClientFactory,
+                    this.defaultMQPushConsumer.getConsumerGroup(), isUnitMode());
+                this.pullAPIWrapper.registerFilterMessageHook(filterMessageHookList);
+
+                if (this.defaultMQPushConsumer.getOffsetStore() != null) {
+                    this.offsetStore = this.defaultMQPushConsumer.getOffsetStore();
+                } else {
+                    switch (this.defaultMQPushConsumer.getMessageModel()) {
+                        case BROADCASTING:
+                            this.offsetStore = new LocalFileOffsetStore(this.mQClientFactory, this.defaultMQPushConsumer.getConsumerGroup());
+                            break;
+                        case CLUSTERING:
+                            this.offsetStore = new RemoteBrokerOffsetStore(this.mQClientFactory, this.defaultMQPushConsumer.getConsumerGroup());
+                            break;
+                        default:
+                            break;
+                    }
+                    this.defaultMQPushConsumer.setOffsetStore(this.offsetStore);
+                }
+                // offsetStore 维护当前consumer的消费记录（offset）；有两种实现，Local和Rmote，Local存储在本地磁盘上，适用于BROADCASTING广播消费模式；而Remote则将消费进度存储在Broker上，适用于CLUSTERING集群消费模式；
+                this.offsetStore.load();
+
+                if (this.getMessageListenerInner() instanceof MessageListenerOrderly) {
+                    this.consumeOrderly = true;
+                    this.consumeMessageService =
+                        new ConsumeMessageOrderlyService(this, (MessageListenerOrderly) this.getMessageListenerInner());
+                } else if (this.getMessageListenerInner() instanceof MessageListenerConcurrently) {
+                    this.consumeOrderly = false;
+                    this.consumeMessageService =
+                        new ConsumeMessageConcurrentlyService(this, (MessageListenerConcurrently) this.getMessageListenerInner());
+                }
+
+                // 实现所谓的"Push-被动"消费机制；从Broker拉取的消息后，封装成ConsumeRequest提交给ConsumeMessageSerivce，此service负责回调用户的Listener消费消息；
+                this.consumeMessageService.start();
+
+                boolean registerOK = mQClientFactory.registerConsumer(this.defaultMQPushConsumer.getConsumerGroup(), this);
+                if (!registerOK) {
+                    this.serviceState = ServiceState.CREATE_JUST;
+                    this.consumeMessageService.shutdown();
+                    throw new MQClientException("The consumer group[" + this.defaultMQPushConsumer.getConsumerGroup()
+                        + "] has been created before, specify another name please." + FAQUrl.suggestTodo(FAQUrl.GROUP_NAME_DUPLICATE_URL),
+                        null);
+                }
+
+                mQClientFactory.start();
+                log.info("the consumer [{}] start OK.", this.defaultMQPushConsumer.getConsumerGroup());
+                this.serviceState = ServiceState.RUNNING;
+                break;
+            case RUNNING:
+            case START_FAILED:
+            case SHUTDOWN_ALREADY:
+                throw new MQClientException("The PushConsumer service state not OK, maybe started once, "
+                    + this.serviceState
+                    + FAQUrl.suggestTodo(FAQUrl.CLIENT_SERVICE_NOT_OK),
+                    null);
+            default:
+                break;
+        }
+
+        this.updateTopicSubscribeInfoWhenSubscriptionChanged();
+        this.mQClientFactory.checkClientInBroker();
+        this.mQClientFactory.sendHeartbeatToAllBrokerWithLock();
+        this.mQClientFactory.rebalanceImmediately();
+    }

      然后我们往下看主要的目光聚焦mQClientFactory.start()

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      public void start() throws MQClientException {

              synchronized (this) {
                  switch (this.serviceState) {
                      case CREATE_JUST:
                          this.serviceState = ServiceState.START_FAILED;
                          // If not specified,looking address from name server
                          if (null == this.clientConfig.getNamesrvAddr()) {
                              this.mQClientAPIImpl.fetchNameServerAddr();
                          }
                          // Start request-response channel
                          // 这里主要是初始化了个网络客户端
                          this.mQClientAPIImpl.start();
                          // Start various schedule tasks
                          // 定时任务
                          this.startScheduledTask();
                          // Start pull service
                          // 这里重点说下
                          this.pullMessageService.start();
                          // Start rebalance service
                          this.rebalanceService.start();
                          // Start push service
                          this.defaultMQProducer.getDefaultMQProducerImpl().start(false);
                          log.info("the client factory [{}] start OK", this.clientId);
                          this.serviceState = ServiceState.RUNNING;
                          break;
                      case START_FAILED:
                          throw new MQClientException("The Factory object[" + this.getClientId() + "] has been created before, and failed.", null);
                      default:
                          break;
                  }
              }
          }
      -

      我们来看下这个 pullMessageService，org.apache.rocketmq.client.impl.consumer.PullMessageService，

      实现了 runnable 接口，
      然后可以看到 run 方法

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      public void run() {
              log.info(this.getServiceName() + " service started");

              while (!this.isStopped()) {
                  try {
                      PullRequest pullRequest = this.pullRequestQueue.take();
                      this.pullMessage(pullRequest);
                  } catch (InterruptedException ignored) {
                  } catch (Exception e) {
                      log.error("Pull Message Service Run Method exception", e);
                  }
              }

              log.info(this.getServiceName() + " service end");
          }
      +
      public void start() throws MQClientException {
+
+        synchronized (this) {
+            switch (this.serviceState) {
+                case CREATE_JUST:
+                    this.serviceState = ServiceState.START_FAILED;
+                    // If not specified,looking address from name server
+                    if (null == this.clientConfig.getNamesrvAddr()) {
+                        this.mQClientAPIImpl.fetchNameServerAddr();
+                    }
+                    // Start request-response channel
+                    // 这里主要是初始化了个网络客户端
+                    this.mQClientAPIImpl.start();
+                    // Start various schedule tasks
+                    // 定时任务
+                    this.startScheduledTask();
+                    // Start pull service
+                    // 这里重点说下
+                    this.pullMessageService.start();
+                    // Start rebalance service
+                    this.rebalanceService.start();
+                    // Start push service
+                    this.defaultMQProducer.getDefaultMQProducerImpl().start(false);
+                    log.info("the client factory [{}] start OK", this.clientId);
+                    this.serviceState = ServiceState.RUNNING;
+                    break;
+                case START_FAILED:
+                    throw new MQClientException("The Factory object[" + this.getClientId() + "] has been created before, and failed.", null);
+                default:
+                    break;
+            }
+        }
+    }
      +

      我们来看下这个 pullMessageService，org.apache.rocketmq.client.impl.consumer.PullMessageService，

      实现了 runnable 接口，
      然后可以看到 run 方法

      +
      public void run() {
+        log.info(this.getServiceName() + " service started");
+
+        while (!this.isStopped()) {
+            try {
+                PullRequest pullRequest = this.pullRequestQueue.take();
+                this.pullMessage(pullRequest);
+            } catch (InterruptedException ignored) {
+            } catch (Exception e) {
+                log.error("Pull Message Service Run Method exception", e);
+            }
+        }
+
+        log.info(this.getServiceName() + " service end");
+    }

      接着在看 pullMessage 方法

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      private void pullMessage(final PullRequest pullRequest) {
              final MQConsumerInner consumer = this.mQClientFactory.selectConsumer(pullRequest.getConsumerGroup());
              if (consumer != null) {
                  DefaultMQPushConsumerImpl impl = (DefaultMQPushConsumerImpl) consumer;
                  impl.pullMessage(pullRequest);
              } else {
                  log.warn("No matched consumer for the PullRequest {}, drop it", pullRequest);
              }
          }
      +
      private void pullMessage(final PullRequest pullRequest) {
+        final MQConsumerInner consumer = this.mQClientFactory.selectConsumer(pullRequest.getConsumerGroup());
+        if (consumer != null) {
+            DefaultMQPushConsumerImpl impl = (DefaultMQPushConsumerImpl) consumer;
+            impl.pullMessage(pullRequest);
+        } else {
+            log.warn("No matched consumer for the PullRequest {}, drop it", pullRequest);
+        }
+    }

      实际上调用了这个方法，这个方法很长，我在代码里注释下下每一段的功能

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      public void pullMessage(final PullRequest pullRequest) {
              final ProcessQueue processQueue = pullRequest.getProcessQueue();
              // 这里开始就是检查状态，确定是否往下执行
              if (processQueue.isDropped()) {
                  log.info("the pull request[{}] is dropped.", pullRequest.toString());
                  return;
              }

              pullRequest.getProcessQueue().setLastPullTimestamp(System.currentTimeMillis());

              try {
                  this.makeSureStateOK();
              } catch (MQClientException e) {
                  log.warn("pullMessage exception, consumer state not ok", e);
                  this.executePullRequestLater(pullRequest, pullTimeDelayMillsWhenException);
                  return;
              }

              if (this.isPause()) {
                  log.warn("consumer was paused, execute pull request later. instanceName={}, group={}", this.defaultMQPushConsumer.getInstanceName(), this.defaultMQPushConsumer.getConsumerGroup());
                  this.executePullRequestLater(pullRequest, PULL_TIME_DELAY_MILLS_WHEN_SUSPEND);
                  return;
              }

              // 这块其实是个类似于限流的功能块，对消息数量和消息大小做限制
              long cachedMessageCount = processQueue.getMsgCount().get();
              long cachedMessageSizeInMiB = processQueue.getMsgSize().get() / (1024 * 1024);

              if (cachedMessageCount > this.defaultMQPushConsumer.getPullThresholdForQueue()) {
                  this.executePullRequestLater(pullRequest, PULL_TIME_DELAY_MILLS_WHEN_FLOW_CONTROL);
                  if ((queueFlowControlTimes++ % 1000) == 0) {
                      log.warn(
                          "the cached message count exceeds the threshold {}, so do flow control, minOffset={}, maxOffset={}, count={}, size={} MiB, pullRequest={}, flowControlTimes={}",
                          this.defaultMQPushConsumer.getPullThresholdForQueue(), processQueue.getMsgTreeMap().firstKey(), processQueue.getMsgTreeMap().lastKey(), cachedMessageCount, cachedMessageSizeInMiB, pullRequest, queueFlowControlTimes);
                  }
                  return;
              }

              if (cachedMessageSizeInMiB > this.defaultMQPushConsumer.getPullThresholdSizeForQueue()) {
                  this.executePullRequestLater(pullRequest, PULL_TIME_DELAY_MILLS_WHEN_FLOW_CONTROL);
                  if ((queueFlowControlTimes++ % 1000) == 0) {
                      log.warn(
                          "the cached message size exceeds the threshold {} MiB, so do flow control, minOffset={}, maxOffset={}, count={}, size={} MiB, pullRequest={}, flowControlTimes={}",
                          this.defaultMQPushConsumer.getPullThresholdSizeForQueue(), processQueue.getMsgTreeMap().firstKey(), processQueue.getMsgTreeMap().lastKey(), cachedMessageCount, cachedMessageSizeInMiB, pullRequest, queueFlowControlTimes);
                  }
                  return;
              }

              // 若不是顺序消费（即DefaultMQPushConsumerImpl.consumeOrderly等于false），则检查ProcessQueue对象的msgTreeMap:TreeMap<Long,MessageExt>变量的第一个key值与最后一个key值之间的差额，该key值表示查询的队列偏移量queueoffset；若差额大于阈值（由DefaultMQPushConsumer. consumeConcurrentlyMaxSpan指定，默认是2000），则调用PullMessageService.executePullRequestLater方法，在50毫秒之后重新将该PullRequest请求放入PullMessageService.pullRequestQueue队列中；并跳出该方法；这里的意思主要就是消息有堆积了，等会再来拉取
              if (!this.consumeOrderly) {
                  if (processQueue.getMaxSpan() > this.defaultMQPushConsumer.getConsumeConcurrentlyMaxSpan()) {
                      this.executePullRequestLater(pullRequest, PULL_TIME_DELAY_MILLS_WHEN_FLOW_CONTROL);
                      if ((queueMaxSpanFlowControlTimes++ % 1000) == 0) {
                          log.warn(
                              "the queue's messages, span too long, so do flow control, minOffset={}, maxOffset={}, maxSpan={}, pullRequest={}, flowControlTimes={}",
                              processQueue.getMsgTreeMap().firstKey(), processQueue.getMsgTreeMap().lastKey(), processQueue.getMaxSpan(),
                              pullRequest, queueMaxSpanFlowControlTimes);
                      }
                      return;
                  }
              } else {
                  if (processQueue.isLocked()) {
                      if (!pullRequest.isLockedFirst()) {
                          final long offset = this.rebalanceImpl.computePullFromWhere(pullRequest.getMessageQueue());
                          boolean brokerBusy = offset < pullRequest.getNextOffset();
                          log.info("the first time to pull message, so fix offset from broker. pullRequest: {} NewOffset: {} brokerBusy: {}",
                              pullRequest, offset, brokerBusy);
                          if (brokerBusy) {
                              log.info("[NOTIFYME]the first time to pull message, but pull request offset larger than broker consume offset. pullRequest: {} NewOffset: {}",
                                  pullRequest, offset);
                          }

                          pullRequest.setLockedFirst(true);
                          pullRequest.setNextOffset(offset);
                      }
                  } else {
                      this.executePullRequestLater(pullRequest, pullTimeDelayMillsWhenException);
                      log.info("pull message later because not locked in broker, {}", pullRequest);
                      return;
                  }
              }

              // 以PullRequest.messageQueue对象的topic值为参数从RebalanceImpl.subscriptionInner: ConcurrentHashMap, SubscriptionData>中获取对应的SubscriptionData对象，若该对象为null，考虑到并发的关系，调用executePullRequestLater方法，稍后重试；并跳出该方法；
              final SubscriptionData subscriptionData = this.rebalanceImpl.getSubscriptionInner().get(pullRequest.getMessageQueue().getTopic());
              if (null == subscriptionData) {
                  this.executePullRequestLater(pullRequest, pullTimeDelayMillsWhenException);
                  log.warn("find the consumer's subscription failed, {}", pullRequest);
                  return;
              }

              final long beginTimestamp = System.currentTimeMillis();

              // 异步拉取回调，先不讨论细节
              PullCallback pullCallback = new PullCallback() {
                  @Override
                  public void onSuccess(PullResult pullResult) {
                      if (pullResult != null) {
                          pullResult = DefaultMQPushConsumerImpl.this.pullAPIWrapper.processPullResult(pullRequest.getMessageQueue(), pullResult,
                              subscriptionData);

                          switch (pullResult.getPullStatus()) {
                              case FOUND:
                                  long prevRequestOffset = pullRequest.getNextOffset();
                                  pullRequest.setNextOffset(pullResult.getNextBeginOffset());
                                  long pullRT = System.currentTimeMillis() - beginTimestamp;
                                  DefaultMQPushConsumerImpl.this.getConsumerStatsManager().incPullRT(pullRequest.getConsumerGroup(),
                                      pullRequest.getMessageQueue().getTopic(), pullRT);

                                  long firstMsgOffset = Long.MAX_VALUE;
                                  if (pullResult.getMsgFoundList() == null || pullResult.getMsgFoundList().isEmpty()) {
                                      DefaultMQPushConsumerImpl.this.executePullRequestImmediately(pullRequest);
                                  } else {
                                      firstMsgOffset = pullResult.getMsgFoundList().get(0).getQueueOffset();

                                      DefaultMQPushConsumerImpl.this.getConsumerStatsManager().incPullTPS(pullRequest.getConsumerGroup(),
                                          pullRequest.getMessageQueue().getTopic(), pullResult.getMsgFoundList().size());

                                      boolean dispatchToConsume = processQueue.putMessage(pullResult.getMsgFoundList());
                                      DefaultMQPushConsumerImpl.this.consumeMessageService.submitConsumeRequest(
                                          pullResult.getMsgFoundList(),
                                          processQueue,
                                          pullRequest.getMessageQueue(),
                                          dispatchToConsume);

                                      if (DefaultMQPushConsumerImpl.this.defaultMQPushConsumer.getPullInterval() > 0) {
                                          DefaultMQPushConsumerImpl.this.executePullRequestLater(pullRequest,
                                              DefaultMQPushConsumerImpl.this.defaultMQPushConsumer.getPullInterval());
                                      } else {
                                          DefaultMQPushConsumerImpl.this.executePullRequestImmediately(pullRequest);
                                      }
                                  }

                                  if (pullResult.getNextBeginOffset() < prevRequestOffset
                                      || firstMsgOffset < prevRequestOffset) {
                                      log.warn(
                                          "[BUG] pull message result maybe data wrong, nextBeginOffset: {} firstMsgOffset: {} prevRequestOffset: {}",
                                          pullResult.getNextBeginOffset(),
                                          firstMsgOffset,
                                          prevRequestOffset);
                                  }

                                  break;
                              case NO_NEW_MSG:
                                  pullRequest.setNextOffset(pullResult.getNextBeginOffset());

                                  DefaultMQPushConsumerImpl.this.correctTagsOffset(pullRequest);

                                  DefaultMQPushConsumerImpl.this.executePullRequestImmediately(pullRequest);
                                  break;
                              case NO_MATCHED_MSG:
                                  pullRequest.setNextOffset(pullResult.getNextBeginOffset());

                                  DefaultMQPushConsumerImpl.this.correctTagsOffset(pullRequest);

                                  DefaultMQPushConsumerImpl.this.executePullRequestImmediately(pullRequest);
                                  break;
                              case OFFSET_ILLEGAL:
                                  log.warn("the pull request offset illegal, {} {}",
                                      pullRequest.toString(), pullResult.toString());
                                  pullRequest.setNextOffset(pullResult.getNextBeginOffset());

                                  pullRequest.getProcessQueue().setDropped(true);
                                  DefaultMQPushConsumerImpl.this.executeTaskLater(new Runnable() {

                                      @Override
                                      public void run() {
                                          try {
                                              DefaultMQPushConsumerImpl.this.offsetStore.updateOffset(pullRequest.getMessageQueue(),
                                                  pullRequest.getNextOffset(), false);

                                              DefaultMQPushConsumerImpl.this.offsetStore.persist(pullRequest.getMessageQueue());

                                              DefaultMQPushConsumerImpl.this.rebalanceImpl.removeProcessQueue(pullRequest.getMessageQueue());

                                              log.warn("fix the pull request offset, {}", pullRequest);
                                          } catch (Throwable e) {
                                              log.error("executeTaskLater Exception", e);
                                          }
                                      }
                                  }, 10000);
                                  break;
                              default:
                                  break;
                          }
                      }
                  }

                  @Override
                  public void onException(Throwable e) {
                      if (!pullRequest.getMessageQueue().getTopic().startsWith(MixAll.RETRY_GROUP_TOPIC_PREFIX)) {
                          log.warn("execute the pull request exception", e);
                      }

                      DefaultMQPushConsumerImpl.this.executePullRequestLater(pullRequest, pullTimeDelayMillsWhenException);
                  }
              };
              // 如果为集群模式，即可置commitOffsetEnable为 true
              boolean commitOffsetEnable = false;
              long commitOffsetValue = 0L;
              if (MessageModel.CLUSTERING == this.defaultMQPushConsumer.getMessageModel()) {
                  commitOffsetValue = this.offsetStore.readOffset(pullRequest.getMessageQueue(), ReadOffsetType.READ_FROM_MEMORY);
                  if (commitOffsetValue > 0) {
                      commitOffsetEnable = true;
                  }
              }

              // 将上面获得的commitOffsetEnable更新到订阅关系里
              String subExpression = null;
              boolean classFilter = false;
              SubscriptionData sd = this.rebalanceImpl.getSubscriptionInner().get(pullRequest.getMessageQueue().getTopic());
              if (sd != null) {
                  if (this.defaultMQPushConsumer.isPostSubscriptionWhenPull() && !sd.isClassFilterMode()) {
                      subExpression = sd.getSubString();
                  }

                  classFilter = sd.isClassFilterMode();
              }

              // 组成 sysFlag
              int sysFlag = PullSysFlag.buildSysFlag(
                  commitOffsetEnable, // commitOffset
                  true, // suspend
                  subExpression != null, // subscription
                  classFilter // class filter
              );
              // 调用真正的拉取消息接口
              try {
                  this.pullAPIWrapper.pullKernelImpl(
                      pullRequest.getMessageQueue(),
                      subExpression,
                      subscriptionData.getExpressionType(),
                      subscriptionData.getSubVersion(),
                      pullRequest.getNextOffset(),
                      this.defaultMQPushConsumer.getPullBatchSize(),
                      sysFlag,
                      commitOffsetValue,
                      BROKER_SUSPEND_MAX_TIME_MILLIS,
                      CONSUMER_TIMEOUT_MILLIS_WHEN_SUSPEND,
                      CommunicationMode.ASYNC,
                      pullCallback
                  );
              } catch (Exception e) {
                  log.error("pullKernelImpl exception", e);
                  this.executePullRequestLater(pullRequest, pullTimeDelayMillsWhenException);
              }
          }
      +
      public void pullMessage(final PullRequest pullRequest) {
+        final ProcessQueue processQueue = pullRequest.getProcessQueue();
+        // 这里开始就是检查状态，确定是否往下执行
+        if (processQueue.isDropped()) {
+            log.info("the pull request[{}] is dropped.", pullRequest.toString());
+            return;
+        }
+
+        pullRequest.getProcessQueue().setLastPullTimestamp(System.currentTimeMillis());
+
+        try {
+            this.makeSureStateOK();
+        } catch (MQClientException e) {
+            log.warn("pullMessage exception, consumer state not ok", e);
+            this.executePullRequestLater(pullRequest, pullTimeDelayMillsWhenException);
+            return;
+        }
+
+        if (this.isPause()) {
+            log.warn("consumer was paused, execute pull request later. instanceName={}, group={}", this.defaultMQPushConsumer.getInstanceName(), this.defaultMQPushConsumer.getConsumerGroup());
+            this.executePullRequestLater(pullRequest, PULL_TIME_DELAY_MILLS_WHEN_SUSPEND);
+            return;
+        }
+
+        // 这块其实是个类似于限流的功能块，对消息数量和消息大小做限制
+        long cachedMessageCount = processQueue.getMsgCount().get();
+        long cachedMessageSizeInMiB = processQueue.getMsgSize().get() / (1024 * 1024);
+
+        if (cachedMessageCount > this.defaultMQPushConsumer.getPullThresholdForQueue()) {
+            this.executePullRequestLater(pullRequest, PULL_TIME_DELAY_MILLS_WHEN_FLOW_CONTROL);
+            if ((queueFlowControlTimes++ % 1000) == 0) {
+                log.warn(
+                    "the cached message count exceeds the threshold {}, so do flow control, minOffset={}, maxOffset={}, count={}, size={} MiB, pullRequest={}, flowControlTimes={}",
+                    this.defaultMQPushConsumer.getPullThresholdForQueue(), processQueue.getMsgTreeMap().firstKey(), processQueue.getMsgTreeMap().lastKey(), cachedMessageCount, cachedMessageSizeInMiB, pullRequest, queueFlowControlTimes);
+            }
+            return;
+        }
+
+        if (cachedMessageSizeInMiB > this.defaultMQPushConsumer.getPullThresholdSizeForQueue()) {
+            this.executePullRequestLater(pullRequest, PULL_TIME_DELAY_MILLS_WHEN_FLOW_CONTROL);
+            if ((queueFlowControlTimes++ % 1000) == 0) {
+                log.warn(
+                    "the cached message size exceeds the threshold {} MiB, so do flow control, minOffset={}, maxOffset={}, count={}, size={} MiB, pullRequest={}, flowControlTimes={}",
+                    this.defaultMQPushConsumer.getPullThresholdSizeForQueue(), processQueue.getMsgTreeMap().firstKey(), processQueue.getMsgTreeMap().lastKey(), cachedMessageCount, cachedMessageSizeInMiB, pullRequest, queueFlowControlTimes);
+            }
+            return;
+        }
+
+        // 若不是顺序消费（即DefaultMQPushConsumerImpl.consumeOrderly等于false），则检查ProcessQueue对象的msgTreeMap:TreeMap<Long,MessageExt>变量的第一个key值与最后一个key值之间的差额，该key值表示查询的队列偏移量queueoffset；若差额大于阈值（由DefaultMQPushConsumer. consumeConcurrentlyMaxSpan指定，默认是2000），则调用PullMessageService.executePullRequestLater方法，在50毫秒之后重新将该PullRequest请求放入PullMessageService.pullRequestQueue队列中；并跳出该方法；这里的意思主要就是消息有堆积了，等会再来拉取
+        if (!this.consumeOrderly) {
+            if (processQueue.getMaxSpan() > this.defaultMQPushConsumer.getConsumeConcurrentlyMaxSpan()) {
+                this.executePullRequestLater(pullRequest, PULL_TIME_DELAY_MILLS_WHEN_FLOW_CONTROL);
+                if ((queueMaxSpanFlowControlTimes++ % 1000) == 0) {
+                    log.warn(
+                        "the queue's messages, span too long, so do flow control, minOffset={}, maxOffset={}, maxSpan={}, pullRequest={}, flowControlTimes={}",
+                        processQueue.getMsgTreeMap().firstKey(), processQueue.getMsgTreeMap().lastKey(), processQueue.getMaxSpan(),
+                        pullRequest, queueMaxSpanFlowControlTimes);
+                }
+                return;
+            }
+        } else {
+            if (processQueue.isLocked()) {
+                if (!pullRequest.isLockedFirst()) {
+                    final long offset = this.rebalanceImpl.computePullFromWhere(pullRequest.getMessageQueue());
+                    boolean brokerBusy = offset < pullRequest.getNextOffset();
+                    log.info("the first time to pull message, so fix offset from broker. pullRequest: {} NewOffset: {} brokerBusy: {}",
+                        pullRequest, offset, brokerBusy);
+                    if (brokerBusy) {
+                        log.info("[NOTIFYME]the first time to pull message, but pull request offset larger than broker consume offset. pullRequest: {} NewOffset: {}",
+                            pullRequest, offset);
+                    }
+
+                    pullRequest.setLockedFirst(true);
+                    pullRequest.setNextOffset(offset);
+                }
+            } else {
+                this.executePullRequestLater(pullRequest, pullTimeDelayMillsWhenException);
+                log.info("pull message later because not locked in broker, {}", pullRequest);
+                return;
+            }
+        }
+
+        // 以PullRequest.messageQueue对象的topic值为参数从RebalanceImpl.subscriptionInner: ConcurrentHashMap, SubscriptionData>中获取对应的SubscriptionData对象，若该对象为null，考虑到并发的关系，调用executePullRequestLater方法，稍后重试；并跳出该方法；
+        final SubscriptionData subscriptionData = this.rebalanceImpl.getSubscriptionInner().get(pullRequest.getMessageQueue().getTopic());
+        if (null == subscriptionData) {
+            this.executePullRequestLater(pullRequest, pullTimeDelayMillsWhenException);
+            log.warn("find the consumer's subscription failed, {}", pullRequest);
+            return;
+        }
+
+        final long beginTimestamp = System.currentTimeMillis();
+
+        // 异步拉取回调，先不讨论细节
+        PullCallback pullCallback = new PullCallback() {
+            @Override
+            public void onSuccess(PullResult pullResult) {
+                if (pullResult != null) {
+                    pullResult = DefaultMQPushConsumerImpl.this.pullAPIWrapper.processPullResult(pullRequest.getMessageQueue(), pullResult,
+                        subscriptionData);
+
+                    switch (pullResult.getPullStatus()) {
+                        case FOUND:
+                            long prevRequestOffset = pullRequest.getNextOffset();
+                            pullRequest.setNextOffset(pullResult.getNextBeginOffset());
+                            long pullRT = System.currentTimeMillis() - beginTimestamp;
+                            DefaultMQPushConsumerImpl.this.getConsumerStatsManager().incPullRT(pullRequest.getConsumerGroup(),
+                                pullRequest.getMessageQueue().getTopic(), pullRT);
+
+                            long firstMsgOffset = Long.MAX_VALUE;
+                            if (pullResult.getMsgFoundList() == null || pullResult.getMsgFoundList().isEmpty()) {
+                                DefaultMQPushConsumerImpl.this.executePullRequestImmediately(pullRequest);
+                            } else {
+                                firstMsgOffset = pullResult.getMsgFoundList().get(0).getQueueOffset();
+
+                                DefaultMQPushConsumerImpl.this.getConsumerStatsManager().incPullTPS(pullRequest.getConsumerGroup(),
+                                    pullRequest.getMessageQueue().getTopic(), pullResult.getMsgFoundList().size());
+
+                                boolean dispatchToConsume = processQueue.putMessage(pullResult.getMsgFoundList());
+                                DefaultMQPushConsumerImpl.this.consumeMessageService.submitConsumeRequest(
+                                    pullResult.getMsgFoundList(),
+                                    processQueue,
+                                    pullRequest.getMessageQueue(),
+                                    dispatchToConsume);
+
+                                if (DefaultMQPushConsumerImpl.this.defaultMQPushConsumer.getPullInterval() > 0) {
+                                    DefaultMQPushConsumerImpl.this.executePullRequestLater(pullRequest,
+                                        DefaultMQPushConsumerImpl.this.defaultMQPushConsumer.getPullInterval());
+                                } else {
+                                    DefaultMQPushConsumerImpl.this.executePullRequestImmediately(pullRequest);
+                                }
+                            }
+
+                            if (pullResult.getNextBeginOffset() < prevRequestOffset
+                                || firstMsgOffset < prevRequestOffset) {
+                                log.warn(
+                                    "[BUG] pull message result maybe data wrong, nextBeginOffset: {} firstMsgOffset: {} prevRequestOffset: {}",
+                                    pullResult.getNextBeginOffset(),
+                                    firstMsgOffset,
+                                    prevRequestOffset);
+                            }
+
+                            break;
+                        case NO_NEW_MSG:
+                            pullRequest.setNextOffset(pullResult.getNextBeginOffset());
+
+                            DefaultMQPushConsumerImpl.this.correctTagsOffset(pullRequest);
+
+                            DefaultMQPushConsumerImpl.this.executePullRequestImmediately(pullRequest);
+                            break;
+                        case NO_MATCHED_MSG:
+                            pullRequest.setNextOffset(pullResult.getNextBeginOffset());
+
+                            DefaultMQPushConsumerImpl.this.correctTagsOffset(pullRequest);
+
+                            DefaultMQPushConsumerImpl.this.executePullRequestImmediately(pullRequest);
+                            break;
+                        case OFFSET_ILLEGAL:
+                            log.warn("the pull request offset illegal, {} {}",
+                                pullRequest.toString(), pullResult.toString());
+                            pullRequest.setNextOffset(pullResult.getNextBeginOffset());
+
+                            pullRequest.getProcessQueue().setDropped(true);
+                            DefaultMQPushConsumerImpl.this.executeTaskLater(new Runnable() {
+
+                                @Override
+                                public void run() {
+                                    try {
+                                        DefaultMQPushConsumerImpl.this.offsetStore.updateOffset(pullRequest.getMessageQueue(),
+                                            pullRequest.getNextOffset(), false);
+
+                                        DefaultMQPushConsumerImpl.this.offsetStore.persist(pullRequest.getMessageQueue());
+
+                                        DefaultMQPushConsumerImpl.this.rebalanceImpl.removeProcessQueue(pullRequest.getMessageQueue());
+
+                                        log.warn("fix the pull request offset, {}", pullRequest);
+                                    } catch (Throwable e) {
+                                        log.error("executeTaskLater Exception", e);
+                                    }
+                                }
+                            }, 10000);
+                            break;
+                        default:
+                            break;
+                    }
+                }
+            }
+
+            @Override
+            public void onException(Throwable e) {
+                if (!pullRequest.getMessageQueue().getTopic().startsWith(MixAll.RETRY_GROUP_TOPIC_PREFIX)) {
+                    log.warn("execute the pull request exception", e);
+                }
+
+                DefaultMQPushConsumerImpl.this.executePullRequestLater(pullRequest, pullTimeDelayMillsWhenException);
+            }
+        };
+        // 如果为集群模式，即可置commitOffsetEnable为 true
+        boolean commitOffsetEnable = false;
+        long commitOffsetValue = 0L;
+        if (MessageModel.CLUSTERING == this.defaultMQPushConsumer.getMessageModel()) {
+            commitOffsetValue = this.offsetStore.readOffset(pullRequest.getMessageQueue(), ReadOffsetType.READ_FROM_MEMORY);
+            if (commitOffsetValue > 0) {
+                commitOffsetEnable = true;
+            }
+        }
+
+        // 将上面获得的commitOffsetEnable更新到订阅关系里
+        String subExpression = null;
+        boolean classFilter = false;
+        SubscriptionData sd = this.rebalanceImpl.getSubscriptionInner().get(pullRequest.getMessageQueue().getTopic());
+        if (sd != null) {
+            if (this.defaultMQPushConsumer.isPostSubscriptionWhenPull() && !sd.isClassFilterMode()) {
+                subExpression = sd.getSubString();
+            }
+
+            classFilter = sd.isClassFilterMode();
+        }
+
+        // 组成 sysFlag
+        int sysFlag = PullSysFlag.buildSysFlag(
+            commitOffsetEnable, // commitOffset
+            true, // suspend
+            subExpression != null, // subscription
+            classFilter // class filter
+        );
+        // 调用真正的拉取消息接口
+        try {
+            this.pullAPIWrapper.pullKernelImpl(
+                pullRequest.getMessageQueue(),
+                subExpression,
+                subscriptionData.getExpressionType(),
+                subscriptionData.getSubVersion(),
+                pullRequest.getNextOffset(),
+                this.defaultMQPushConsumer.getPullBatchSize(),
+                sysFlag,
+                commitOffsetValue,
+                BROKER_SUSPEND_MAX_TIME_MILLIS,
+                CONSUMER_TIMEOUT_MILLIS_WHEN_SUSPEND,
+                CommunicationMode.ASYNC,
+                pullCallback
+            );
+        } catch (Exception e) {
+            log.error("pullKernelImpl exception", e);
+            this.executePullRequestLater(pullRequest, pullTimeDelayMillsWhenException);
+        }
+    }

      以下就是拉取消息的底层 api，不够不是特别复杂，主要是在找 broker，和设置请求参数

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      public PullResult pullKernelImpl(
          final MessageQueue mq,
          final String subExpression,
          final String expressionType,
          final long subVersion,
          final long offset,
          final int maxNums,
          final int sysFlag,
          final long commitOffset,
          final long brokerSuspendMaxTimeMillis,
          final long timeoutMillis,
          final CommunicationMode communicationMode,
          final PullCallback pullCallback
      ) throws MQClientException, RemotingException, MQBrokerException, InterruptedException {
          FindBrokerResult findBrokerResult =
              this.mQClientFactory.findBrokerAddressInSubscribe(mq.getBrokerName(),
                  this.recalculatePullFromWhichNode(mq), false);
          if (null == findBrokerResult) {
              this.mQClientFactory.updateTopicRouteInfoFromNameServer(mq.getTopic());
              findBrokerResult =
                  this.mQClientFactory.findBrokerAddressInSubscribe(mq.getBrokerName(),
                      this.recalculatePullFromWhichNode(mq), false);
          }

          if (findBrokerResult != null) {
              {
                  // check version
                  if (!ExpressionType.isTagType(expressionType)
                      && findBrokerResult.getBrokerVersion() < MQVersion.Version.V4_1_0_SNAPSHOT.ordinal()) {
                      throw new MQClientException("The broker[" + mq.getBrokerName() + ", "
                          + findBrokerResult.getBrokerVersion() + "] does not upgrade to support for filter message by " + expressionType, null);
                  }
              }
              int sysFlagInner = sysFlag;

              if (findBrokerResult.isSlave()) {
                  sysFlagInner = PullSysFlag.clearCommitOffsetFlag(sysFlagInner);
              }

              PullMessageRequestHeader requestHeader = new PullMessageRequestHeader();
              requestHeader.setConsumerGroup(this.consumerGroup);
              requestHeader.setTopic(mq.getTopic());
              requestHeader.setQueueId(mq.getQueueId());
              requestHeader.setQueueOffset(offset);
              requestHeader.setMaxMsgNums(maxNums);
              requestHeader.setSysFlag(sysFlagInner);
              requestHeader.setCommitOffset(commitOffset);
              requestHeader.setSuspendTimeoutMillis(brokerSuspendMaxTimeMillis);
              requestHeader.setSubscription(subExpression);
              requestHeader.setSubVersion(subVersion);
              requestHeader.setExpressionType(expressionType);

              String brokerAddr = findBrokerResult.getBrokerAddr();
              if (PullSysFlag.hasClassFilterFlag(sysFlagInner)) {
                  brokerAddr = computPullFromWhichFilterServer(mq.getTopic(), brokerAddr);
              }

              PullResult pullResult = this.mQClientFactory.getMQClientAPIImpl().pullMessage(
                  brokerAddr,
                  requestHeader,
                  timeoutMillis,
                  communicationMode,
                  pullCallback);

              return pullResult;
          }

          throw new MQClientException("The broker[" + mq.getBrokerName() + "] not exist", null);
      }
      +
      public PullResult pullKernelImpl(
+    final MessageQueue mq,
+    final String subExpression,
+    final String expressionType,
+    final long subVersion,
+    final long offset,
+    final int maxNums,
+    final int sysFlag,
+    final long commitOffset,
+    final long brokerSuspendMaxTimeMillis,
+    final long timeoutMillis,
+    final CommunicationMode communicationMode,
+    final PullCallback pullCallback
+) throws MQClientException, RemotingException, MQBrokerException, InterruptedException {
+    FindBrokerResult findBrokerResult =
+        this.mQClientFactory.findBrokerAddressInSubscribe(mq.getBrokerName(),
+            this.recalculatePullFromWhichNode(mq), false);
+    if (null == findBrokerResult) {
+        this.mQClientFactory.updateTopicRouteInfoFromNameServer(mq.getTopic());
+        findBrokerResult =
+            this.mQClientFactory.findBrokerAddressInSubscribe(mq.getBrokerName(),
+                this.recalculatePullFromWhichNode(mq), false);
+    }
+
+    if (findBrokerResult != null) {
+        {
+            // check version
+            if (!ExpressionType.isTagType(expressionType)
+                && findBrokerResult.getBrokerVersion() < MQVersion.Version.V4_1_0_SNAPSHOT.ordinal()) {
+                throw new MQClientException("The broker[" + mq.getBrokerName() + ", "
+                    + findBrokerResult.getBrokerVersion() + "] does not upgrade to support for filter message by " + expressionType, null);
+            }
+        }
+        int sysFlagInner = sysFlag;
+
+        if (findBrokerResult.isSlave()) {
+            sysFlagInner = PullSysFlag.clearCommitOffsetFlag(sysFlagInner);
+        }
+
+        PullMessageRequestHeader requestHeader = new PullMessageRequestHeader();
+        requestHeader.setConsumerGroup(this.consumerGroup);
+        requestHeader.setTopic(mq.getTopic());
+        requestHeader.setQueueId(mq.getQueueId());
+        requestHeader.setQueueOffset(offset);
+        requestHeader.setMaxMsgNums(maxNums);
+        requestHeader.setSysFlag(sysFlagInner);
+        requestHeader.setCommitOffset(commitOffset);
+        requestHeader.setSuspendTimeoutMillis(brokerSuspendMaxTimeMillis);
+        requestHeader.setSubscription(subExpression);
+        requestHeader.setSubVersion(subVersion);
+        requestHeader.setExpressionType(expressionType);
+
+        String brokerAddr = findBrokerResult.getBrokerAddr();
+        if (PullSysFlag.hasClassFilterFlag(sysFlagInner)) {
+            brokerAddr = computPullFromWhichFilterServer(mq.getTopic(), brokerAddr);
+        }
+
+        PullResult pullResult = this.mQClientFactory.getMQClientAPIImpl().pullMessage(
+            brokerAddr,
+            requestHeader,
+            timeoutMillis,
+            communicationMode,
+            pullCallback);
+
+        return pullResult;
+    }
+
+    throw new MQClientException("The broker[" + mq.getBrokerName() + "] not exist", null);
+}

      再看下一步的

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      public PullResult pullMessage(
          final String addr,
          final PullMessageRequestHeader requestHeader,
          final long timeoutMillis,
          final CommunicationMode communicationMode,
          final PullCallback pullCallback
      ) throws RemotingException, MQBrokerException, InterruptedException {
          RemotingCommand request = RemotingCommand.createRequestCommand(RequestCode.PULL_MESSAGE, requestHeader);

          switch (communicationMode) {
              case ONEWAY:
                  assert false;
                  return null;
              case ASYNC:
                  this.pullMessageAsync(addr, request, timeoutMillis, pullCallback);
                  return null;
              case SYNC:
                  return this.pullMessageSync(addr, request, timeoutMillis);
              default:
                  assert false;
                  break;
          }

          return null;
      }
      +
      public PullResult pullMessage(
+    final String addr,
+    final PullMessageRequestHeader requestHeader,
+    final long timeoutMillis,
+    final CommunicationMode communicationMode,
+    final PullCallback pullCallback
+) throws RemotingException, MQBrokerException, InterruptedException {
+    RemotingCommand request = RemotingCommand.createRequestCommand(RequestCode.PULL_MESSAGE, requestHeader);
+
+    switch (communicationMode) {
+        case ONEWAY:
+            assert false;
+            return null;
+        case ASYNC:
+            this.pullMessageAsync(addr, request, timeoutMillis, pullCallback);
+            return null;
+        case SYNC:
+            return this.pullMessageSync(addr, request, timeoutMillis);
+        default:
+            assert false;
+            break;
+    }
+
+    return null;
+}

      通过 communicationMode 判断是同步拉取还是异步拉取，异步就调用

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      private void pullMessageAsync(
              final String addr,
              final RemotingCommand request,
              final long timeoutMillis,
              final PullCallback pullCallback
          ) throws RemotingException, InterruptedException {
              this.remotingClient.invokeAsync(addr, request, timeoutMillis, new InvokeCallback() {
                  @Override
                  public void operationComplete(ResponseFuture responseFuture) {
                      异步
                      RemotingCommand response = responseFuture.getResponseCommand();
                      if (response != null) {
                          try {
                              PullResult pullResult = MQClientAPIImpl.this.processPullResponse(response);
                              assert pullResult != null;
                              pullCallback.onSuccess(pullResult);
                          } catch (Exception e) {
                              pullCallback.onException(e);
                          }
                      } else {
                          if (!responseFuture.isSendRequestOK()) {
                              pullCallback.onException(new MQClientException("send request failed to " + addr + ". Request: " + request, responseFuture.getCause()));
                          } else if (responseFuture.isTimeout()) {
                              pullCallback.onException(new MQClientException("wait response from " + addr + " timeout :" + responseFuture.getTimeoutMillis() + "ms" + ". Request: " + request,
                                  responseFuture.getCause()));
                          } else {
                              pullCallback.onException(new MQClientException("unknown reason. addr: " + addr + ", timeoutMillis: " + timeoutMillis + ". Request: " + request, responseFuture.getCause()));
                          }
                      }
                  }
              });
          }
      +
      private void pullMessageAsync(
+        final String addr,
+        final RemotingCommand request,
+        final long timeoutMillis,
+        final PullCallback pullCallback
+    ) throws RemotingException, InterruptedException {
+        this.remotingClient.invokeAsync(addr, request, timeoutMillis, new InvokeCallback() {
+            @Override
+            public void operationComplete(ResponseFuture responseFuture) {
+                异步
+                RemotingCommand response = responseFuture.getResponseCommand();
+                if (response != null) {
+                    try {
+                        PullResult pullResult = MQClientAPIImpl.this.processPullResponse(response);
+                        assert pullResult != null;
+                        pullCallback.onSuccess(pullResult);
+                    } catch (Exception e) {
+                        pullCallback.onException(e);
+                    }
+                } else {
+                    if (!responseFuture.isSendRequestOK()) {
+                        pullCallback.onException(new MQClientException("send request failed to " + addr + ". Request: " + request, responseFuture.getCause()));
+                    } else if (responseFuture.isTimeout()) {
+                        pullCallback.onException(new MQClientException("wait response from " + addr + " timeout :" + responseFuture.getTimeoutMillis() + "ms" + ". Request: " + request,
+                            responseFuture.getCause()));
+                    } else {
+                        pullCallback.onException(new MQClientException("unknown reason. addr: " + addr + ", timeoutMillis: " + timeoutMillis + ". Request: " + request, responseFuture.getCause()));
+                    }
+                }
+            }
+        });
+    }

      并且会调用前面 pullCallback 的onSuccess和onException方法，同步的就是调用

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      private PullResult pullMessageSync(
              final String addr,
              final RemotingCommand request,
              final long timeoutMillis
          ) throws RemotingException, InterruptedException, MQBrokerException {
              RemotingCommand response = this.remotingClient.invokeSync(addr, request, timeoutMillis);
              assert response != null;
              return this.processPullResponse(response);
          }
      +
      private PullResult pullMessageSync(
+        final String addr,
+        final RemotingCommand request,
+        final long timeoutMillis
+    ) throws RemotingException, InterruptedException, MQBrokerException {
+        RemotingCommand response = this.remotingClient.invokeSync(addr, request, timeoutMillis);
+        assert response != null;
+        return this.processPullResponse(response);
+    }

      然后就是这个 remotingClient 的 invokeAsync 跟 invokeSync 方法

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      @Override
          public void invokeAsync(String addr, RemotingCommand request, long timeoutMillis, InvokeCallback invokeCallback)
              throws InterruptedException, RemotingConnectException, RemotingTooMuchRequestException, RemotingTimeoutException,
              RemotingSendRequestException {
              long beginStartTime = System.currentTimeMillis();
              final Channel channel = this.getAndCreateChannel(addr);
              if (channel != null && channel.isActive()) {
                  try {
                      doBeforeRpcHooks(addr, request);
                      long costTime = System.currentTimeMillis() - beginStartTime;
                      if (timeoutMillis < costTime) {
                          throw new RemotingTooMuchRequestException("invokeAsync call timeout");
                      }
                      this.invokeAsyncImpl(channel, request, timeoutMillis - costTime, invokeCallback);
                  } catch (RemotingSendRequestException e) {
                      log.warn("invokeAsync: send request exception, so close the channel[{}]", addr);
                      this.closeChannel(addr, channel);
                      throw e;
                  }
              } else {
                  this.closeChannel(addr, channel);
                  throw new RemotingConnectException(addr);
              }
          }
      @Override
          public RemotingCommand invokeSync(String addr, final RemotingCommand request, long timeoutMillis)
              throws InterruptedException, RemotingConnectException, RemotingSendRequestException, RemotingTimeoutException {
              long beginStartTime = System.currentTimeMillis();
              final Channel channel = this.getAndCreateChannel(addr);
              if (channel != null && channel.isActive()) {
                  try {
                      doBeforeRpcHooks(addr, request);
                      long costTime = System.currentTimeMillis() - beginStartTime;
                      if (timeoutMillis < costTime) {
                          throw new RemotingTimeoutException("invokeSync call timeout");
                      }
                      RemotingCommand response = this.invokeSyncImpl(channel, request, timeoutMillis - costTime);
                      doAfterRpcHooks(RemotingHelper.parseChannelRemoteAddr(channel), request, response);
                      return response;
                  } catch (RemotingSendRequestException e) {
                      log.warn("invokeSync: send request exception, so close the channel[{}]", addr);
                      this.closeChannel(addr, channel);
                      throw e;
                  } catch (RemotingTimeoutException e) {
                      if (nettyClientConfig.isClientCloseSocketIfTimeout()) {
                          this.closeChannel(addr, channel);
                          log.warn("invokeSync: close socket because of timeout, {}ms, {}", timeoutMillis, addr);
                      }
                      log.warn("invokeSync: wait response timeout exception, the channel[{}]", addr);
                      throw e;
                  }
              } else {
                  this.closeChannel(addr, channel);
                  throw new RemotingConnectException(addr);
              }
          }
      +
      @Override
+    public void invokeAsync(String addr, RemotingCommand request, long timeoutMillis, InvokeCallback invokeCallback)
+        throws InterruptedException, RemotingConnectException, RemotingTooMuchRequestException, RemotingTimeoutException,
+        RemotingSendRequestException {
+        long beginStartTime = System.currentTimeMillis();
+        final Channel channel = this.getAndCreateChannel(addr);
+        if (channel != null && channel.isActive()) {
+            try {
+                doBeforeRpcHooks(addr, request);
+                long costTime = System.currentTimeMillis() - beginStartTime;
+                if (timeoutMillis < costTime) {
+                    throw new RemotingTooMuchRequestException("invokeAsync call timeout");
+                }
+                this.invokeAsyncImpl(channel, request, timeoutMillis - costTime, invokeCallback);
+            } catch (RemotingSendRequestException e) {
+                log.warn("invokeAsync: send request exception, so close the channel[{}]", addr);
+                this.closeChannel(addr, channel);
+                throw e;
+            }
+        } else {
+            this.closeChannel(addr, channel);
+            throw new RemotingConnectException(addr);
+        }
+    }
+@Override
+    public RemotingCommand invokeSync(String addr, final RemotingCommand request, long timeoutMillis)
+        throws InterruptedException, RemotingConnectException, RemotingSendRequestException, RemotingTimeoutException {
+        long beginStartTime = System.currentTimeMillis();
+        final Channel channel = this.getAndCreateChannel(addr);
+        if (channel != null && channel.isActive()) {
+            try {
+                doBeforeRpcHooks(addr, request);
+                long costTime = System.currentTimeMillis() - beginStartTime;
+                if (timeoutMillis < costTime) {
+                    throw new RemotingTimeoutException("invokeSync call timeout");
+                }
+                RemotingCommand response = this.invokeSyncImpl(channel, request, timeoutMillis - costTime);
+                doAfterRpcHooks(RemotingHelper.parseChannelRemoteAddr(channel), request, response);
+                return response;
+            } catch (RemotingSendRequestException e) {
+                log.warn("invokeSync: send request exception, so close the channel[{}]", addr);
+                this.closeChannel(addr, channel);
+                throw e;
+            } catch (RemotingTimeoutException e) {
+                if (nettyClientConfig.isClientCloseSocketIfTimeout()) {
+                    this.closeChannel(addr, channel);
+                    log.warn("invokeSync: close socket because of timeout, {}ms, {}", timeoutMillis, addr);
+                }
+                log.warn("invokeSync: wait response timeout exception, the channel[{}]", addr);
+                throw e;
+            }
+        } else {
+            this.closeChannel(addr, channel);
+            throw new RemotingConnectException(addr);
+        }
+    }

      再往下看

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      public RemotingCommand invokeSyncImpl(final Channel channel, final RemotingCommand request,
              final long timeoutMillis)
              throws InterruptedException, RemotingSendRequestException, RemotingTimeoutException {
              final int opaque = request.getOpaque();

              try {
                  同步跟异步都是会把结果用ResponseFuture抱起来
                  final ResponseFuture responseFuture = new ResponseFuture(channel, opaque, timeoutMillis, null, null);
                  this.responseTable.put(opaque, responseFuture);
                  final SocketAddress addr = channel.remoteAddress();
                  channel.writeAndFlush(request).addListener(new ChannelFutureListener() {
                      @Override
                      public void operationComplete(ChannelFuture f) throws Exception {
                          if (f.isSuccess()) {
                              responseFuture.setSendRequestOK(true);
                              return;
                          } else {
                              responseFuture.setSendRequestOK(false);
                          }

                          responseTable.remove(opaque);
                          responseFuture.setCause(f.cause());
                          responseFuture.putResponse(null);
                          log.warn("send a request command to channel <" + addr + "> failed.");
                      }
                  });
                  // 区别是同步的是在这等待
                  RemotingCommand responseCommand = responseFuture.waitResponse(timeoutMillis);
                  if (null == responseCommand) {
                      if (responseFuture.isSendRequestOK()) {
                          throw new RemotingTimeoutException(RemotingHelper.parseSocketAddressAddr(addr), timeoutMillis,
                              responseFuture.getCause());
                      } else {
                          throw new RemotingSendRequestException(RemotingHelper.parseSocketAddressAddr(addr), responseFuture.getCause());
                      }
                  }

                  return responseCommand;
              } finally {
                  this.responseTable.remove(opaque);
              }
          }

          public void invokeAsyncImpl(final Channel channel, final RemotingCommand request, final long timeoutMillis,
              final InvokeCallback invokeCallback)
              throws InterruptedException, RemotingTooMuchRequestException, RemotingTimeoutException, RemotingSendRequestException {
              long beginStartTime = System.currentTimeMillis();
              final int opaque = request.getOpaque();
              boolean acquired = this.semaphoreAsync.tryAcquire(timeoutMillis, TimeUnit.MILLISECONDS);
              if (acquired) {
                  final SemaphoreReleaseOnlyOnce once = new SemaphoreReleaseOnlyOnce(this.semaphoreAsync);
                  long costTime = System.currentTimeMillis() - beginStartTime;
                  if (timeoutMillis < costTime) {
                      once.release();
                      throw new RemotingTimeoutException("invokeAsyncImpl call timeout");
                  }

                  final ResponseFuture responseFuture = new ResponseFuture(channel, opaque, timeoutMillis - costTime, invokeCallback, once);
                  this.responseTable.put(opaque, responseFuture);
                  try {
                      channel.writeAndFlush(request).addListener(new ChannelFutureListener() {
                          @Override
                          public void operationComplete(ChannelFuture f) throws Exception {
                              if (f.isSuccess()) {
                                  responseFuture.setSendRequestOK(true);
                                  return;
                              }
                              requestFail(opaque);
                              log.warn("send a request command to channel <{}> failed.", RemotingHelper.parseChannelRemoteAddr(channel));
                          }
                      });
                  } catch (Exception e) {
                      responseFuture.release();
                      log.warn("send a request command to channel <" + RemotingHelper.parseChannelRemoteAddr(channel) + "> Exception", e);
                      throw new RemotingSendRequestException(RemotingHelper.parseChannelRemoteAddr(channel), e);
                  }
              } else {
                  if (timeoutMillis <= 0) {
                      throw new RemotingTooMuchRequestException("invokeAsyncImpl invoke too fast");
                  } else {
                      String info =
                          String.format("invokeAsyncImpl tryAcquire semaphore timeout, %dms, waiting thread nums: %d semaphoreAsyncValue: %d",
                              timeoutMillis,
                              this.semaphoreAsync.getQueueLength(),
                              this.semaphoreAsync.availablePermits()
                          );
                      log.warn(info);
                      throw new RemotingTimeoutException(info);
                  }
              }
          }
      +
      public RemotingCommand invokeSyncImpl(final Channel channel, final RemotingCommand request,
+        final long timeoutMillis)
+        throws InterruptedException, RemotingSendRequestException, RemotingTimeoutException {
+        final int opaque = request.getOpaque();
+
+        try {
+            同步跟异步都是会把结果用ResponseFuture抱起来
+            final ResponseFuture responseFuture = new ResponseFuture(channel, opaque, timeoutMillis, null, null);
+            this.responseTable.put(opaque, responseFuture);
+            final SocketAddress addr = channel.remoteAddress();
+            channel.writeAndFlush(request).addListener(new ChannelFutureListener() {
+                @Override
+                public void operationComplete(ChannelFuture f) throws Exception {
+                    if (f.isSuccess()) {
+                        responseFuture.setSendRequestOK(true);
+                        return;
+                    } else {
+                        responseFuture.setSendRequestOK(false);
+                    }
+
+                    responseTable.remove(opaque);
+                    responseFuture.setCause(f.cause());
+                    responseFuture.putResponse(null);
+                    log.warn("send a request command to channel <" + addr + "> failed.");
+                }
+            });
+            // 区别是同步的是在这等待
+            RemotingCommand responseCommand = responseFuture.waitResponse(timeoutMillis);
+            if (null == responseCommand) {
+                if (responseFuture.isSendRequestOK()) {
+                    throw new RemotingTimeoutException(RemotingHelper.parseSocketAddressAddr(addr), timeoutMillis,
+                        responseFuture.getCause());
+                } else {
+                    throw new RemotingSendRequestException(RemotingHelper.parseSocketAddressAddr(addr), responseFuture.getCause());
+                }
+            }
+
+            return responseCommand;
+        } finally {
+            this.responseTable.remove(opaque);
+        }
+    }
+
+    public void invokeAsyncImpl(final Channel channel, final RemotingCommand request, final long timeoutMillis,
+        final InvokeCallback invokeCallback)
+        throws InterruptedException, RemotingTooMuchRequestException, RemotingTimeoutException, RemotingSendRequestException {
+        long beginStartTime = System.currentTimeMillis();
+        final int opaque = request.getOpaque();
+        boolean acquired = this.semaphoreAsync.tryAcquire(timeoutMillis, TimeUnit.MILLISECONDS);
+        if (acquired) {
+            final SemaphoreReleaseOnlyOnce once = new SemaphoreReleaseOnlyOnce(this.semaphoreAsync);
+            long costTime = System.currentTimeMillis() - beginStartTime;
+            if (timeoutMillis < costTime) {
+                once.release();
+                throw new RemotingTimeoutException("invokeAsyncImpl call timeout");
+            }
+
+            final ResponseFuture responseFuture = new ResponseFuture(channel, opaque, timeoutMillis - costTime, invokeCallback, once);
+            this.responseTable.put(opaque, responseFuture);
+            try {
+                channel.writeAndFlush(request).addListener(new ChannelFutureListener() {
+                    @Override
+                    public void operationComplete(ChannelFuture f) throws Exception {
+                        if (f.isSuccess()) {
+                            responseFuture.setSendRequestOK(true);
+                            return;
+                        }
+                        requestFail(opaque);
+                        log.warn("send a request command to channel <{}> failed.", RemotingHelper.parseChannelRemoteAddr(channel));
+                    }
+                });
+            } catch (Exception e) {
+                responseFuture.release();
+                log.warn("send a request command to channel <" + RemotingHelper.parseChannelRemoteAddr(channel) + "> Exception", e);
+                throw new RemotingSendRequestException(RemotingHelper.parseChannelRemoteAddr(channel), e);
+            }
+        } else {
+            if (timeoutMillis <= 0) {
+                throw new RemotingTooMuchRequestException("invokeAsyncImpl invoke too fast");
+            } else {
+                String info =
+                    String.format("invokeAsyncImpl tryAcquire semaphore timeout, %dms, waiting thread nums: %d semaphoreAsyncValue: %d",
+                        timeoutMillis,
+                        this.semaphoreAsync.getQueueLength(),
+                        this.semaphoreAsync.availablePermits()
+                    );
+                log.warn(info);
+                throw new RemotingTimeoutException(info);
+            }
+        }
+    }
      diff --git a/2020/07/05/聊一下-RocketMQ-的-NameServer-源码/index.html b/2020/07/05/聊一下-RocketMQ-的-NameServer-源码/index.html index 0d36fa9ada..ab95478589 100644 --- a/2020/07/05/聊一下-RocketMQ-的-NameServer-源码/index.html +++ b/2020/07/05/聊一下-RocketMQ-的-NameServer-源码/index.html @@ -4,7 +4,7 @@ - + @@ -26,14 +26,15 @@ var CONFIG = {"hostname":"nicksxs.me","root":"/","scheme":"Pisces","version":"7.8.0","exturl":false,"sidebar":{"position":"left","display":"post","padding":18,"offset":12,"onmobile":false},"copycode":{"enable":true,"show_result":false,"style":null},"back2top":{"enable":true,"sidebar":false,"scrollpercent":false},"bookmark":{"enable":false,"color":"#222","save":"auto"},"fancybox":true,"mediumzoom":false,"lazyload":true,"pangu":false,"comments":{"style":"tabs","active":null,"storage":true,"lazyload":false,"nav":null},"algolia":{"hits":{"per_page":10},"labels":{"input_placeholder":"Search for Posts","hits_empty":"We didn't find any results for the search: ${query}","hits_stats":"${hits} results found in ${time} ms"}},"localsearch":{"enable":false,"trigger":"auto","top_n_per_article":1,"unescape":false,"preload":false},"motion":{"enable":true,"async":false,"transition":{"post_block":"fadeIn","post_header":"slideDownIn","post_body":"slideDownIn","coll_header":"slideLeftIn","sidebar":"slideUpIn"}}}; - + - + + - + @@ -231,9 +232,8 @@       Posted on - - +       @@ -305,42 +305,607 @@

      前面介绍了，nameserver相当于dubbo的注册中心，用与管理broker，broker会在启动的时候注册到nameserver，并且会发送心跳给namaserver，nameserver负责保存活跃的broker，包括master和slave，同时保存topic和topic下的队列，以及filter列表，然后为producer和consumer的请求提供服务。

      -

      启动过程

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      public static void main(String[] args) {
              main0(args);
          }

          public static NamesrvController main0(String[] args) {

              try {
                  NamesrvController controller = createNamesrvController(args);
                  start(controller);
                  String tip = "The Name Server boot success. serializeType=" + RemotingCommand.getSerializeTypeConfigInThisServer();
                  log.info(tip);
                  System.out.printf("%s%n", tip);
                  return controller;
              } catch (Throwable e) {
                  e.printStackTrace();
                  System.exit(-1);
              }

              return null;
          }
      +

      启动过程

      public static void main(String[] args) {
+        main0(args);
+    }
+
+    public static NamesrvController main0(String[] args) {
+
+        try {
+            NamesrvController controller = createNamesrvController(args);
+            start(controller);
+            String tip = "The Name Server boot success. serializeType=" + RemotingCommand.getSerializeTypeConfigInThisServer();
+            log.info(tip);
+            System.out.printf("%s%n", tip);
+            return controller;
+        } catch (Throwable e) {
+            e.printStackTrace();
+            System.exit(-1);
+        }
+
+        return null;
+    }

      入口的代码时这样子，其实主要的逻辑在createNamesrvController和start方法，来看下这两个的实现

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      public static NamesrvController createNamesrvController(String[] args) throws IOException, JoranException {
              System.setProperty(RemotingCommand.REMOTING_VERSION_KEY, Integer.toString(MQVersion.CURRENT_VERSION));
              //PackageConflictDetect.detectFastjson();

              Options options = ServerUtil.buildCommandlineOptions(new Options());
              commandLine = ServerUtil.parseCmdLine("mqnamesrv", args, buildCommandlineOptions(options), new PosixParser());
              if (null == commandLine) {
                  System.exit(-1);
                  return null;
              }

              final NamesrvConfig namesrvConfig = new NamesrvConfig();
              final NettyServerConfig nettyServerConfig = new NettyServerConfig();
              nettyServerConfig.setListenPort(9876);
              if (commandLine.hasOption('c')) {
                  String file = commandLine.getOptionValue('c');
                  if (file != null) {
                      InputStream in = new BufferedInputStream(new FileInputStream(file));
                      properties = new Properties();
                      properties.load(in);
                      MixAll.properties2Object(properties, namesrvConfig);
                      MixAll.properties2Object(properties, nettyServerConfig);

                      namesrvConfig.setConfigStorePath(file);

                      System.out.printf("load config properties file OK, %s%n", file);
                      in.close();
                  }
              }

              if (commandLine.hasOption('p')) {
                  InternalLogger console = InternalLoggerFactory.getLogger(LoggerName.NAMESRV_CONSOLE_NAME);
                  MixAll.printObjectProperties(console, namesrvConfig);
                  MixAll.printObjectProperties(console, nettyServerConfig);
                  System.exit(0);
              }

              MixAll.properties2Object(ServerUtil.commandLine2Properties(commandLine), namesrvConfig);

              if (null == namesrvConfig.getRocketmqHome()) {
                  System.out.printf("Please set the %s variable in your environment to match the location of the RocketMQ installation%n", MixAll.ROCKETMQ_HOME_ENV);
                  System.exit(-2);
              }

              LoggerContext lc = (LoggerContext) LoggerFactory.getILoggerFactory();
              JoranConfigurator configurator = new JoranConfigurator();
              configurator.setContext(lc);
              lc.reset();
              configurator.doConfigure(namesrvConfig.getRocketmqHome() + "/conf/logback_namesrv.xml");

              log = InternalLoggerFactory.getLogger(LoggerName.NAMESRV_LOGGER_NAME);

              MixAll.printObjectProperties(log, namesrvConfig);
              MixAll.printObjectProperties(log, nettyServerConfig);

              final NamesrvController controller = new NamesrvController(namesrvConfig, nettyServerConfig);

              // remember all configs to prevent discard
              controller.getConfiguration().registerConfig(properties);

              return controller;
          }
      +
      public static NamesrvController createNamesrvController(String[] args) throws IOException, JoranException {
+        System.setProperty(RemotingCommand.REMOTING_VERSION_KEY, Integer.toString(MQVersion.CURRENT_VERSION));
+        //PackageConflictDetect.detectFastjson();
+
+        Options options = ServerUtil.buildCommandlineOptions(new Options());
+        commandLine = ServerUtil.parseCmdLine("mqnamesrv", args, buildCommandlineOptions(options), new PosixParser());
+        if (null == commandLine) {
+            System.exit(-1);
+            return null;
+        }
+
+        final NamesrvConfig namesrvConfig = new NamesrvConfig();
+        final NettyServerConfig nettyServerConfig = new NettyServerConfig();
+        nettyServerConfig.setListenPort(9876);
+        if (commandLine.hasOption('c')) {
+            String file = commandLine.getOptionValue('c');
+            if (file != null) {
+                InputStream in = new BufferedInputStream(new FileInputStream(file));
+                properties = new Properties();
+                properties.load(in);
+                MixAll.properties2Object(properties, namesrvConfig);
+                MixAll.properties2Object(properties, nettyServerConfig);
+
+                namesrvConfig.setConfigStorePath(file);
+
+                System.out.printf("load config properties file OK, %s%n", file);
+                in.close();
+            }
+        }
+
+        if (commandLine.hasOption('p')) {
+            InternalLogger console = InternalLoggerFactory.getLogger(LoggerName.NAMESRV_CONSOLE_NAME);
+            MixAll.printObjectProperties(console, namesrvConfig);
+            MixAll.printObjectProperties(console, nettyServerConfig);
+            System.exit(0);
+        }
+
+        MixAll.properties2Object(ServerUtil.commandLine2Properties(commandLine), namesrvConfig);
+
+        if (null == namesrvConfig.getRocketmqHome()) {
+            System.out.printf("Please set the %s variable in your environment to match the location of the RocketMQ installation%n", MixAll.ROCKETMQ_HOME_ENV);
+            System.exit(-2);
+        }
+
+        LoggerContext lc = (LoggerContext) LoggerFactory.getILoggerFactory();
+        JoranConfigurator configurator = new JoranConfigurator();
+        configurator.setContext(lc);
+        lc.reset();
+        configurator.doConfigure(namesrvConfig.getRocketmqHome() + "/conf/logback_namesrv.xml");
+
+        log = InternalLoggerFactory.getLogger(LoggerName.NAMESRV_LOGGER_NAME);
+
+        MixAll.printObjectProperties(log, namesrvConfig);
+        MixAll.printObjectProperties(log, nettyServerConfig);
+
+        final NamesrvController controller = new NamesrvController(namesrvConfig, nettyServerConfig);
+
+        // remember all configs to prevent discard
+        controller.getConfiguration().registerConfig(properties);
+
+        return controller;
+    }

      这个方法里其实主要是读取一些配置啥的，不是很复杂，

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      public static NamesrvController start(final NamesrvController controller) throws Exception {

              if (null == controller) {
                  throw new IllegalArgumentException("NamesrvController is null");
              }

              boolean initResult = controller.initialize();
              if (!initResult) {
                  controller.shutdown();
                  System.exit(-3);
              }

              Runtime.getRuntime().addShutdownHook(new ShutdownHookThread(log, new Callable<Void>() {
                  @Override
                  public Void call() throws Exception {
                      controller.shutdown();
                      return null;
                  }
              }));

              controller.start();

              return controller;
          }
      +
      public static NamesrvController start(final NamesrvController controller) throws Exception {
+
+        if (null == controller) {
+            throw new IllegalArgumentException("NamesrvController is null");
+        }
+
+        boolean initResult = controller.initialize();
+        if (!initResult) {
+            controller.shutdown();
+            System.exit(-3);
+        }
+
+        Runtime.getRuntime().addShutdownHook(new ShutdownHookThread(log, new Callable<Void>() {
+            @Override
+            public Void call() throws Exception {
+                controller.shutdown();
+                return null;
+            }
+        }));
+
+        controller.start();
+
+        return controller;
+    }

      这个start里主要关注initialize方法，后面就是一个停机的hook，来看下initialize方法

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      public boolean initialize() {

              this.kvConfigManager.load();

              this.remotingServer = new NettyRemotingServer(this.nettyServerConfig, this.brokerHousekeepingService);

              this.remotingExecutor =
                  Executors.newFixedThreadPool(nettyServerConfig.getServerWorkerThreads(), new ThreadFactoryImpl("RemotingExecutorThread_"));

              this.registerProcessor();

              this.scheduledExecutorService.scheduleAtFixedRate(new Runnable() {

                  @Override
                  public void run() {
                      NamesrvController.this.routeInfoManager.scanNotActiveBroker();
                  }
              }, 5, 10, TimeUnit.SECONDS);

              this.scheduledExecutorService.scheduleAtFixedRate(new Runnable() {

                  @Override
                  public void run() {
                      NamesrvController.this.kvConfigManager.printAllPeriodically();
                  }
              }, 1, 10, TimeUnit.MINUTES);

              if (TlsSystemConfig.tlsMode != TlsMode.DISABLED) {
                  // Register a listener to reload SslContext
                  try {
                      fileWatchService = new FileWatchService(
                          new String[] {
                              TlsSystemConfig.tlsServerCertPath,
                              TlsSystemConfig.tlsServerKeyPath,
                              TlsSystemConfig.tlsServerTrustCertPath
                          },
                          new FileWatchService.Listener() {
                              boolean certChanged, keyChanged = false;
                              @Override
                              public void onChanged(String path) {
                                  if (path.equals(TlsSystemConfig.tlsServerTrustCertPath)) {
                                      log.info("The trust certificate changed, reload the ssl context");
                                      reloadServerSslContext();
                                  }
                                  if (path.equals(TlsSystemConfig.tlsServerCertPath)) {
                                      certChanged = true;
                                  }
                                  if (path.equals(TlsSystemConfig.tlsServerKeyPath)) {
                                      keyChanged = true;
                                  }
                                  if (certChanged && keyChanged) {
                                      log.info("The certificate and private key changed, reload the ssl context");
                                      certChanged = keyChanged = false;
                                      reloadServerSslContext();
                                  }
                              }
                              private void reloadServerSslContext() {
                                  ((NettyRemotingServer) remotingServer).loadSslContext();
                              }
                          });
                  } catch (Exception e) {
                      log.warn("FileWatchService created error, can't load the certificate dynamically");
                  }
              }

              return true;
          }
      +
      public boolean initialize() {
+
+        this.kvConfigManager.load();
+
+        this.remotingServer = new NettyRemotingServer(this.nettyServerConfig, this.brokerHousekeepingService);
+
+        this.remotingExecutor =
+            Executors.newFixedThreadPool(nettyServerConfig.getServerWorkerThreads(), new ThreadFactoryImpl("RemotingExecutorThread_"));
+
+        this.registerProcessor();
+
+        this.scheduledExecutorService.scheduleAtFixedRate(new Runnable() {
+
+            @Override
+            public void run() {
+                NamesrvController.this.routeInfoManager.scanNotActiveBroker();
+            }
+        }, 5, 10, TimeUnit.SECONDS);
+
+        this.scheduledExecutorService.scheduleAtFixedRate(new Runnable() {
+
+            @Override
+            public void run() {
+                NamesrvController.this.kvConfigManager.printAllPeriodically();
+            }
+        }, 1, 10, TimeUnit.MINUTES);
+
+        if (TlsSystemConfig.tlsMode != TlsMode.DISABLED) {
+            // Register a listener to reload SslContext
+            try {
+                fileWatchService = new FileWatchService(
+                    new String[] {
+                        TlsSystemConfig.tlsServerCertPath,
+                        TlsSystemConfig.tlsServerKeyPath,
+                        TlsSystemConfig.tlsServerTrustCertPath
+                    },
+                    new FileWatchService.Listener() {
+                        boolean certChanged, keyChanged = false;
+                        @Override
+                        public void onChanged(String path) {
+                            if (path.equals(TlsSystemConfig.tlsServerTrustCertPath)) {
+                                log.info("The trust certificate changed, reload the ssl context");
+                                reloadServerSslContext();
+                            }
+                            if (path.equals(TlsSystemConfig.tlsServerCertPath)) {
+                                certChanged = true;
+                            }
+                            if (path.equals(TlsSystemConfig.tlsServerKeyPath)) {
+                                keyChanged = true;
+                            }
+                            if (certChanged && keyChanged) {
+                                log.info("The certificate and private key changed, reload the ssl context");
+                                certChanged = keyChanged = false;
+                                reloadServerSslContext();
+                            }
+                        }
+                        private void reloadServerSslContext() {
+                            ((NettyRemotingServer) remotingServer).loadSslContext();
+                        }
+                    });
+            } catch (Exception e) {
+                log.warn("FileWatchService created error, can't load the certificate dynamically");
+            }
+        }
+
+        return true;
+    }

      这里的kvConfigManager主要是来加载NameServer的配置参数，存到org.apache.rocketmq.namesrv.kvconfig.KVConfigManager#configTable中，然后是以BrokerHousekeepingService对象为参数初始化NettyRemotingServer对象，BrokerHousekeepingService对象作为该Netty连接中Socket链接的监听器（ChannelEventListener）；监听与Broker建立的渠道的状态（空闲、关闭、异常三个状态），并调用BrokerHousekeepingService的相应onChannel方法。其中渠道的空闲、关闭、异常状态均调用RouteInfoManager.onChannelDestory方法处理。这个BrokerHousekeepingService可以字面化地理解为broker的管家服务，这个类内部三个状态方法其实都是调用的org.apache.rocketmq.namesrv.NamesrvController#getRouteInfoManager方法，而这个RouteInfoManager里面的对象有这些

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      public class RouteInfoManager {
          private static final InternalLogger log = InternalLoggerFactory.getLogger(LoggerName.NAMESRV_LOGGER_NAME);
          private final static long BROKER_CHANNEL_EXPIRED_TIME = 1000 * 60 * 2;
          private final ReadWriteLock lock = new ReentrantReadWriteLock();
        // topic与queue的对应关系
          private final HashMap<String/* topic */, List<QueueData>> topicQueueTable;
        // Broker名称与broker属性的map
          private final HashMap<String/* brokerName */, BrokerData> brokerAddrTable;
        // 集群与broker集合的对应关系
          private final HashMap<String/* clusterName */, Set<String/* brokerName */>> clusterAddrTable;
        // 活跃的broker信息
          private final HashMap<String/* brokerAddr */, BrokerLiveInfo> brokerLiveTable;
        // Broker地址与过滤器
          private final HashMap<String/* brokerAddr */, List<String>/* Filter Server */> filterServerTable;
      +
      public class RouteInfoManager {
+    private static final InternalLogger log = InternalLoggerFactory.getLogger(LoggerName.NAMESRV_LOGGER_NAME);
+    private final static long BROKER_CHANNEL_EXPIRED_TIME = 1000 * 60 * 2;
+    private final ReadWriteLock lock = new ReentrantReadWriteLock();
+  // topic与queue的对应关系
+    private final HashMap<String/* topic */, List<QueueData>> topicQueueTable;
+  // Broker名称与broker属性的map
+    private final HashMap<String/* brokerName */, BrokerData> brokerAddrTable;
+  // 集群与broker集合的对应关系
+    private final HashMap<String/* clusterName */, Set<String/* brokerName */>> clusterAddrTable;
+  // 活跃的broker信息
+    private final HashMap<String/* brokerAddr */, BrokerLiveInfo> brokerLiveTable;
+  // Broker地址与过滤器
+    private final HashMap<String/* brokerAddr */, List<String>/* Filter Server */> filterServerTable;

      然后接下去就是初始化了一个线程池，然后注册默认的处理类this.registerProcessor();默认都是这个处理器去处理请求 org.apache.rocketmq.namesrv.processor.DefaultRequestProcessor#DefaultRequestProcessor然后是初始化两个定时任务

      第一是每10秒检查一遍Broker的状态的定时任务，调用scanNotActiveBroker方法；遍历brokerLiveTable集合，查看每个broker的最后更新时间（BrokerLiveInfo.lastUpdateTimestamp）是否超过2分钟，若超过则关闭该broker的渠道并调用RouteInfoManager.onChannelDestory方法清理RouteInfoManager类的topicQueueTable、brokerAddrTable、clusterAddrTable、filterServerTable成员变量。

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      this.scheduledExecutorService.scheduleAtFixedRate(new Runnable() {

                  @Override
                  public void run() {
                      NamesrvController.this.routeInfoManager.scanNotActiveBroker();
                  }
              }, 5, 10, TimeUnit.SECONDS);
      public void scanNotActiveBroker() {
              Iterator<Entry<String, BrokerLiveInfo>> it = this.brokerLiveTable.entrySet().iterator();
              while (it.hasNext()) {
                  Entry<String, BrokerLiveInfo> next = it.next();
                  long last = next.getValue().getLastUpdateTimestamp();
                  if ((last + BROKER_CHANNEL_EXPIRED_TIME) < System.currentTimeMillis()) {
                      RemotingUtil.closeChannel(next.getValue().getChannel());
                      it.remove();
                      log.warn("The broker channel expired, {} {}ms", next.getKey(), BROKER_CHANNEL_EXPIRED_TIME);
                      this.onChannelDestroy(next.getKey(), next.getValue().getChannel());
                  }
              }
          }

          public void onChannelDestroy(String remoteAddr, Channel channel) {
              String brokerAddrFound = null;
              if (channel != null) {
                  try {
                      try {
                          this.lock.readLock().lockInterruptibly();
                          Iterator<Entry<String, BrokerLiveInfo>> itBrokerLiveTable =
                              this.brokerLiveTable.entrySet().iterator();
                          while (itBrokerLiveTable.hasNext()) {
                              Entry<String, BrokerLiveInfo> entry = itBrokerLiveTable.next();
                              if (entry.getValue().getChannel() == channel) {
                                  brokerAddrFound = entry.getKey();
                                  break;
                              }
                          }
                      } finally {
                          this.lock.readLock().unlock();
                      }
                  } catch (Exception e) {
                      log.error("onChannelDestroy Exception", e);
                  }
              }

              if (null == brokerAddrFound) {
                  brokerAddrFound = remoteAddr;
              } else {
                  log.info("the broker's channel destroyed, {}, clean it's data structure at once", brokerAddrFound);
              }

              if (brokerAddrFound != null && brokerAddrFound.length() > 0) {

                  try {
                      try {
                          this.lock.writeLock().lockInterruptibly();
                          this.brokerLiveTable.remove(brokerAddrFound);
                          this.filterServerTable.remove(brokerAddrFound);
                          String brokerNameFound = null;
                          boolean removeBrokerName = false;
                          Iterator<Entry<String, BrokerData>> itBrokerAddrTable =
                              this.brokerAddrTable.entrySet().iterator();
                          while (itBrokerAddrTable.hasNext() && (null == brokerNameFound)) {
                              BrokerData brokerData = itBrokerAddrTable.next().getValue();

                              Iterator<Entry<Long, String>> it = brokerData.getBrokerAddrs().entrySet().iterator();
                              while (it.hasNext()) {
                                  Entry<Long, String> entry = it.next();
                                  Long brokerId = entry.getKey();
                                  String brokerAddr = entry.getValue();
                                  if (brokerAddr.equals(brokerAddrFound)) {
                                      brokerNameFound = brokerData.getBrokerName();
                                      it.remove();
                                      log.info("remove brokerAddr[{}, {}] from brokerAddrTable, because channel destroyed",
                                          brokerId, brokerAddr);
                                      break;
                                  }
                              }

                              if (brokerData.getBrokerAddrs().isEmpty()) {
                                  removeBrokerName = true;
                                  itBrokerAddrTable.remove();
                                  log.info("remove brokerName[{}] from brokerAddrTable, because channel destroyed",
                                      brokerData.getBrokerName());
                              }
                          }

                          if (brokerNameFound != null && removeBrokerName) {
                              Iterator<Entry<String, Set<String>>> it = this.clusterAddrTable.entrySet().iterator();
                              while (it.hasNext()) {
                                  Entry<String, Set<String>> entry = it.next();
                                  String clusterName = entry.getKey();
                                  Set<String> brokerNames = entry.getValue();
                                  boolean removed = brokerNames.remove(brokerNameFound);
                                  if (removed) {
                                      log.info("remove brokerName[{}], clusterName[{}] from clusterAddrTable, because channel destroyed",
                                          brokerNameFound, clusterName);

                                      if (brokerNames.isEmpty()) {
                                          log.info("remove the clusterName[{}] from clusterAddrTable, because channel destroyed and no broker in this cluster",
                                              clusterName);
                                          it.remove();
                                      }

                                      break;
                                  }
                              }
                          }

                          if (removeBrokerName) {
                              Iterator<Entry<String, List<QueueData>>> itTopicQueueTable =
                                  this.topicQueueTable.entrySet().iterator();
                              while (itTopicQueueTable.hasNext()) {
                                  Entry<String, List<QueueData>> entry = itTopicQueueTable.next();
                                  String topic = entry.getKey();
                                  List<QueueData> queueDataList = entry.getValue();

                                  Iterator<QueueData> itQueueData = queueDataList.iterator();
                                  while (itQueueData.hasNext()) {
                                      QueueData queueData = itQueueData.next();
                                      if (queueData.getBrokerName().equals(brokerNameFound)) {
                                          itQueueData.remove();
                                          log.info("remove topic[{} {}], from topicQueueTable, because channel destroyed",
                                              topic, queueData);
                                      }
                                  }

                                  if (queueDataList.isEmpty()) {
                                      itTopicQueueTable.remove();
                                      log.info("remove topic[{}] all queue, from topicQueueTable, because channel destroyed",
                                          topic);
                                  }
                              }
                          }
                      } finally {
                          this.lock.writeLock().unlock();
                      }
                  } catch (Exception e) {
                      log.error("onChannelDestroy Exception", e);
                  }
              }
          }
      +
      this.scheduledExecutorService.scheduleAtFixedRate(new Runnable() {
+
+            @Override
+            public void run() {
+                NamesrvController.this.routeInfoManager.scanNotActiveBroker();
+            }
+        }, 5, 10, TimeUnit.SECONDS);
+public void scanNotActiveBroker() {
+        Iterator<Entry<String, BrokerLiveInfo>> it = this.brokerLiveTable.entrySet().iterator();
+        while (it.hasNext()) {
+            Entry<String, BrokerLiveInfo> next = it.next();
+            long last = next.getValue().getLastUpdateTimestamp();
+            if ((last + BROKER_CHANNEL_EXPIRED_TIME) < System.currentTimeMillis()) {
+                RemotingUtil.closeChannel(next.getValue().getChannel());
+                it.remove();
+                log.warn("The broker channel expired, {} {}ms", next.getKey(), BROKER_CHANNEL_EXPIRED_TIME);
+                this.onChannelDestroy(next.getKey(), next.getValue().getChannel());
+            }
+        }
+    }
+
+    public void onChannelDestroy(String remoteAddr, Channel channel) {
+        String brokerAddrFound = null;
+        if (channel != null) {
+            try {
+                try {
+                    this.lock.readLock().lockInterruptibly();
+                    Iterator<Entry<String, BrokerLiveInfo>> itBrokerLiveTable =
+                        this.brokerLiveTable.entrySet().iterator();
+                    while (itBrokerLiveTable.hasNext()) {
+                        Entry<String, BrokerLiveInfo> entry = itBrokerLiveTable.next();
+                        if (entry.getValue().getChannel() == channel) {
+                            brokerAddrFound = entry.getKey();
+                            break;
+                        }
+                    }
+                } finally {
+                    this.lock.readLock().unlock();
+                }
+            } catch (Exception e) {
+                log.error("onChannelDestroy Exception", e);
+            }
+        }
+
+        if (null == brokerAddrFound) {
+            brokerAddrFound = remoteAddr;
+        } else {
+            log.info("the broker's channel destroyed, {}, clean it's data structure at once", brokerAddrFound);
+        }
+
+        if (brokerAddrFound != null && brokerAddrFound.length() > 0) {
+
+            try {
+                try {
+                    this.lock.writeLock().lockInterruptibly();
+                    this.brokerLiveTable.remove(brokerAddrFound);
+                    this.filterServerTable.remove(brokerAddrFound);
+                    String brokerNameFound = null;
+                    boolean removeBrokerName = false;
+                    Iterator<Entry<String, BrokerData>> itBrokerAddrTable =
+                        this.brokerAddrTable.entrySet().iterator();
+                    while (itBrokerAddrTable.hasNext() && (null == brokerNameFound)) {
+                        BrokerData brokerData = itBrokerAddrTable.next().getValue();
+
+                        Iterator<Entry<Long, String>> it = brokerData.getBrokerAddrs().entrySet().iterator();
+                        while (it.hasNext()) {
+                            Entry<Long, String> entry = it.next();
+                            Long brokerId = entry.getKey();
+                            String brokerAddr = entry.getValue();
+                            if (brokerAddr.equals(brokerAddrFound)) {
+                                brokerNameFound = brokerData.getBrokerName();
+                                it.remove();
+                                log.info("remove brokerAddr[{}, {}] from brokerAddrTable, because channel destroyed",
+                                    brokerId, brokerAddr);
+                                break;
+                            }
+                        }
+
+                        if (brokerData.getBrokerAddrs().isEmpty()) {
+                            removeBrokerName = true;
+                            itBrokerAddrTable.remove();
+                            log.info("remove brokerName[{}] from brokerAddrTable, because channel destroyed",
+                                brokerData.getBrokerName());
+                        }
+                    }
+
+                    if (brokerNameFound != null && removeBrokerName) {
+                        Iterator<Entry<String, Set<String>>> it = this.clusterAddrTable.entrySet().iterator();
+                        while (it.hasNext()) {
+                            Entry<String, Set<String>> entry = it.next();
+                            String clusterName = entry.getKey();
+                            Set<String> brokerNames = entry.getValue();
+                            boolean removed = brokerNames.remove(brokerNameFound);
+                            if (removed) {
+                                log.info("remove brokerName[{}], clusterName[{}] from clusterAddrTable, because channel destroyed",
+                                    brokerNameFound, clusterName);
+
+                                if (brokerNames.isEmpty()) {
+                                    log.info("remove the clusterName[{}] from clusterAddrTable, because channel destroyed and no broker in this cluster",
+                                        clusterName);
+                                    it.remove();
+                                }
+
+                                break;
+                            }
+                        }
+                    }
+
+                    if (removeBrokerName) {
+                        Iterator<Entry<String, List<QueueData>>> itTopicQueueTable =
+                            this.topicQueueTable.entrySet().iterator();
+                        while (itTopicQueueTable.hasNext()) {
+                            Entry<String, List<QueueData>> entry = itTopicQueueTable.next();
+                            String topic = entry.getKey();
+                            List<QueueData> queueDataList = entry.getValue();
+
+                            Iterator<QueueData> itQueueData = queueDataList.iterator();
+                            while (itQueueData.hasNext()) {
+                                QueueData queueData = itQueueData.next();
+                                if (queueData.getBrokerName().equals(brokerNameFound)) {
+                                    itQueueData.remove();
+                                    log.info("remove topic[{} {}], from topicQueueTable, because channel destroyed",
+                                        topic, queueData);
+                                }
+                            }
+
+                            if (queueDataList.isEmpty()) {
+                                itTopicQueueTable.remove();
+                                log.info("remove topic[{}] all queue, from topicQueueTable, because channel destroyed",
+                                    topic);
+                            }
+                        }
+                    }
+                } finally {
+                    this.lock.writeLock().unlock();
+                }
+            } catch (Exception e) {
+                log.error("onChannelDestroy Exception", e);
+            }
+        }
+    }

      第二个是每10分钟打印一次NameServer的配置参数。即KVConfigManager.configTable变量的内容。

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      this.scheduledExecutorService.scheduleAtFixedRate(new Runnable() {

                  @Override
                  public void run() {
                      NamesrvController.this.kvConfigManager.printAllPeriodically();
                  }
              }, 1, 10, TimeUnit.MINUTES);
      +
      this.scheduledExecutorService.scheduleAtFixedRate(new Runnable() {
+
+            @Override
+            public void run() {
+                NamesrvController.this.kvConfigManager.printAllPeriodically();
+            }
+        }, 1, 10, TimeUnit.MINUTES);

      然后这个初始化就差不多完成了，后面只需要把remotingServer start一下就好了

      处理请求

      直接上代码，其实主体是swtich case去判断

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      @Override
          public RemotingCommand processRequest(ChannelHandlerContext ctx,
              RemotingCommand request) throws RemotingCommandException {

              if (ctx != null) {
                  log.debug("receive request, {} {} {}",
                      request.getCode(),
                      RemotingHelper.parseChannelRemoteAddr(ctx.channel()),
                      request);
              }


              switch (request.getCode()) {
                  case RequestCode.PUT_KV_CONFIG:
                      return this.putKVConfig(ctx, request);
                  case RequestCode.GET_KV_CONFIG:
                      return this.getKVConfig(ctx, request);
                  case RequestCode.DELETE_KV_CONFIG:
                      return this.deleteKVConfig(ctx, request);
                  case RequestCode.QUERY_DATA_VERSION:
                      return queryBrokerTopicConfig(ctx, request);
                  case RequestCode.REGISTER_BROKER:
                      Version brokerVersion = MQVersion.value2Version(request.getVersion());
                      if (brokerVersion.ordinal() >= MQVersion.Version.V3_0_11.ordinal()) {
                          return this.registerBrokerWithFilterServer(ctx, request);
                      } else {
                          return this.registerBroker(ctx, request);
                      }
                  case RequestCode.UNREGISTER_BROKER:
                      return this.unregisterBroker(ctx, request);
                  case RequestCode.GET_ROUTEINTO_BY_TOPIC:
                      return this.getRouteInfoByTopic(ctx, request);
                  case RequestCode.GET_BROKER_CLUSTER_INFO:
                      return this.getBrokerClusterInfo(ctx, request);
                  case RequestCode.WIPE_WRITE_PERM_OF_BROKER:
                      return this.wipeWritePermOfBroker(ctx, request);
                  case RequestCode.GET_ALL_TOPIC_LIST_FROM_NAMESERVER:
                      return getAllTopicListFromNameserver(ctx, request);
                  case RequestCode.DELETE_TOPIC_IN_NAMESRV:
                      return deleteTopicInNamesrv(ctx, request);
                  case RequestCode.GET_KVLIST_BY_NAMESPACE:
                      return this.getKVListByNamespace(ctx, request);
                  case RequestCode.GET_TOPICS_BY_CLUSTER:
                      return this.getTopicsByCluster(ctx, request);
                  case RequestCode.GET_SYSTEM_TOPIC_LIST_FROM_NS:
                      return this.getSystemTopicListFromNs(ctx, request);
                  case RequestCode.GET_UNIT_TOPIC_LIST:
                      return this.getUnitTopicList(ctx, request);
                  case RequestCode.GET_HAS_UNIT_SUB_TOPIC_LIST:
                      return this.getHasUnitSubTopicList(ctx, request);
                  case RequestCode.GET_HAS_UNIT_SUB_UNUNIT_TOPIC_LIST:
                      return this.getHasUnitSubUnUnitTopicList(ctx, request);
                  case RequestCode.UPDATE_NAMESRV_CONFIG:
                      return this.updateConfig(ctx, request);
                  case RequestCode.GET_NAMESRV_CONFIG:
                      return this.getConfig(ctx, request);
                  default:
                      break;
              }
              return null;
          }
      +
      @Override
+    public RemotingCommand processRequest(ChannelHandlerContext ctx,
+        RemotingCommand request) throws RemotingCommandException {
+
+        if (ctx != null) {
+            log.debug("receive request, {} {} {}",
+                request.getCode(),
+                RemotingHelper.parseChannelRemoteAddr(ctx.channel()),
+                request);
+        }
+
+
+        switch (request.getCode()) {
+            case RequestCode.PUT_KV_CONFIG:
+                return this.putKVConfig(ctx, request);
+            case RequestCode.GET_KV_CONFIG:
+                return this.getKVConfig(ctx, request);
+            case RequestCode.DELETE_KV_CONFIG:
+                return this.deleteKVConfig(ctx, request);
+            case RequestCode.QUERY_DATA_VERSION:
+                return queryBrokerTopicConfig(ctx, request);
+            case RequestCode.REGISTER_BROKER:
+                Version brokerVersion = MQVersion.value2Version(request.getVersion());
+                if (brokerVersion.ordinal() >= MQVersion.Version.V3_0_11.ordinal()) {
+                    return this.registerBrokerWithFilterServer(ctx, request);
+                } else {
+                    return this.registerBroker(ctx, request);
+                }
+            case RequestCode.UNREGISTER_BROKER:
+                return this.unregisterBroker(ctx, request);
+            case RequestCode.GET_ROUTEINTO_BY_TOPIC:
+                return this.getRouteInfoByTopic(ctx, request);
+            case RequestCode.GET_BROKER_CLUSTER_INFO:
+                return this.getBrokerClusterInfo(ctx, request);
+            case RequestCode.WIPE_WRITE_PERM_OF_BROKER:
+                return this.wipeWritePermOfBroker(ctx, request);
+            case RequestCode.GET_ALL_TOPIC_LIST_FROM_NAMESERVER:
+                return getAllTopicListFromNameserver(ctx, request);
+            case RequestCode.DELETE_TOPIC_IN_NAMESRV:
+                return deleteTopicInNamesrv(ctx, request);
+            case RequestCode.GET_KVLIST_BY_NAMESPACE:
+                return this.getKVListByNamespace(ctx, request);
+            case RequestCode.GET_TOPICS_BY_CLUSTER:
+                return this.getTopicsByCluster(ctx, request);
+            case RequestCode.GET_SYSTEM_TOPIC_LIST_FROM_NS:
+                return this.getSystemTopicListFromNs(ctx, request);
+            case RequestCode.GET_UNIT_TOPIC_LIST:
+                return this.getUnitTopicList(ctx, request);
+            case RequestCode.GET_HAS_UNIT_SUB_TOPIC_LIST:
+                return this.getHasUnitSubTopicList(ctx, request);
+            case RequestCode.GET_HAS_UNIT_SUB_UNUNIT_TOPIC_LIST:
+                return this.getHasUnitSubUnUnitTopicList(ctx, request);
+            case RequestCode.UPDATE_NAMESRV_CONFIG:
+                return this.updateConfig(ctx, request);
+            case RequestCode.GET_NAMESRV_CONFIG:
+                return this.getConfig(ctx, request);
+            default:
+                break;
+        }
+        return null;
+    }

      以broker注册为例，

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      case RequestCode.REGISTER_BROKER:
                      Version brokerVersion = MQVersion.value2Version(request.getVersion());
                      if (brokerVersion.ordinal() >= MQVersion.Version.V3_0_11.ordinal()) {
                          return this.registerBrokerWithFilterServer(ctx, request);
                      } else {
                          return this.registerBroker(ctx, request);
                      }
      +
      case RequestCode.REGISTER_BROKER:
+                Version brokerVersion = MQVersion.value2Version(request.getVersion());
+                if (brokerVersion.ordinal() >= MQVersion.Version.V3_0_11.ordinal()) {
+                    return this.registerBrokerWithFilterServer(ctx, request);
+                } else {
+                    return this.registerBroker(ctx, request);
+                }

      做了个简单的版本管理，我们看下前面一个的代码

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      public RemotingCommand registerBrokerWithFilterServer(ChannelHandlerContext ctx, RemotingCommand request)
          throws RemotingCommandException {
          final RemotingCommand response = RemotingCommand.createResponseCommand(RegisterBrokerResponseHeader.class);
          final RegisterBrokerResponseHeader responseHeader = (RegisterBrokerResponseHeader) response.readCustomHeader();
          final RegisterBrokerRequestHeader requestHeader =
              (RegisterBrokerRequestHeader) request.decodeCommandCustomHeader(RegisterBrokerRequestHeader.class);

          if (!checksum(ctx, request, requestHeader)) {
              response.setCode(ResponseCode.SYSTEM_ERROR);
              response.setRemark("crc32 not match");
              return response;
          }

          RegisterBrokerBody registerBrokerBody = new RegisterBrokerBody();

          if (request.getBody() != null) {
              try {
                  registerBrokerBody = RegisterBrokerBody.decode(request.getBody(), requestHeader.isCompressed());
              } catch (Exception e) {
                  throw new RemotingCommandException("Failed to decode RegisterBrokerBody", e);
              }
          } else {
              registerBrokerBody.getTopicConfigSerializeWrapper().getDataVersion().setCounter(new AtomicLong(0));
              registerBrokerBody.getTopicConfigSerializeWrapper().getDataVersion().setTimestamp(0);
          }

          RegisterBrokerResult result = this.namesrvController.getRouteInfoManager().registerBroker(
              requestHeader.getClusterName(),
              requestHeader.getBrokerAddr(),
              requestHeader.getBrokerName(),
              requestHeader.getBrokerId(),
              requestHeader.getHaServerAddr(),
              registerBrokerBody.getTopicConfigSerializeWrapper(),
              registerBrokerBody.getFilterServerList(),
              ctx.channel());

          responseHeader.setHaServerAddr(result.getHaServerAddr());
          responseHeader.setMasterAddr(result.getMasterAddr());

          byte[] jsonValue = this.namesrvController.getKvConfigManager().getKVListByNamespace(NamesrvUtil.NAMESPACE_ORDER_TOPIC_CONFIG);
          response.setBody(jsonValue);

          response.setCode(ResponseCode.SUCCESS);
          response.setRemark(null);
          return response;
      }
      +
      public RemotingCommand registerBrokerWithFilterServer(ChannelHandlerContext ctx, RemotingCommand request)
+    throws RemotingCommandException {
+    final RemotingCommand response = RemotingCommand.createResponseCommand(RegisterBrokerResponseHeader.class);
+    final RegisterBrokerResponseHeader responseHeader = (RegisterBrokerResponseHeader) response.readCustomHeader();
+    final RegisterBrokerRequestHeader requestHeader =
+        (RegisterBrokerRequestHeader) request.decodeCommandCustomHeader(RegisterBrokerRequestHeader.class);
+
+    if (!checksum(ctx, request, requestHeader)) {
+        response.setCode(ResponseCode.SYSTEM_ERROR);
+        response.setRemark("crc32 not match");
+        return response;
+    }
+
+    RegisterBrokerBody registerBrokerBody = new RegisterBrokerBody();
+
+    if (request.getBody() != null) {
+        try {
+            registerBrokerBody = RegisterBrokerBody.decode(request.getBody(), requestHeader.isCompressed());
+        } catch (Exception e) {
+            throw new RemotingCommandException("Failed to decode RegisterBrokerBody", e);
+        }
+    } else {
+        registerBrokerBody.getTopicConfigSerializeWrapper().getDataVersion().setCounter(new AtomicLong(0));
+        registerBrokerBody.getTopicConfigSerializeWrapper().getDataVersion().setTimestamp(0);
+    }
+
+    RegisterBrokerResult result = this.namesrvController.getRouteInfoManager().registerBroker(
+        requestHeader.getClusterName(),
+        requestHeader.getBrokerAddr(),
+        requestHeader.getBrokerName(),
+        requestHeader.getBrokerId(),
+        requestHeader.getHaServerAddr(),
+        registerBrokerBody.getTopicConfigSerializeWrapper(),
+        registerBrokerBody.getFilterServerList(),
+        ctx.channel());
+
+    responseHeader.setHaServerAddr(result.getHaServerAddr());
+    responseHeader.setMasterAddr(result.getMasterAddr());
+
+    byte[] jsonValue = this.namesrvController.getKvConfigManager().getKVListByNamespace(NamesrvUtil.NAMESPACE_ORDER_TOPIC_CONFIG);
+    response.setBody(jsonValue);
+
+    response.setCode(ResponseCode.SUCCESS);
+    response.setRemark(null);
+    return response;
+}

      可以看到主要的逻辑还是在org.apache.rocketmq.namesrv.routeinfo.RouteInfoManager#registerBroker这个方法里

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      public RegisterBrokerResult registerBroker(
              final String clusterName,
              final String brokerAddr,
              final String brokerName,
              final long brokerId,
              final String haServerAddr,
              final TopicConfigSerializeWrapper topicConfigWrapper,
              final List<String> filterServerList,
              final Channel channel) {
              RegisterBrokerResult result = new RegisterBrokerResult();
              try {
                  try {
                      this.lock.writeLock().lockInterruptibly();

                    // 更新这个clusterAddrTable
                      Set<String> brokerNames = this.clusterAddrTable.get(clusterName);
                      if (null == brokerNames) {
                          brokerNames = new HashSet<String>();
                          this.clusterAddrTable.put(clusterName, brokerNames);
                      }
                      brokerNames.add(brokerName);

                      boolean registerFirst = false;

                    // 更新brokerAddrTable
                      BrokerData brokerData = this.brokerAddrTable.get(brokerName);
                      if (null == brokerData) {
                          registerFirst = true;
                          brokerData = new BrokerData(clusterName, brokerName, new HashMap<Long, String>());
                          this.brokerAddrTable.put(brokerName, brokerData);
                      }
                      Map<Long, String> brokerAddrsMap = brokerData.getBrokerAddrs();
                      //Switch slave to master: first remove <1, IP:PORT> in namesrv, then add <0, IP:PORT>
                      //The same IP:PORT must only have one record in brokerAddrTable
                      Iterator<Entry<Long, String>> it = brokerAddrsMap.entrySet().iterator();
                      while (it.hasNext()) {
                          Entry<Long, String> item = it.next();
                          if (null != brokerAddr && brokerAddr.equals(item.getValue()) && brokerId != item.getKey()) {
                              it.remove();
                          }
                      }

                      String oldAddr = brokerData.getBrokerAddrs().put(brokerId, brokerAddr);
                      registerFirst = registerFirst || (null == oldAddr);

                    // 更新了org.apache.rocketmq.namesrv.routeinfo.RouteInfoManager#topicQueueTable中的数据
                      if (null != topicConfigWrapper
                          && MixAll.MASTER_ID == brokerId) {
                          if (this.isBrokerTopicConfigChanged(brokerAddr, topicConfigWrapper.getDataVersion())
                              || registerFirst) {
                              ConcurrentMap<String, TopicConfig> tcTable =
                                  topicConfigWrapper.getTopicConfigTable();
                              if (tcTable != null) {
                                  for (Map.Entry<String, TopicConfig> entry : tcTable.entrySet()) {
                                      this.createAndUpdateQueueData(brokerName, entry.getValue());
                                  }
                              }
                          }
                      }

                    // 更新活跃broker信息
                      BrokerLiveInfo prevBrokerLiveInfo = this.brokerLiveTable.put(brokerAddr,
                          new BrokerLiveInfo(
                              System.currentTimeMillis(),
                              topicConfigWrapper.getDataVersion(),
                              channel,
                              haServerAddr));
                      if (null == prevBrokerLiveInfo) {
                          log.info("new broker registered, {} HAServer: {}", brokerAddr, haServerAddr);
                      }

                    // 处理filter
                      if (filterServerList != null) {
                          if (filterServerList.isEmpty()) {
                              this.filterServerTable.remove(brokerAddr);
                          } else {
                              this.filterServerTable.put(brokerAddr, filterServerList);
                          }
                      }

                    // 当当前broker非master时返回master信息
                      if (MixAll.MASTER_ID != brokerId) {
                          String masterAddr = brokerData.getBrokerAddrs().get(MixAll.MASTER_ID);
                          if (masterAddr != null) {
                              BrokerLiveInfo brokerLiveInfo = this.brokerLiveTable.get(masterAddr);
                              if (brokerLiveInfo != null) {
                                  result.setHaServerAddr(brokerLiveInfo.getHaServerAddr());
                                  result.setMasterAddr(masterAddr);
                              }
                          }
                      }
                  } finally {
                      this.lock.writeLock().unlock();
                  }
              } catch (Exception e) {
                  log.error("registerBroker Exception", e);
              }

              return result;
          }
      +
      public RegisterBrokerResult registerBroker(
+        final String clusterName,
+        final String brokerAddr,
+        final String brokerName,
+        final long brokerId,
+        final String haServerAddr,
+        final TopicConfigSerializeWrapper topicConfigWrapper,
+        final List<String> filterServerList,
+        final Channel channel) {
+        RegisterBrokerResult result = new RegisterBrokerResult();
+        try {
+            try {
+                this.lock.writeLock().lockInterruptibly();
+
+              // 更新这个clusterAddrTable
+                Set<String> brokerNames = this.clusterAddrTable.get(clusterName);
+                if (null == brokerNames) {
+                    brokerNames = new HashSet<String>();
+                    this.clusterAddrTable.put(clusterName, brokerNames);
+                }
+                brokerNames.add(brokerName);
+
+                boolean registerFirst = false;
+
+              // 更新brokerAddrTable
+                BrokerData brokerData = this.brokerAddrTable.get(brokerName);
+                if (null == brokerData) {
+                    registerFirst = true;
+                    brokerData = new BrokerData(clusterName, brokerName, new HashMap<Long, String>());
+                    this.brokerAddrTable.put(brokerName, brokerData);
+                }
+                Map<Long, String> brokerAddrsMap = brokerData.getBrokerAddrs();
+                //Switch slave to master: first remove <1, IP:PORT> in namesrv, then add <0, IP:PORT>
+                //The same IP:PORT must only have one record in brokerAddrTable
+                Iterator<Entry<Long, String>> it = brokerAddrsMap.entrySet().iterator();
+                while (it.hasNext()) {
+                    Entry<Long, String> item = it.next();
+                    if (null != brokerAddr && brokerAddr.equals(item.getValue()) && brokerId != item.getKey()) {
+                        it.remove();
+                    }
+                }
+
+                String oldAddr = brokerData.getBrokerAddrs().put(brokerId, brokerAddr);
+                registerFirst = registerFirst || (null == oldAddr);
+
+              // 更新了org.apache.rocketmq.namesrv.routeinfo.RouteInfoManager#topicQueueTable中的数据
+                if (null != topicConfigWrapper
+                    && MixAll.MASTER_ID == brokerId) {
+                    if (this.isBrokerTopicConfigChanged(brokerAddr, topicConfigWrapper.getDataVersion())
+                        || registerFirst) {
+                        ConcurrentMap<String, TopicConfig> tcTable =
+                            topicConfigWrapper.getTopicConfigTable();
+                        if (tcTable != null) {
+                            for (Map.Entry<String, TopicConfig> entry : tcTable.entrySet()) {
+                                this.createAndUpdateQueueData(brokerName, entry.getValue());
+                            }
+                        }
+                    }
+                }
+
+              // 更新活跃broker信息
+                BrokerLiveInfo prevBrokerLiveInfo = this.brokerLiveTable.put(brokerAddr,
+                    new BrokerLiveInfo(
+                        System.currentTimeMillis(),
+                        topicConfigWrapper.getDataVersion(),
+                        channel,
+                        haServerAddr));
+                if (null == prevBrokerLiveInfo) {
+                    log.info("new broker registered, {} HAServer: {}", brokerAddr, haServerAddr);
+                }
+
+              // 处理filter
+                if (filterServerList != null) {
+                    if (filterServerList.isEmpty()) {
+                        this.filterServerTable.remove(brokerAddr);
+                    } else {
+                        this.filterServerTable.put(brokerAddr, filterServerList);
+                    }
+                }
+
+              // 当当前broker非master时返回master信息
+                if (MixAll.MASTER_ID != brokerId) {
+                    String masterAddr = brokerData.getBrokerAddrs().get(MixAll.MASTER_ID);
+                    if (masterAddr != null) {
+                        BrokerLiveInfo brokerLiveInfo = this.brokerLiveTable.get(masterAddr);
+                        if (brokerLiveInfo != null) {
+                            result.setHaServerAddr(brokerLiveInfo.getHaServerAddr());
+                            result.setMasterAddr(masterAddr);
+                        }
+                    }
+                }
+            } finally {
+                this.lock.writeLock().unlock();
+            }
+        } catch (Exception e) {
+            log.error("registerBroker Exception", e);
+        }
+
+        return result;
+    }

      这个是注册 broker 的逻辑，再看下根据 topic 获取 broker 信息和 topic 信息，org.apache.rocketmq.namesrv.processor.DefaultRequestProcessor#getRouteInfoByTopic 主要是这个方法的逻辑

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      public RemotingCommand getRouteInfoByTopic(ChannelHandlerContext ctx,
              RemotingCommand request) throws RemotingCommandException {
              final RemotingCommand response = RemotingCommand.createResponseCommand(null);
              final GetRouteInfoRequestHeader requestHeader =
                  (GetRouteInfoRequestHeader) request.decodeCommandCustomHeader(GetRouteInfoRequestHeader.class);

              TopicRouteData topicRouteData = this.namesrvController.getRouteInfoManager().pickupTopicRouteData(requestHeader.getTopic());

              if (topicRouteData != null) {
                  if (this.namesrvController.getNamesrvConfig().isOrderMessageEnable()) {
                      String orderTopicConf =
                          this.namesrvController.getKvConfigManager().getKVConfig(NamesrvUtil.NAMESPACE_ORDER_TOPIC_CONFIG,
                              requestHeader.getTopic());
                      topicRouteData.setOrderTopicConf(orderTopicConf);
                  }

                  byte[] content = topicRouteData.encode();
                  response.setBody(content);
                  response.setCode(ResponseCode.SUCCESS);
                  response.setRemark(null);
                  return response;
              }

              response.setCode(ResponseCode.TOPIC_NOT_EXIST);
              response.setRemark("No topic route info in name server for the topic: " + requestHeader.getTopic()
                  + FAQUrl.suggestTodo(FAQUrl.APPLY_TOPIC_URL));
              return response;
          }
      +
      public RemotingCommand getRouteInfoByTopic(ChannelHandlerContext ctx,
+        RemotingCommand request) throws RemotingCommandException {
+        final RemotingCommand response = RemotingCommand.createResponseCommand(null);
+        final GetRouteInfoRequestHeader requestHeader =
+            (GetRouteInfoRequestHeader) request.decodeCommandCustomHeader(GetRouteInfoRequestHeader.class);
+
+        TopicRouteData topicRouteData = this.namesrvController.getRouteInfoManager().pickupTopicRouteData(requestHeader.getTopic());
+
+        if (topicRouteData != null) {
+            if (this.namesrvController.getNamesrvConfig().isOrderMessageEnable()) {
+                String orderTopicConf =
+                    this.namesrvController.getKvConfigManager().getKVConfig(NamesrvUtil.NAMESPACE_ORDER_TOPIC_CONFIG,
+                        requestHeader.getTopic());
+                topicRouteData.setOrderTopicConf(orderTopicConf);
+            }
+
+            byte[] content = topicRouteData.encode();
+            response.setBody(content);
+            response.setCode(ResponseCode.SUCCESS);
+            response.setRemark(null);
+            return response;
+        }
+
+        response.setCode(ResponseCode.TOPIC_NOT_EXIST);
+        response.setRemark("No topic route info in name server for the topic: " + requestHeader.getTopic()
+            + FAQUrl.suggestTodo(FAQUrl.APPLY_TOPIC_URL));
+        return response;
+    }

      首先调用org.apache.rocketmq.namesrv.routeinfo.RouteInfoManager#pickupTopicRouteData从org.apache.rocketmq.namesrv.routeinfo.RouteInfoManager#topicQueueTable获取到org.apache.rocketmq.common.protocol.route.QueueData这里面存了 brokerName，再通过org.apache.rocketmq.namesrv.routeinfo.RouteInfoManager#brokerAddrTable里获取到 broker 的地址信息等，然后再获取 orderMessage 的配置。

      简要分析了下 RocketMQ 的 NameServer 的代码，比较粗粒度。

      @@ -491,7 +1056,7 @@
      -
      1. 1. 启动过程
      2. 2. 处理请求
      +
      1. 1. 启动过程
      2. 2. 处理请求
      diff --git a/2020/07/11/2020年中总结/index.html b/2020/07/11/2020年中总结/index.html index 72ed759594..944d3a37d2 100644 --- a/2020/07/11/2020年中总结/index.html +++ b/2020/07/11/2020年中总结/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,13 @@ + - + - + @@ -227,9 +228,8 @@       Posted on - - +       @@ -308,13 +308,13 @@
      在老丈人家的小工记四
    • -
      周末我在老丈人家打了天小工
      +
      从丁仲礼被美国制裁聊点啥
    • -
      从清华美院学姐聊聊我们身边的恶人
      +
      关于公共交通再吐个槽
    • -
      在老丈人家的小工记三
      +
      周末我在老丈人家打了天小工
    diff --git a/2020/07/19/聊聊-RocketMQ-的-Broker-源码/index.html b/2020/07/19/聊聊-RocketMQ-的-Broker-源码/index.html index fe7ee559da..14bef7275f 100644 --- a/2020/07/19/聊聊-RocketMQ-的-Broker-源码/index.html +++ b/2020/07/19/聊聊-RocketMQ-的-Broker-源码/index.html @@ -4,7 +4,7 @@ - + @@ -26,22 +26,23 @@ var CONFIG = {"hostname":"nicksxs.me","root":"/","scheme":"Pisces","version":"7.8.0","exturl":false,"sidebar":{"position":"left","display":"post","padding":18,"offset":12,"onmobile":false},"copycode":{"enable":true,"show_result":false,"style":null},"back2top":{"enable":true,"sidebar":false,"scrollpercent":false},"bookmark":{"enable":false,"color":"#222","save":"auto"},"fancybox":true,"mediumzoom":false,"lazyload":true,"pangu":false,"comments":{"style":"tabs","active":null,"storage":true,"lazyload":false,"nav":null},"algolia":{"hits":{"per_page":10},"labels":{"input_placeholder":"Search for Posts","hits_empty":"We didn't find any results for the search: ${query}","hits_stats":"${hits} results found in ${time} ms"}},"localsearch":{"enable":false,"trigger":"auto","top_n_per_article":1,"unescape":false,"preload":false},"motion":{"enable":true,"async":false,"transition":{"post_block":"fadeIn","post_header":"slideDownIn","post_body":"slideDownIn","coll_header":"slideLeftIn","sidebar":"slideUpIn"}}}; - + - + + - + - + @@ -231,9 +232,8 @@     Posted on - - +     @@ -306,26 +306,117 @@

    broker 的启动形式有点类似于 NameServer，都是服务类型的，跟 Consumer 差别比较大，

    首先是org.apache.rocketmq.broker.BrokerStartup中的 main 函数，org.apache.rocketmq.broker.BrokerStartup#createBrokerController基本就是读取参数，这里差点把最核心的初始化给漏了，

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    final BrokerController controller = new BrokerController(
                    brokerConfig,
                    nettyServerConfig,
                    nettyClientConfig,
                    messageStoreConfig);
                // remember all configs to prevent discard
                controller.getConfiguration().registerConfig(properties);

                boolean initResult = controller.initialize();
    +
    final BrokerController controller = new BrokerController(
+                brokerConfig,
+                nettyServerConfig,
+                nettyClientConfig,
+                messageStoreConfig);
+            // remember all configs to prevent discard
+            controller.getConfiguration().registerConfig(properties);
+
+            boolean initResult = controller.initialize();

    前面是以 broker 配置，netty 的服务端和客户端配置，以及消息存储配置在实例化 BrokerController，然后就是初始化了

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    public boolean initialize() throws CloneNotSupportedException {
            boolean result = this.topicConfigManager.load();

            result = result && this.consumerOffsetManager.load();
            result = result && this.subscriptionGroupManager.load();
            result = result && this.consumerFilterManager.load();
    +
    public boolean initialize() throws CloneNotSupportedException {
+        boolean result = this.topicConfigManager.load();
+
+        result = result && this.consumerOffsetManager.load();
+        result = result && this.subscriptionGroupManager.load();
+        result = result && this.consumerFilterManager.load();

    前面这些就是各个配置的 load 了，然后是个我认为比较重要的部分messageStore 的实例化，

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    if (result) {
        try {
            this.messageStore =
                new DefaultMessageStore(this.messageStoreConfig, this.brokerStatsManager, this.messageArrivingListener,
                    this.brokerConfig);
            if (messageStoreConfig.isEnableDLegerCommitLog()) {
                DLedgerRoleChangeHandler roleChangeHandler = new DLedgerRoleChangeHandler(this, (DefaultMessageStore) messageStore);
                ((DLedgerCommitLog)((DefaultMessageStore) messageStore).getCommitLog()).getdLedgerServer().getdLedgerLeaderElector().addRoleChangeHandler(roleChangeHandler);
            }
            this.brokerStats = new BrokerStats((DefaultMessageStore) this.messageStore);
            //load plugin
            MessageStorePluginContext context = new MessageStorePluginContext(messageStoreConfig, brokerStatsManager, messageArrivingListener, brokerConfig);
            this.messageStore = MessageStoreFactory.build(context, this.messageStore);
            this.messageStore.getDispatcherList().addFirst(new CommitLogDispatcherCalcBitMap(this.brokerConfig, this.consumerFilterManager));
        } catch (IOException e) {
            result = false;
            log.error("Failed to initialize", e);
        }
    }

    result = result && this.messageStore.load();
    +
    if (result) {
+    try {
+        this.messageStore =
+            new DefaultMessageStore(this.messageStoreConfig, this.brokerStatsManager, this.messageArrivingListener,
+                this.brokerConfig);
+        if (messageStoreConfig.isEnableDLegerCommitLog()) {
+            DLedgerRoleChangeHandler roleChangeHandler = new DLedgerRoleChangeHandler(this, (DefaultMessageStore) messageStore);
+            ((DLedgerCommitLog)((DefaultMessageStore) messageStore).getCommitLog()).getdLedgerServer().getdLedgerLeaderElector().addRoleChangeHandler(roleChangeHandler);
+        }
+        this.brokerStats = new BrokerStats((DefaultMessageStore) this.messageStore);
+        //load plugin
+        MessageStorePluginContext context = new MessageStorePluginContext(messageStoreConfig, brokerStatsManager, messageArrivingListener, brokerConfig);
+        this.messageStore = MessageStoreFactory.build(context, this.messageStore);
+        this.messageStore.getDispatcherList().addFirst(new CommitLogDispatcherCalcBitMap(this.brokerConfig, this.consumerFilterManager));
+    } catch (IOException e) {
+        result = false;
+        log.error("Failed to initialize", e);
+    }
+}
+
+result = result && this.messageStore.load();

    先是实例化，实例化构造函数里的代码比较重要，重点看一下

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    public DefaultMessageStore(final MessageStoreConfig messageStoreConfig, final BrokerStatsManager brokerStatsManager,
            final MessageArrivingListener messageArrivingListener, final BrokerConfig brokerConfig) throws IOException {
            this.messageArrivingListener = messageArrivingListener;
            this.brokerConfig = brokerConfig;
            this.messageStoreConfig = messageStoreConfig;
            this.brokerStatsManager = brokerStatsManager;
            this.allocateMappedFileService = new AllocateMappedFileService(this);
            if (messageStoreConfig.isEnableDLegerCommitLog()) {
                this.commitLog = new DLedgerCommitLog(this);
            } else {
                this.commitLog = new CommitLog(this);
            }
            this.consumeQueueTable = new ConcurrentHashMap<>(32);

            this.flushConsumeQueueService = new FlushConsumeQueueService();
            this.cleanCommitLogService = new CleanCommitLogService();
            this.cleanConsumeQueueService = new CleanConsumeQueueService();
            this.storeStatsService = new StoreStatsService();
            this.indexService = new IndexService(this);
            if (!messageStoreConfig.isEnableDLegerCommitLog()) {
                this.haService = new HAService(this);
            } else {
                this.haService = null;
            }
            this.reputMessageService = new ReputMessageService();

            this.scheduleMessageService = new ScheduleMessageService(this);

            this.transientStorePool = new TransientStorePool(messageStoreConfig);

            if (messageStoreConfig.isTransientStorePoolEnable()) {
                this.transientStorePool.init();
            }

            this.allocateMappedFileService.start();

            this.indexService.start();

            this.dispatcherList = new LinkedList<>();
            this.dispatcherList.addLast(new CommitLogDispatcherBuildConsumeQueue());
            this.dispatcherList.addLast(new CommitLogDispatcherBuildIndex());

            File file = new File(StorePathConfigHelper.getLockFile(messageStoreConfig.getStorePathRootDir()));
            MappedFile.ensureDirOK(file.getParent());
            lockFile = new RandomAccessFile(file, "rw");
        }
    +
    public DefaultMessageStore(final MessageStoreConfig messageStoreConfig, final BrokerStatsManager brokerStatsManager,
+        final MessageArrivingListener messageArrivingListener, final BrokerConfig brokerConfig) throws IOException {
+        this.messageArrivingListener = messageArrivingListener;
+        this.brokerConfig = brokerConfig;
+        this.messageStoreConfig = messageStoreConfig;
+        this.brokerStatsManager = brokerStatsManager;
+        this.allocateMappedFileService = new AllocateMappedFileService(this);
+        if (messageStoreConfig.isEnableDLegerCommitLog()) {
+            this.commitLog = new DLedgerCommitLog(this);
+        } else {
+            this.commitLog = new CommitLog(this);
+        }
+        this.consumeQueueTable = new ConcurrentHashMap<>(32);
+
+        this.flushConsumeQueueService = new FlushConsumeQueueService();
+        this.cleanCommitLogService = new CleanCommitLogService();
+        this.cleanConsumeQueueService = new CleanConsumeQueueService();
+        this.storeStatsService = new StoreStatsService();
+        this.indexService = new IndexService(this);
+        if (!messageStoreConfig.isEnableDLegerCommitLog()) {
+            this.haService = new HAService(this);
+        } else {
+            this.haService = null;
+        }
+        this.reputMessageService = new ReputMessageService();
+
+        this.scheduleMessageService = new ScheduleMessageService(this);
+
+        this.transientStorePool = new TransientStorePool(messageStoreConfig);
+
+        if (messageStoreConfig.isTransientStorePoolEnable()) {
+            this.transientStorePool.init();
+        }
+
+        this.allocateMappedFileService.start();
+
+        this.indexService.start();
+
+        this.dispatcherList = new LinkedList<>();
+        this.dispatcherList.addLast(new CommitLogDispatcherBuildConsumeQueue());
+        this.dispatcherList.addLast(new CommitLogDispatcherBuildIndex());
+
+        File file = new File(StorePathConfigHelper.getLockFile(messageStoreConfig.getStorePathRootDir()));
+        MappedFile.ensureDirOK(file.getParent());
+        lockFile = new RandomAccessFile(file, "rw");
+    }

    这里面有很多类，不过先把从构造函数里传进来的忽略下，接下来就是 AllocateMappedFileService 这个service，前面看过文章的可能会根据上面的代码猜到，这也是个 ServiceThread，如果是对RocketMQ 有所了解的可能从名字可以看出这个类是关于 RocketMQ 消息怎么落盘的，当需要创建MappedFile时（在MapedFileQueue.getLastMapedFile方法中），向该线程的requestQueue队列中放入AllocateRequest请求对象，该线程会在后台监听该队列，并在后台创建MapedFile对象，即同时创建了物理文件。然后是创建了 IndexService 服务线程，用来给创建索引；还有是FlushConsumeQueueService是将ConsumeQueue 刷入磁盘；CleanCommitLogService用来清理过期的 CommitLog，默认是 72 小时以上；CleanConsumeQueueService是将小于最新的 CommitLog 偏移量的 ConsumeQueue 清理掉；StoreStatsService是储存统计服务；HAService用于CommitLog 的主备同步；ScheduleMessageService用于定时消息；还有就是这个ReputMessageService非常重要，就是由它实现了将 CommitLog 以 topic+queue 纬度构建 ConsumeQueue，后面TransientStorePool是异步刷盘时的存储buffer，也可以从后面的判断中看出来

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    public boolean isTransientStorePoolEnable() {
            return transientStorePoolEnable && FlushDiskType.ASYNC_FLUSH == getFlushDiskType()
                && BrokerRole.SLAVE != getBrokerRole();
        }
    +
    public boolean isTransientStorePoolEnable() {
+        return transientStorePoolEnable && FlushDiskType.ASYNC_FLUSH == getFlushDiskType()
+            && BrokerRole.SLAVE != getBrokerRole();
+    }

    再然后就是启动两个服务线程，dispatcherList是为CommitLog文件转发请求，差不多这个初始化就这些内容。

    然后回到外层，下面是主备切换的配置，然后是数据统计，接着是存储插件加载，然后是往转发器链表里再加一个过滤器

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    if (messageStoreConfig.isEnableDLegerCommitLog()) {
                DLedgerRoleChangeHandler roleChangeHandler = new DLedgerRoleChangeHandler(this, (DefaultMessageStore) messageStore);
                ((DLedgerCommitLog)((DefaultMessageStore) messageStore).getCommitLog()).getdLedgerServer().getdLedgerLeaderElector().addRoleChangeHandler(roleChangeHandler);
            }
            this.brokerStats = new BrokerStats((DefaultMessageStore) this.messageStore);
            //load plugin
            MessageStorePluginContext context = new MessageStorePluginContext(messageStoreConfig, brokerStatsManager, messageArrivingListener, brokerConfig);
            this.messageStore = MessageStoreFactory.build(context, this.messageStore);
            this.messageStore.getDispatcherList().addFirst(new CommitLogDispatcherCalcBitMap(this.brokerConfig, this.consumerFilterManager));
    +
    if (messageStoreConfig.isEnableDLegerCommitLog()) {
+            DLedgerRoleChangeHandler roleChangeHandler = new DLedgerRoleChangeHandler(this, (DefaultMessageStore) messageStore);
+            ((DLedgerCommitLog)((DefaultMessageStore) messageStore).getCommitLog()).getdLedgerServer().getdLedgerLeaderElector().addRoleChangeHandler(roleChangeHandler);
+        }
+        this.brokerStats = new BrokerStats((DefaultMessageStore) this.messageStore);
+        //load plugin
+        MessageStorePluginContext context = new MessageStorePluginContext(messageStoreConfig, brokerStatsManager, messageArrivingListener, brokerConfig);
+        this.messageStore = MessageStoreFactory.build(context, this.messageStore);
+        this.messageStore.getDispatcherList().addFirst(new CommitLogDispatcherCalcBitMap(this.brokerConfig, this.consumerFilterManager));

    接下来就是org.apache.rocketmq.store.MessageStore#load的过程了，

    -

    1) 调用ScheduleMessageService.load方法，初始化延迟级别列表。将这些级别（”1s 5s 10s 30s 1m 2m 3m 4m 5m 6m 7m 8m 9m 10m 20m 30m 1h 2h”）的延时存入延迟级别delayLevelTable：ConcurrentHashMap<Integer /* level /, Long/ delay timeMillis */>变量中，例如1s的kv值为1:1000,5s的kv值为2:5000，key值依次类推；每个延迟级别即为一个队列。

    +
      +
    1. 调用ScheduleMessageService.load方法，初始化延迟级别列表。将这些级别（”1s 5s 10s 30s 1m 2m 3m 4m 5m 6m 7m 8m 9m 10m 20m 30m 1h 2h”）的延时存入延迟级别delayLevelTable：ConcurrentHashMap<Integer /* level */, Long/* delay timeMillis */>变量中，例如1s的kv值为1:1000,5s的kv值为2:5000，key值依次类推；每个延迟级别即为一个队列。
      2. +

    2)调用CommitLog.load方法，在此方法中调用MapedFileQueue.load方法，将$HOME /store/commitlog目录下的所有文件加载到MapedFileQueue的List变量中；

    3)调用DefaultMessageStore.loadConsumeQueue方法加载consumequeue文件数据到DefaultMessageStore.consumeQueueTable集合中。

    初始化StoreCheckPoint对象，加载$HOME/store/checkpoint文件，该文件记录三个字段值，分别是物理队列消息时间戳、逻辑队列消息时间戳、索引队列消息时间戳。

    @@ -337,21 +428,373 @@

    BrokerController.this.consumerFilterManager.persist();持久化consumerFilter

    BrokerController.this.protectBroker(); 保护 broker，消费慢，不让继续投递

    BrokerController.this.printWaterMark(); 打印水位

    -

    log.info("dispatch behind commit log {} bytes", BrokerController.this.getMessageStore().dispatchBehindBytes()); 检查落后程度

    +

    log.info("dispatch behind commit log {} bytes", BrokerController.this.getMessageStore().dispatchBehindBytes()); 检查落后程度

    BrokerController.this.brokerOuterAPI.fetchNameServerAddr(); 定时获取 nameserver

    BrokerController.this.printMasterAndSlaveDiff(); 打印主从不一致

    然后是 tsl，初始化事务消息，初始化 RPCHook

    请把害怕打到公屏上🤦‍♂️，从线程池名字和调用的方法应该可以看出大部分的用途

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    this.remotingServer = new NettyRemotingServer(this.nettyServerConfig, this.clientHousekeepingService);
                NettyServerConfig fastConfig = (NettyServerConfig) this.nettyServerConfig.clone();
                fastConfig.setListenPort(nettyServerConfig.getListenPort() - 2);
                this.fastRemotingServer = new NettyRemotingServer(fastConfig, this.clientHousekeepingService);
                this.sendMessageExecutor = new BrokerFixedThreadPoolExecutor(
                    this.brokerConfig.getSendMessageThreadPoolNums(),
                    this.brokerConfig.getSendMessageThreadPoolNums(),
                    1000 * 60,
                    TimeUnit.MILLISECONDS,
                    this.sendThreadPoolQueue,
                    new ThreadFactoryImpl("SendMessageThread_"));

                this.pullMessageExecutor = new BrokerFixedThreadPoolExecutor(
                    this.brokerConfig.getPullMessageThreadPoolNums(),
                    this.brokerConfig.getPullMessageThreadPoolNums(),
                    1000 * 60,
                    TimeUnit.MILLISECONDS,
                    this.pullThreadPoolQueue,
                    new ThreadFactoryImpl("PullMessageThread_"));

                this.replyMessageExecutor = new BrokerFixedThreadPoolExecutor(
                    this.brokerConfig.getProcessReplyMessageThreadPoolNums(),
                    this.brokerConfig.getProcessReplyMessageThreadPoolNums(),
                    1000 * 60,
                    TimeUnit.MILLISECONDS,
                    this.replyThreadPoolQueue,
                    new ThreadFactoryImpl("ProcessReplyMessageThread_"));

                this.queryMessageExecutor = new BrokerFixedThreadPoolExecutor(
                    this.brokerConfig.getQueryMessageThreadPoolNums(),
                    this.brokerConfig.getQueryMessageThreadPoolNums(),
                    1000 * 60,
                    TimeUnit.MILLISECONDS,
                    this.queryThreadPoolQueue,
                    new ThreadFactoryImpl("QueryMessageThread_"));

                this.adminBrokerExecutor =
                    Executors.newFixedThreadPool(this.brokerConfig.getAdminBrokerThreadPoolNums(), new ThreadFactoryImpl(
                        "AdminBrokerThread_"));

                this.clientManageExecutor = new ThreadPoolExecutor(
                    this.brokerConfig.getClientManageThreadPoolNums(),
                    this.brokerConfig.getClientManageThreadPoolNums(),
                    1000 * 60,
                    TimeUnit.MILLISECONDS,
                    this.clientManagerThreadPoolQueue,
                    new ThreadFactoryImpl("ClientManageThread_"));

                this.heartbeatExecutor = new BrokerFixedThreadPoolExecutor(
                    this.brokerConfig.getHeartbeatThreadPoolNums(),
                    this.brokerConfig.getHeartbeatThreadPoolNums(),
                    1000 * 60,
                    TimeUnit.MILLISECONDS,
                    this.heartbeatThreadPoolQueue,
                    new ThreadFactoryImpl("HeartbeatThread_", true));

                this.endTransactionExecutor = new BrokerFixedThreadPoolExecutor(
                    this.brokerConfig.getEndTransactionThreadPoolNums(),
                    this.brokerConfig.getEndTransactionThreadPoolNums(),
                    1000 * 60,
                    TimeUnit.MILLISECONDS,
                    this.endTransactionThreadPoolQueue,
                    new ThreadFactoryImpl("EndTransactionThread_"));

                this.consumerManageExecutor =
                    Executors.newFixedThreadPool(this.brokerConfig.getConsumerManageThreadPoolNums(), new ThreadFactoryImpl(
                        "ConsumerManageThread_"));

                this.registerProcessor();

                final long initialDelay = UtilAll.computeNextMorningTimeMillis() - System.currentTimeMillis();
                final long period = 1000 * 60 * 60 * 24;
                this.scheduledExecutorService.scheduleAtFixedRate(new Runnable() {
                    @Override
                    public void run() {
                        try {
                            BrokerController.this.getBrokerStats().record();
                        } catch (Throwable e) {
                            log.error("schedule record error.", e);
                        }
                    }
                }, initialDelay, period, TimeUnit.MILLISECONDS);

                this.scheduledExecutorService.scheduleAtFixedRate(new Runnable() {
                    @Override
                    public void run() {
                        try {
                            BrokerController.this.consumerOffsetManager.persist();
                        } catch (Throwable e) {
                            log.error("schedule persist consumerOffset error.", e);
                        }
                    }
                }, 1000 * 10, this.brokerConfig.getFlushConsumerOffsetInterval(), TimeUnit.MILLISECONDS);

                this.scheduledExecutorService.scheduleAtFixedRate(new Runnable() {
                    @Override
                    public void run() {
                        try {
                            BrokerController.this.consumerFilterManager.persist();
                        } catch (Throwable e) {
                            log.error("schedule persist consumer filter error.", e);
                        }
                    }
                }, 1000 * 10, 1000 * 10, TimeUnit.MILLISECONDS);

                this.scheduledExecutorService.scheduleAtFixedRate(new Runnable() {
                    @Override
                    public void run() {
                        try {
                            BrokerController.this.protectBroker();
                        } catch (Throwable e) {
                            log.error("protectBroker error.", e);
                        }
                    }
                }, 3, 3, TimeUnit.MINUTES);

                this.scheduledExecutorService.scheduleAtFixedRate(new Runnable() {
                    @Override
                    public void run() {
                        try {
                            BrokerController.this.printWaterMark();
                        } catch (Throwable e) {
                            log.error("printWaterMark error.", e);
                        }
                    }
                }, 10, 1, TimeUnit.SECONDS);

                this.scheduledExecutorService.scheduleAtFixedRate(new Runnable() {

                    @Override
                    public void run() {
                        try {
                            log.info("dispatch behind commit log {} bytes", BrokerController.this.getMessageStore().dispatchBehindBytes());
                        } catch (Throwable e) {
                            log.error("schedule dispatchBehindBytes error.", e);
                        }
                    }
                }, 1000 * 10, 1000 * 60, TimeUnit.MILLISECONDS);

                if (this.brokerConfig.getNamesrvAddr() != null) {
                    this.brokerOuterAPI.updateNameServerAddressList(this.brokerConfig.getNamesrvAddr());
                    log.info("Set user specified name server address: {}", this.brokerConfig.getNamesrvAddr());
                } else if (this.brokerConfig.isFetchNamesrvAddrByAddressServer()) {
                    this.scheduledExecutorService.scheduleAtFixedRate(new Runnable() {

                        @Override
                        public void run() {
                            try {
                                BrokerController.this.brokerOuterAPI.fetchNameServerAddr();
                            } catch (Throwable e) {
                                log.error("ScheduledTask fetchNameServerAddr exception", e);
                            }
                        }
                    }, 1000 * 10, 1000 * 60 * 2, TimeUnit.MILLISECONDS);
                }

                if (!messageStoreConfig.isEnableDLegerCommitLog()) {
                    if (BrokerRole.SLAVE == this.messageStoreConfig.getBrokerRole()) {
                        if (this.messageStoreConfig.getHaMasterAddress() != null && this.messageStoreConfig.getHaMasterAddress().length() >= 6) {
                            this.messageStore.updateHaMasterAddress(this.messageStoreConfig.getHaMasterAddress());
                            this.updateMasterHAServerAddrPeriodically = false;
                        } else {
                            this.updateMasterHAServerAddrPeriodically = true;
                        }
                    } else {
                        this.scheduledExecutorService.scheduleAtFixedRate(new Runnable() {
                            @Override
                            public void run() {
                                try {
                                    BrokerController.this.printMasterAndSlaveDiff();
                                } catch (Throwable e) {
                                    log.error("schedule printMasterAndSlaveDiff error.", e);
                                }
                            }
                        }, 1000 * 10, 1000 * 60, TimeUnit.MILLISECONDS);
                    }
                }

                if (TlsSystemConfig.tlsMode != TlsMode.DISABLED) {
                    // Register a listener to reload SslContext
                    try {
                        fileWatchService = new FileWatchService(
                            new String[] {
                                TlsSystemConfig.tlsServerCertPath,
                                TlsSystemConfig.tlsServerKeyPath,
                                TlsSystemConfig.tlsServerTrustCertPath
                            },
                            new FileWatchService.Listener() {
                                boolean certChanged, keyChanged = false;

                                @Override
                                public void onChanged(String path) {
                                    if (path.equals(TlsSystemConfig.tlsServerTrustCertPath)) {
                                        log.info("The trust certificate changed, reload the ssl context");
                                        reloadServerSslContext();
                                    }
                                    if (path.equals(TlsSystemConfig.tlsServerCertPath)) {
                                        certChanged = true;
                                    }
                                    if (path.equals(TlsSystemConfig.tlsServerKeyPath)) {
                                        keyChanged = true;
                                    }
                                    if (certChanged && keyChanged) {
                                        log.info("The certificate and private key changed, reload the ssl context");
                                        certChanged = keyChanged = false;
                                        reloadServerSslContext();
                                    }
                                }

                                private void reloadServerSslContext() {
                                    ((NettyRemotingServer) remotingServer).loadSslContext();
                                    ((NettyRemotingServer) fastRemotingServer).loadSslContext();
                                }
                            });
                    } catch (Exception e) {
                        log.warn("FileWatchService created error, can't load the certificate dynamically");
                    }
                }
                initialTransaction();
                initialAcl();
                initialRpcHooks();
            }
            return result;
    +
    this.remotingServer = new NettyRemotingServer(this.nettyServerConfig, this.clientHousekeepingService);
+            NettyServerConfig fastConfig = (NettyServerConfig) this.nettyServerConfig.clone();
+            fastConfig.setListenPort(nettyServerConfig.getListenPort() - 2);
+            this.fastRemotingServer = new NettyRemotingServer(fastConfig, this.clientHousekeepingService);
+            this.sendMessageExecutor = new BrokerFixedThreadPoolExecutor(
+                this.brokerConfig.getSendMessageThreadPoolNums(),
+                this.brokerConfig.getSendMessageThreadPoolNums(),
+                1000 * 60,
+                TimeUnit.MILLISECONDS,
+                this.sendThreadPoolQueue,
+                new ThreadFactoryImpl("SendMessageThread_"));
+
+            this.pullMessageExecutor = new BrokerFixedThreadPoolExecutor(
+                this.brokerConfig.getPullMessageThreadPoolNums(),
+                this.brokerConfig.getPullMessageThreadPoolNums(),
+                1000 * 60,
+                TimeUnit.MILLISECONDS,
+                this.pullThreadPoolQueue,
+                new ThreadFactoryImpl("PullMessageThread_"));
+
+            this.replyMessageExecutor = new BrokerFixedThreadPoolExecutor(
+                this.brokerConfig.getProcessReplyMessageThreadPoolNums(),
+                this.brokerConfig.getProcessReplyMessageThreadPoolNums(),
+                1000 * 60,
+                TimeUnit.MILLISECONDS,
+                this.replyThreadPoolQueue,
+                new ThreadFactoryImpl("ProcessReplyMessageThread_"));
+
+            this.queryMessageExecutor = new BrokerFixedThreadPoolExecutor(
+                this.brokerConfig.getQueryMessageThreadPoolNums(),
+                this.brokerConfig.getQueryMessageThreadPoolNums(),
+                1000 * 60,
+                TimeUnit.MILLISECONDS,
+                this.queryThreadPoolQueue,
+                new ThreadFactoryImpl("QueryMessageThread_"));
+
+            this.adminBrokerExecutor =
+                Executors.newFixedThreadPool(this.brokerConfig.getAdminBrokerThreadPoolNums(), new ThreadFactoryImpl(
+                    "AdminBrokerThread_"));
+
+            this.clientManageExecutor = new ThreadPoolExecutor(
+                this.brokerConfig.getClientManageThreadPoolNums(),
+                this.brokerConfig.getClientManageThreadPoolNums(),
+                1000 * 60,
+                TimeUnit.MILLISECONDS,
+                this.clientManagerThreadPoolQueue,
+                new ThreadFactoryImpl("ClientManageThread_"));
+
+            this.heartbeatExecutor = new BrokerFixedThreadPoolExecutor(
+                this.brokerConfig.getHeartbeatThreadPoolNums(),
+                this.brokerConfig.getHeartbeatThreadPoolNums(),
+                1000 * 60,
+                TimeUnit.MILLISECONDS,
+                this.heartbeatThreadPoolQueue,
+                new ThreadFactoryImpl("HeartbeatThread_", true));
+
+            this.endTransactionExecutor = new BrokerFixedThreadPoolExecutor(
+                this.brokerConfig.getEndTransactionThreadPoolNums(),
+                this.brokerConfig.getEndTransactionThreadPoolNums(),
+                1000 * 60,
+                TimeUnit.MILLISECONDS,
+                this.endTransactionThreadPoolQueue,
+                new ThreadFactoryImpl("EndTransactionThread_"));
+
+            this.consumerManageExecutor =
+                Executors.newFixedThreadPool(this.brokerConfig.getConsumerManageThreadPoolNums(), new ThreadFactoryImpl(
+                    "ConsumerManageThread_"));
+
+            this.registerProcessor();
+
+            final long initialDelay = UtilAll.computeNextMorningTimeMillis() - System.currentTimeMillis();
+            final long period = 1000 * 60 * 60 * 24;
+            this.scheduledExecutorService.scheduleAtFixedRate(new Runnable() {
+                @Override
+                public void run() {
+                    try {
+                        BrokerController.this.getBrokerStats().record();
+                    } catch (Throwable e) {
+                        log.error("schedule record error.", e);
+                    }
+                }
+            }, initialDelay, period, TimeUnit.MILLISECONDS);
+
+            this.scheduledExecutorService.scheduleAtFixedRate(new Runnable() {
+                @Override
+                public void run() {
+                    try {
+                        BrokerController.this.consumerOffsetManager.persist();
+                    } catch (Throwable e) {
+                        log.error("schedule persist consumerOffset error.", e);
+                    }
+                }
+            }, 1000 * 10, this.brokerConfig.getFlushConsumerOffsetInterval(), TimeUnit.MILLISECONDS);
+
+            this.scheduledExecutorService.scheduleAtFixedRate(new Runnable() {
+                @Override
+                public void run() {
+                    try {
+                        BrokerController.this.consumerFilterManager.persist();
+                    } catch (Throwable e) {
+                        log.error("schedule persist consumer filter error.", e);
+                    }
+                }
+            }, 1000 * 10, 1000 * 10, TimeUnit.MILLISECONDS);
+
+            this.scheduledExecutorService.scheduleAtFixedRate(new Runnable() {
+                @Override
+                public void run() {
+                    try {
+                        BrokerController.this.protectBroker();
+                    } catch (Throwable e) {
+                        log.error("protectBroker error.", e);
+                    }
+                }
+            }, 3, 3, TimeUnit.MINUTES);
+
+            this.scheduledExecutorService.scheduleAtFixedRate(new Runnable() {
+                @Override
+                public void run() {
+                    try {
+                        BrokerController.this.printWaterMark();
+                    } catch (Throwable e) {
+                        log.error("printWaterMark error.", e);
+                    }
+                }
+            }, 10, 1, TimeUnit.SECONDS);
+
+            this.scheduledExecutorService.scheduleAtFixedRate(new Runnable() {
+
+                @Override
+                public void run() {
+                    try {
+                        log.info("dispatch behind commit log {} bytes", BrokerController.this.getMessageStore().dispatchBehindBytes());
+                    } catch (Throwable e) {
+                        log.error("schedule dispatchBehindBytes error.", e);
+                    }
+                }
+            }, 1000 * 10, 1000 * 60, TimeUnit.MILLISECONDS);
+
+            if (this.brokerConfig.getNamesrvAddr() != null) {
+                this.brokerOuterAPI.updateNameServerAddressList(this.brokerConfig.getNamesrvAddr());
+                log.info("Set user specified name server address: {}", this.brokerConfig.getNamesrvAddr());
+            } else if (this.brokerConfig.isFetchNamesrvAddrByAddressServer()) {
+                this.scheduledExecutorService.scheduleAtFixedRate(new Runnable() {
+
+                    @Override
+                    public void run() {
+                        try {
+                            BrokerController.this.brokerOuterAPI.fetchNameServerAddr();
+                        } catch (Throwable e) {
+                            log.error("ScheduledTask fetchNameServerAddr exception", e);
+                        }
+                    }
+                }, 1000 * 10, 1000 * 60 * 2, TimeUnit.MILLISECONDS);
+            }
+
+            if (!messageStoreConfig.isEnableDLegerCommitLog()) {
+                if (BrokerRole.SLAVE == this.messageStoreConfig.getBrokerRole()) {
+                    if (this.messageStoreConfig.getHaMasterAddress() != null && this.messageStoreConfig.getHaMasterAddress().length() >= 6) {
+                        this.messageStore.updateHaMasterAddress(this.messageStoreConfig.getHaMasterAddress());
+                        this.updateMasterHAServerAddrPeriodically = false;
+                    } else {
+                        this.updateMasterHAServerAddrPeriodically = true;
+                    }
+                } else {
+                    this.scheduledExecutorService.scheduleAtFixedRate(new Runnable() {
+                        @Override
+                        public void run() {
+                            try {
+                                BrokerController.this.printMasterAndSlaveDiff();
+                            } catch (Throwable e) {
+                                log.error("schedule printMasterAndSlaveDiff error.", e);
+                            }
+                        }
+                    }, 1000 * 10, 1000 * 60, TimeUnit.MILLISECONDS);
+                }
+            }
+
+            if (TlsSystemConfig.tlsMode != TlsMode.DISABLED) {
+                // Register a listener to reload SslContext
+                try {
+                    fileWatchService = new FileWatchService(
+                        new String[] {
+                            TlsSystemConfig.tlsServerCertPath,
+                            TlsSystemConfig.tlsServerKeyPath,
+                            TlsSystemConfig.tlsServerTrustCertPath
+                        },
+                        new FileWatchService.Listener() {
+                            boolean certChanged, keyChanged = false;
+
+                            @Override
+                            public void onChanged(String path) {
+                                if (path.equals(TlsSystemConfig.tlsServerTrustCertPath)) {
+                                    log.info("The trust certificate changed, reload the ssl context");
+                                    reloadServerSslContext();
+                                }
+                                if (path.equals(TlsSystemConfig.tlsServerCertPath)) {
+                                    certChanged = true;
+                                }
+                                if (path.equals(TlsSystemConfig.tlsServerKeyPath)) {
+                                    keyChanged = true;
+                                }
+                                if (certChanged && keyChanged) {
+                                    log.info("The certificate and private key changed, reload the ssl context");
+                                    certChanged = keyChanged = false;
+                                    reloadServerSslContext();
+                                }
+                            }
+
+                            private void reloadServerSslContext() {
+                                ((NettyRemotingServer) remotingServer).loadSslContext();
+                                ((NettyRemotingServer) fastRemotingServer).loadSslContext();
+                            }
+                        });
+                } catch (Exception e) {
+                    log.warn("FileWatchService created error, can't load the certificate dynamically");
+                }
+            }
+            initialTransaction();
+            initialAcl();
+            initialRpcHooks();
+        }
+        return result;

    Broker 启动过程

    贴代码

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    public void start() throws Exception {
            if (this.messageStore != null) {
                this.messageStore.start();
            }

            if (this.remotingServer != null) {
                this.remotingServer.start();
            }

            if (this.fastRemotingServer != null) {
                this.fastRemotingServer.start();
            }

            if (this.fileWatchService != null) {
                this.fileWatchService.start();
            }

            if (this.brokerOuterAPI != null) {
                this.brokerOuterAPI.start();
            }

            if (this.pullRequestHoldService != null) {
                this.pullRequestHoldService.start();
            }

            if (this.clientHousekeepingService != null) {
                this.clientHousekeepingService.start();
            }

            if (this.filterServerManager != null) {
                this.filterServerManager.start();
            }

            if (!messageStoreConfig.isEnableDLegerCommitLog()) {
                startProcessorByHa(messageStoreConfig.getBrokerRole());
                handleSlaveSynchronize(messageStoreConfig.getBrokerRole());
                this.registerBrokerAll(true, false, true);
            }

            this.scheduledExecutorService.scheduleAtFixedRate(new Runnable() {

                @Override
                public void run() {
                    try {
                        BrokerController.this.registerBrokerAll(true, false, brokerConfig.isForceRegister());
                    } catch (Throwable e) {
                        log.error("registerBrokerAll Exception", e);
                    }
                }
            }, 1000 * 10, Math.max(10000, Math.min(brokerConfig.getRegisterNameServerPeriod(), 60000)), TimeUnit.MILLISECONDS);

            if (this.brokerStatsManager != null) {
                this.brokerStatsManager.start();
            }

            if (this.brokerFastFailure != null) {
                this.brokerFastFailure.start();
            }


        }
    +
    public void start() throws Exception {
+        if (this.messageStore != null) {
+            this.messageStore.start();
+        }
+
+        if (this.remotingServer != null) {
+            this.remotingServer.start();
+        }
+
+        if (this.fastRemotingServer != null) {
+            this.fastRemotingServer.start();
+        }
+
+        if (this.fileWatchService != null) {
+            this.fileWatchService.start();
+        }
+
+        if (this.brokerOuterAPI != null) {
+            this.brokerOuterAPI.start();
+        }
+
+        if (this.pullRequestHoldService != null) {
+            this.pullRequestHoldService.start();
+        }
+
+        if (this.clientHousekeepingService != null) {
+            this.clientHousekeepingService.start();
+        }
+
+        if (this.filterServerManager != null) {
+            this.filterServerManager.start();
+        }
+
+        if (!messageStoreConfig.isEnableDLegerCommitLog()) {
+            startProcessorByHa(messageStoreConfig.getBrokerRole());
+            handleSlaveSynchronize(messageStoreConfig.getBrokerRole());
+            this.registerBrokerAll(true, false, true);
+        }
+
+        this.scheduledExecutorService.scheduleAtFixedRate(new Runnable() {
+
+            @Override
+            public void run() {
+                try {
+                    BrokerController.this.registerBrokerAll(true, false, brokerConfig.isForceRegister());
+                } catch (Throwable e) {
+                    log.error("registerBrokerAll Exception", e);
+                }
+            }
+        }, 1000 * 10, Math.max(10000, Math.min(brokerConfig.getRegisterNameServerPeriod(), 60000)), TimeUnit.MILLISECONDS);
+
+        if (this.brokerStatsManager != null) {
+            this.brokerStatsManager.start();
+        }
+
+        if (this.brokerFastFailure != null) {
+            this.brokerFastFailure.start();
+        }
+
+
+    }

    首先是启动messageStore，调用 start 方法，这里面又调用了一些代码

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    public void start() throws Exception {

            lock = lockFile.getChannel().tryLock(0, 1, false);
            if (lock == null || lock.isShared() || !lock.isValid()) {
                throw new RuntimeException("Lock failed,MQ already started");
            }

            lockFile.getChannel().write(ByteBuffer.wrap("lock".getBytes()));
            lockFile.getChannel().force(true);
            {
                /**
                 * 1. Make sure the fast-forward messages to be truncated during the recovering according to the max physical offset of the commitlog;
                 * 2. DLedger committedPos may be missing, so the maxPhysicalPosInLogicQueue maybe bigger that maxOffset returned by DLedgerCommitLog, just let it go;
                 * 3. Calculate the reput offset according to the consume queue;
                 * 4. Make sure the fall-behind messages to be dispatched before starting the commitlog, especially when the broker role are automatically changed.
                 */
                long maxPhysicalPosInLogicQueue = commitLog.getMinOffset();
                for (ConcurrentMap<Integer, ConsumeQueue> maps : this.consumeQueueTable.values()) {
                    for (ConsumeQueue logic : maps.values()) {
                        if (logic.getMaxPhysicOffset() > maxPhysicalPosInLogicQueue) {
                            maxPhysicalPosInLogicQueue = logic.getMaxPhysicOffset();
                        }
                    }
                }
                if (maxPhysicalPosInLogicQueue < 0) {
                    maxPhysicalPosInLogicQueue = 0;
                }
                if (maxPhysicalPosInLogicQueue < this.commitLog.getMinOffset()) {
                    maxPhysicalPosInLogicQueue = this.commitLog.getMinOffset();
                    /**
                     * This happens in following conditions:
                     * 1. If someone removes all the consumequeue files or the disk get damaged.
                     * 2. Launch a new broker, and copy the commitlog from other brokers.
                     *
                     * All the conditions has the same in common that the maxPhysicalPosInLogicQueue should be 0.
                     * If the maxPhysicalPosInLogicQueue is gt 0, there maybe something wrong.
                     */
                    log.warn("[TooSmallCqOffset] maxPhysicalPosInLogicQueue={} clMinOffset={}", maxPhysicalPosInLogicQueue, this.commitLog.getMinOffset());
                }
                log.info("[SetReputOffset] maxPhysicalPosInLogicQueue={} clMinOffset={} clMaxOffset={} clConfirmedOffset={}",
                    maxPhysicalPosInLogicQueue, this.commitLog.getMinOffset(), this.commitLog.getMaxOffset(), this.commitLog.getConfirmOffset());
                this.reputMessageService.setReputFromOffset(maxPhysicalPosInLogicQueue);
                this.reputMessageService.start();

                /**
                 *  1. Finish dispatching the messages fall behind, then to start other services.
                 *  2. DLedger committedPos may be missing, so here just require dispatchBehindBytes <= 0
                 */
                while (true) {
                    if (dispatchBehindBytes() <= 0) {
                        break;
                    }
                    Thread.sleep(1000);
                    log.info("Try to finish doing reput the messages fall behind during the starting, reputOffset={} maxOffset={} behind={}", this.reputMessageService.getReputFromOffset(), this.getMaxPhyOffset(), this.dispatchBehindBytes());
                }
                this.recoverTopicQueueTable();
            }

            if (!messageStoreConfig.isEnableDLegerCommitLog()) {
                this.haService.start();
                this.handleScheduleMessageService(messageStoreConfig.getBrokerRole());
            }

            this.flushConsumeQueueService.start();
            this.commitLog.start();
            this.storeStatsService.start();

            this.createTempFile();
            this.addScheduleTask();
            this.shutdown = false;
        }
    +
    public void start() throws Exception {
+
+        lock = lockFile.getChannel().tryLock(0, 1, false);
+        if (lock == null || lock.isShared() || !lock.isValid()) {
+            throw new RuntimeException("Lock failed,MQ already started");
+        }
+
+        lockFile.getChannel().write(ByteBuffer.wrap("lock".getBytes()));
+        lockFile.getChannel().force(true);
+        {
+            /**
+             * 1. Make sure the fast-forward messages to be truncated during the recovering according to the max physical offset of the commitlog;
+             * 2. DLedger committedPos may be missing, so the maxPhysicalPosInLogicQueue maybe bigger that maxOffset returned by DLedgerCommitLog, just let it go;
+             * 3. Calculate the reput offset according to the consume queue;
+             * 4. Make sure the fall-behind messages to be dispatched before starting the commitlog, especially when the broker role are automatically changed.
+             */
+            long maxPhysicalPosInLogicQueue = commitLog.getMinOffset();
+            for (ConcurrentMap<Integer, ConsumeQueue> maps : this.consumeQueueTable.values()) {
+                for (ConsumeQueue logic : maps.values()) {
+                    if (logic.getMaxPhysicOffset() > maxPhysicalPosInLogicQueue) {
+                        maxPhysicalPosInLogicQueue = logic.getMaxPhysicOffset();
+                    }
+                }
+            }
+            if (maxPhysicalPosInLogicQueue < 0) {
+                maxPhysicalPosInLogicQueue = 0;
+            }
+            if (maxPhysicalPosInLogicQueue < this.commitLog.getMinOffset()) {
+                maxPhysicalPosInLogicQueue = this.commitLog.getMinOffset();
+                /**
+                 * This happens in following conditions:
+                 * 1. If someone removes all the consumequeue files or the disk get damaged.
+                 * 2. Launch a new broker, and copy the commitlog from other brokers.
+                 *
+                 * All the conditions has the same in common that the maxPhysicalPosInLogicQueue should be 0.
+                 * If the maxPhysicalPosInLogicQueue is gt 0, there maybe something wrong.
+                 */
+                log.warn("[TooSmallCqOffset] maxPhysicalPosInLogicQueue={} clMinOffset={}", maxPhysicalPosInLogicQueue, this.commitLog.getMinOffset());
+            }
+            log.info("[SetReputOffset] maxPhysicalPosInLogicQueue={} clMinOffset={} clMaxOffset={} clConfirmedOffset={}",
+                maxPhysicalPosInLogicQueue, this.commitLog.getMinOffset(), this.commitLog.getMaxOffset(), this.commitLog.getConfirmOffset());
+            this.reputMessageService.setReputFromOffset(maxPhysicalPosInLogicQueue);
+            this.reputMessageService.start();
+
+            /**
+             *  1. Finish dispatching the messages fall behind, then to start other services.
+             *  2. DLedger committedPos may be missing, so here just require dispatchBehindBytes <= 0
+             */
+            while (true) {
+                if (dispatchBehindBytes() <= 0) {
+                    break;
+                }
+                Thread.sleep(1000);
+                log.info("Try to finish doing reput the messages fall behind during the starting, reputOffset={} maxOffset={} behind={}", this.reputMessageService.getReputFromOffset(), this.getMaxPhyOffset(), this.dispatchBehindBytes());
+            }
+            this.recoverTopicQueueTable();
+        }
+
+        if (!messageStoreConfig.isEnableDLegerCommitLog()) {
+            this.haService.start();
+            this.handleScheduleMessageService(messageStoreConfig.getBrokerRole());
+        }
+
+        this.flushConsumeQueueService.start();
+        this.commitLog.start();
+        this.storeStatsService.start();
+
+        this.createTempFile();
+        this.addScheduleTask();
+        this.shutdown = false;
+    }
    diff --git a/2020/07/26/我是如何走上跑步这条不归路的/index.html b/2020/07/26/我是如何走上跑步这条不归路的/index.html index 4cd1b8ca5b..618b552056 100644 --- a/2020/07/26/我是如何走上跑步这条不归路的/index.html +++ b/2020/07/26/我是如何走上跑步这条不归路的/index.html @@ -4,7 +4,7 @@ - + @@ -32,8 +32,9 @@ + - + @@ -228,9 +229,8 @@     Posted on - - +     diff --git a/2020/08/02/聊聊-Java-自带的那些逆天工具/index.html b/2020/08/02/聊聊-Java-自带的那些逆天工具/index.html index a4ea677306..ee19e18e53 100644 --- a/2020/08/02/聊聊-Java-自带的那些逆天工具/index.html +++ b/2020/08/02/聊聊-Java-自带的那些逆天工具/index.html @@ -4,7 +4,7 @@ - + @@ -32,6 +32,7 @@ + @@ -43,16 +44,12 @@ - + - - - - @@ -246,13 +243,6 @@ - - - - - Edited on - - @@ -315,12 +305,509 @@

    原谅我的标题党，其实这些工具的确很厉害，之前其实介绍过一点相关的，是从我一次问题排查的过程中用到的，但是最近又有碰到一次排查问题，发现其实用 idea 直接 dump thread 是不现实的，毕竟服务器环境的没法这么操作，那就得用 Java 的那些工具了

    -

    jstack & jps

    譬如 jstack，这个命令其实不能更简单了
    看看 help 信息

    用-l参数可以打出锁的额外信息，然后后面的 pid 就是进程 id 咯，机智的小伙伴会问了（就你这个小白才问这么蠢的问题🤦‍♂️），怎么看 Java 应用的进程呢
    那就是 jps 了，命令也很简单，一般直接用 jps命令就好了，不过也可以 help 看一下

    稍微解释下，-q是只显示进程 id，-m是输出给main 方法的参数，比如我在配置中加给参数

    然后用 jps -m查看

    -v加上小 v 的话就是打印 jvm 参数

    还是有点东西，然后就继续介绍 jstack 了，然后我们看看 jstack 出来是啥，为了加点内容我加了个死锁

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    public static void main(String[] args) throws InterruptedException {
            SpringApplication.run(ThreadDumpDemoApplication.class, args);
            ReentrantLock lock1 = new ReentrantLock();
            ReentrantLock lock2 = new ReentrantLock();
            Thread t1 = new Thread() {
                @Override
                public void run() {
                    try {
                        lock1.lock();
                        TimeUnit.SECONDS.sleep(1);
                        lock2.lock();
                    } catch (InterruptedException e) {
                        e.printStackTrace();
                    }
                }
            };
            Thread t2 = new Thread() {
                @Override
                public void run() {
                    try {
                        lock2.lock();
                        TimeUnit.SECONDS.sleep(1);
                        lock1.lock();
                    } catch (InterruptedException e) {
                        e.printStackTrace();
                    }
                }
            };
            t1.setName("mythread1");
            t2.setName("mythread2");
            t1.start();
            t2.start();
            Thread.sleep(10000);
        }
    +

    jstack & jps

    譬如 jstack，这个命令其实不能更简单了
    看看 help 信息

    用-l参数可以打出锁的额外信息，然后后面的 pid 就是进程 id 咯，机智的小伙伴会问了（就你这个小白才问这么蠢的问题🤦‍♂️），怎么看 Java 应用的进程呢
    那就是 jps 了，命令也很简单，一般直接用 jps命令就好了，不过也可以 help 看一下

    稍微解释下，-q是只显示进程 id，-m是输出给main 方法的参数，比如我在配置中加给参数

    然后用 jps -m查看

    -v加上小 v 的话就是打印 jvm 参数

    还是有点东西，然后就继续介绍 jstack 了，然后我们看看 jstack 出来是啥，为了加点内容我加了个死锁

    +
    public static void main(String[] args) throws InterruptedException {
+        SpringApplication.run(ThreadDumpDemoApplication.class, args);
+        ReentrantLock lock1 = new ReentrantLock();
+        ReentrantLock lock2 = new ReentrantLock();
+        Thread t1 = new Thread() {
+            @Override
+            public void run() {
+                try {
+                    lock1.lock();
+                    TimeUnit.SECONDS.sleep(1);
+                    lock2.lock();
+                } catch (InterruptedException e) {
+                    e.printStackTrace();
+                }
+            }
+        };
+        Thread t2 = new Thread() {
+            @Override
+            public void run() {
+                try {
+                    lock2.lock();
+                    TimeUnit.SECONDS.sleep(1);
+                    lock1.lock();
+                } catch (InterruptedException e) {
+                    e.printStackTrace();
+                }
+            }
+        };
+        t1.setName("mythread1");
+        t2.setName("mythread2");
+        t1.start();
+        t2.start();
+        Thread.sleep(10000);
+    }

    然后看看出来时怎么样的

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    2020-08-02 21:50:32
    Full thread dump Java HotSpot(TM) 64-Bit Server VM (25.201-b09 mixed mode):

    "DestroyJavaVM" #147 prio=5 os_prio=31 tid=0x00007fc9dd807000 nid=0x2603 waiting on condition [0x0000000000000000]
       java.lang.Thread.State: RUNNABLE

       Locked ownable synchronizers:
            - None

    "mythread2" #140 prio=5 os_prio=31 tid=0x00007fc9dd877000 nid=0x9903 waiting on condition [0x0000700006fb9000]
       java.lang.Thread.State: WAITING (parking)
            at sun.misc.Unsafe.park(Native Method)
            - parking to wait for  <0x000000076f5d4330> (a java.util.concurrent.locks.ReentrantLock$NonfairSync)
            at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
            at java.util.concurrent.locks.AbstractQueuedSynchronizer.parkAndCheckInterrupt(AbstractQueuedSynchronizer.java:836)
            at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquireQueued(AbstractQueuedSynchronizer.java:870)
            at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquire(AbstractQueuedSynchronizer.java:1199)
            at java.util.concurrent.locks.ReentrantLock$NonfairSync.lock(ReentrantLock.java:209)
            at java.util.concurrent.locks.ReentrantLock.lock(ReentrantLock.java:285)
            at com.nicksxs.thread_dump_demo.ThreadDumpDemoApplication$2.run(ThreadDumpDemoApplication.java:34)

       Locked ownable synchronizers:
            - <0x000000076f5d4360> (a java.util.concurrent.locks.ReentrantLock$NonfairSync)

    "mythread1" #139 prio=5 os_prio=31 tid=0x00007fc9de873800 nid=0x9a03 waiting on condition [0x0000700006eb6000]
       java.lang.Thread.State: WAITING (parking)
            at sun.misc.Unsafe.park(Native Method)
            - parking to wait for  <0x000000076f5d4360> (a java.util.concurrent.locks.ReentrantLock$NonfairSync)
            at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
            at java.util.concurrent.locks.AbstractQueuedSynchronizer.parkAndCheckInterrupt(AbstractQueuedSynchronizer.java:836)
            at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquireQueued(AbstractQueuedSynchronizer.java:870)
            at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquire(AbstractQueuedSynchronizer.java:1199)
            at java.util.concurrent.locks.ReentrantLock$NonfairSync.lock(ReentrantLock.java:209)
            at java.util.concurrent.locks.ReentrantLock.lock(ReentrantLock.java:285)
            at com.nicksxs.thread_dump_demo.ThreadDumpDemoApplication$1.run(ThreadDumpDemoApplication.java:22)

       Locked ownable synchronizers:
            - <0x000000076f5d4330> (a java.util.concurrent.locks.ReentrantLock$NonfairSync)

    "http-nio-8080-Acceptor" #137 daemon prio=5 os_prio=31 tid=0x00007fc9de1ac000 nid=0x9b03 runnable [0x0000700006db3000]
       java.lang.Thread.State: RUNNABLE
            at sun.nio.ch.ServerSocketChannelImpl.accept0(Native Method)
            at sun.nio.ch.ServerSocketChannelImpl.accept(ServerSocketChannelImpl.java:422)
            at sun.nio.ch.ServerSocketChannelImpl.accept(ServerSocketChannelImpl.java:250)
            - locked <0x000000076f1e4820> (a java.lang.Object)
            at org.apache.tomcat.util.net.NioEndpoint.serverSocketAccept(NioEndpoint.java:469)
            at org.apache.tomcat.util.net.NioEndpoint.serverSocketAccept(NioEndpoint.java:71)
            at org.apache.tomcat.util.net.Acceptor.run(Acceptor.java:95)
            at java.lang.Thread.run(Thread.java:748)

       Locked ownable synchronizers:
            - None

    "http-nio-8080-ClientPoller" #136 daemon prio=5 os_prio=31 tid=0x00007fc9dd876800 nid=0x6503 runnable [0x0000700006cb0000]
       java.lang.Thread.State: RUNNABLE
            at sun.nio.ch.KQueueArrayWrapper.kevent0(Native Method)
            at sun.nio.ch.KQueueArrayWrapper.poll(KQueueArrayWrapper.java:198)
            at sun.nio.ch.KQueueSelectorImpl.doSelect(KQueueSelectorImpl.java:117)
            at sun.nio.ch.SelectorImpl.lockAndDoSelect(SelectorImpl.java:86)
            - locked <0x000000076f2978c8> (a sun.nio.ch.Util$3)
            - locked <0x000000076f2978b8> (a java.util.Collections$UnmodifiableSet)
            - locked <0x000000076f297798> (a sun.nio.ch.KQueueSelectorImpl)
            at sun.nio.ch.SelectorImpl.select(SelectorImpl.java:97)
            at org.apache.tomcat.util.net.NioEndpoint$Poller.run(NioEndpoint.java:709)
            at java.lang.Thread.run(Thread.java:748)

       Locked ownable synchronizers:
            - None

    "http-nio-8080-exec-10" #135 daemon prio=5 os_prio=31 tid=0x00007fc9de1af000 nid=0x9d03 waiting on condition [0x0000700006bad000]
       java.lang.Thread.State: WAITING (parking)
            at sun.misc.Unsafe.park(Native Method)
            - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
            at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
            at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
            at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
            at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
            at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
            at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
            at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
            at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
            at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
            at java.lang.Thread.run(Thread.java:748)

       Locked ownable synchronizers:
            - None

    "http-nio-8080-exec-9" #134 daemon prio=5 os_prio=31 tid=0x00007fc9de1ab800 nid=0x6403 waiting on condition [0x0000700006aaa000]
       java.lang.Thread.State: WAITING (parking)
            at sun.misc.Unsafe.park(Native Method)
            - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
            at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
            at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
            at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
            at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
            at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
            at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
            at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
            at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
            at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
            at java.lang.Thread.run(Thread.java:748)

       Locked ownable synchronizers:
            - None

    "http-nio-8080-exec-8" #133 daemon prio=5 os_prio=31 tid=0x00007fc9de873000 nid=0x9f03 waiting on condition [0x00007000069a7000]
       java.lang.Thread.State: WAITING (parking)
            at sun.misc.Unsafe.park(Native Method)
            - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
            at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
            at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
            at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
            at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
            at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
            at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
            at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
            at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
            at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
            at java.lang.Thread.run(Thread.java:748)

       Locked ownable synchronizers:
            - None

    "http-nio-8080-exec-7" #132 daemon prio=5 os_prio=31 tid=0x00007fc9df0a1800 nid=0xa103 waiting on condition [0x00007000068a4000]
       java.lang.Thread.State: WAITING (parking)
            at sun.misc.Unsafe.park(Native Method)
            - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
            at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
            at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
            at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
            at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
            at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
            at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
            at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
            at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
            at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
            at java.lang.Thread.run(Thread.java:748)

       Locked ownable synchronizers:
            - None

    "http-nio-8080-exec-6" #131 daemon prio=5 os_prio=31 tid=0x00007fc9df242800 nid=0x6103 waiting on condition [0x00007000067a1000]
       java.lang.Thread.State: WAITING (parking)
            at sun.misc.Unsafe.park(Native Method)
            - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
            at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
            at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
            at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
            at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
            at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
            at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
            at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
            at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
            at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
            at java.lang.Thread.run(Thread.java:748)

       Locked ownable synchronizers:
            - None

    "http-nio-8080-exec-5" #130 daemon prio=5 os_prio=31 tid=0x00007fc9de872000 nid=0x5f03 waiting on condition [0x000070000669e000]
       java.lang.Thread.State: WAITING (parking)
            at sun.misc.Unsafe.park(Native Method)
            - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
            at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
            at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
            at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
            at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
            at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
            at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
            at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
            at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
            at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
            at java.lang.Thread.run(Thread.java:748)

       Locked ownable synchronizers:
            - None

    "http-nio-8080-exec-4" #129 daemon prio=5 os_prio=31 tid=0x00007fc9de1a6000 nid=0x5e03 waiting on condition [0x000070000659b000]
       java.lang.Thread.State: WAITING (parking)
            at sun.misc.Unsafe.park(Native Method)
            - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
            at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
            at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
            at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
            at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
            at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
            at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
            at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
            at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
            at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
            at java.lang.Thread.run(Thread.java:748)

       Locked ownable synchronizers:
            - None

    "http-nio-8080-exec-3" #128 daemon prio=5 os_prio=31 tid=0x00007fc9de871800 nid=0x5c03 waiting on condition [0x0000700006498000]
       java.lang.Thread.State: WAITING (parking)
            at sun.misc.Unsafe.park(Native Method)
            - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
            at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
            at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
            at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
            at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
            at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
            at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
            at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
            at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
            at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
            at java.lang.Thread.run(Thread.java:748)

       Locked ownable synchronizers:
            - None

    "http-nio-8080-exec-2" #127 daemon prio=5 os_prio=31 tid=0x00007fc9dead9000 nid=0x5b03 waiting on condition [0x0000700006395000]
       java.lang.Thread.State: WAITING (parking)
            at sun.misc.Unsafe.park(Native Method)
            - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
            at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
            at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
            at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
            at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
            at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
            at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
            at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
            at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
            at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
            at java.lang.Thread.run(Thread.java:748)

       Locked ownable synchronizers:
            - None

    "http-nio-8080-exec-1" #126 daemon prio=5 os_prio=31 tid=0x00007fc9ddb00000 nid=0x5a03 waiting on condition [0x0000700006292000]
       java.lang.Thread.State: WAITING (parking)
            at sun.misc.Unsafe.park(Native Method)
            - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
            at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
            at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
            at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
            at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
            at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
            at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
            at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
            at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
            at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
            at java.lang.Thread.run(Thread.java:748)

       Locked ownable synchronizers:
            - None

    "http-nio-8080-BlockPoller" #125 daemon prio=5 os_prio=31 tid=0x00007fc9df242000 nid=0xa503 runnable [0x000070000618f000]
       java.lang.Thread.State: RUNNABLE
            at sun.nio.ch.KQueueArrayWrapper.kevent0(Native Method)
            at sun.nio.ch.KQueueArrayWrapper.poll(KQueueArrayWrapper.java:198)
            at sun.nio.ch.KQueueSelectorImpl.doSelect(KQueueSelectorImpl.java:117)
            at sun.nio.ch.SelectorImpl.lockAndDoSelect(SelectorImpl.java:86)
            - locked <0x000000076f1eea30> (a sun.nio.ch.Util$3)
            - locked <0x000000076f1ee198> (a java.util.Collections$UnmodifiableSet)
            - locked <0x000000076f1ee010> (a sun.nio.ch.KQueueSelectorImpl)
            at sun.nio.ch.SelectorImpl.select(SelectorImpl.java:97)
            at org.apache.tomcat.util.net.NioBlockingSelector$BlockPoller.run(NioBlockingSelector.java:313)

       Locked ownable synchronizers:
            - None

    "container-0" #124 prio=5 os_prio=31 tid=0x00007fc9df06a000 nid=0x5803 waiting on condition [0x000070000608c000]
       java.lang.Thread.State: TIMED_WAITING (sleeping)
            at java.lang.Thread.sleep(Native Method)
            at org.apache.catalina.core.StandardServer.await(StandardServer.java:570)
            at org.springframework.boot.web.embedded.tomcat.TomcatWebServer$1.run(TomcatWebServer.java:197)

       Locked ownable synchronizers:
            - None

    "Catalina-utility-2" #123 prio=1 os_prio=31 tid=0x00007fc9de886000 nid=0xa80f waiting on condition [0x0000700005f89000]
       java.lang.Thread.State: WAITING (parking)
            at sun.misc.Unsafe.park(Native Method)
            - parking to wait for  <0x000000076c88ab58> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
            at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
            at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
            at java.util.concurrent.ScheduledThreadPoolExecutor$DelayedWorkQueue.take(ScheduledThreadPoolExecutor.java:1088)
            at java.util.concurrent.ScheduledThreadPoolExecutor$DelayedWorkQueue.take(ScheduledThreadPoolExecutor.java:809)
            at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
            at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
            at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
            at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
            at java.lang.Thread.run(Thread.java:748)

       Locked ownable synchronizers:
            - None

    "Catalina-utility-1" #122 prio=1 os_prio=31 tid=0x00007fc9de884000 nid=0x5667 waiting on condition [0x0000700005e86000]
       java.lang.Thread.State: TIMED_WAITING (parking)
            at sun.misc.Unsafe.park(Native Method)
            - parking to wait for  <0x000000076c88ab58> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
            at java.util.concurrent.locks.LockSupport.parkNanos(LockSupport.java:215)
            at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.awaitNanos(AbstractQueuedSynchronizer.java:2078)
            at java.util.concurrent.ScheduledThreadPoolExecutor$DelayedWorkQueue.take(ScheduledThreadPoolExecutor.java:1093)
            at java.util.concurrent.ScheduledThreadPoolExecutor$DelayedWorkQueue.take(ScheduledThreadPoolExecutor.java:809)
            at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
            at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
            at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
            at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
            at java.lang.Thread.run(Thread.java:748)

       Locked ownable synchronizers:
            - None

    "RMI Scheduler(0)" #15 daemon prio=5 os_prio=31 tid=0x00007fc9de9ee000 nid=0x5503 waiting on condition [0x0000700005d83000]
       java.lang.Thread.State: TIMED_WAITING (parking)
            at sun.misc.Unsafe.park(Native Method)
            - parking to wait for  <0x00000006c0015410> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
            at java.util.concurrent.locks.LockSupport.parkNanos(LockSupport.java:215)
            at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.awaitNanos(AbstractQueuedSynchronizer.java:2078)
            at java.util.concurrent.ScheduledThreadPoolExecutor$DelayedWorkQueue.take(ScheduledThreadPoolExecutor.java:1093)
            at java.util.concurrent.ScheduledThreadPoolExecutor$DelayedWorkQueue.take(ScheduledThreadPoolExecutor.java:809)
            at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
            at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
            at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
            at java.lang.Thread.run(Thread.java:748)

       Locked ownable synchronizers:
            - None

    "Attach Listener" #13 daemon prio=9 os_prio=31 tid=0x00007fc9df149800 nid=0x3c07 waiting on condition [0x0000000000000000]
       java.lang.Thread.State: RUNNABLE

       Locked ownable synchronizers:
            - None

    "RMI TCP Accept-0" #11 daemon prio=5 os_prio=31 tid=0x00007fc9df100000 nid=0x4003 runnable [0x0000700005977000]
       java.lang.Thread.State: RUNNABLE
            at java.net.PlainSocketImpl.socketAccept(Native Method)
            at java.net.AbstractPlainSocketImpl.accept(AbstractPlainSocketImpl.java:409)
            at java.net.ServerSocket.implAccept(ServerSocket.java:545)
            at java.net.ServerSocket.accept(ServerSocket.java:513)
            at sun.management.jmxremote.LocalRMIServerSocketFactory$1.accept(LocalRMIServerSocketFactory.java:52)
            at sun.rmi.transport.tcp.TCPTransport$AcceptLoop.executeAcceptLoop(TCPTransport.java:405)
            at sun.rmi.transport.tcp.TCPTransport$AcceptLoop.run(TCPTransport.java:377)
            at java.lang.Thread.run(Thread.java:748)

       Locked ownable synchronizers:
            - None

    "Service Thread" #9 daemon prio=9 os_prio=31 tid=0x00007fc9df0ce800 nid=0x4103 runnable [0x0000000000000000]
       java.lang.Thread.State: RUNNABLE

       Locked ownable synchronizers:
            - None

    "C1 CompilerThread2" #8 daemon prio=9 os_prio=31 tid=0x00007fc9df0ce000 nid=0x4203 waiting on condition [0x0000000000000000]
       java.lang.Thread.State: RUNNABLE

       Locked ownable synchronizers:
            - None

    "C2 CompilerThread1" #7 daemon prio=9 os_prio=31 tid=0x00007fc9de0a3800 nid=0x3503 waiting on condition [0x0000000000000000]
       java.lang.Thread.State: RUNNABLE

       Locked ownable synchronizers:
            - None

    "C2 CompilerThread0" #6 daemon prio=9 os_prio=31 tid=0x00007fc9de89b000 nid=0x3403 waiting on condition [0x0000000000000000]
       java.lang.Thread.State: RUNNABLE

       Locked ownable synchronizers:
            - None

    "Monitor Ctrl-Break" #5 daemon prio=5 os_prio=31 tid=0x00007fc9df0ca000 nid=0x3303 runnable [0x0000700005468000]
       java.lang.Thread.State: RUNNABLE
            at java.net.SocketInputStream.socketRead0(Native Method)
            at java.net.SocketInputStream.socketRead(SocketInputStream.java:116)
            at java.net.SocketInputStream.read(SocketInputStream.java:171)
            at java.net.SocketInputStream.read(SocketInputStream.java:141)
            at sun.nio.cs.StreamDecoder.readBytes(StreamDecoder.java:284)
            at sun.nio.cs.StreamDecoder.implRead(StreamDecoder.java:326)
            at sun.nio.cs.StreamDecoder.read(StreamDecoder.java:178)
            - locked <0x00000006c001b760> (a java.io.InputStreamReader)
            at java.io.InputStreamReader.read(InputStreamReader.java:184)
            at java.io.BufferedReader.fill(BufferedReader.java:161)
            at java.io.BufferedReader.readLine(BufferedReader.java:324)
            - locked <0x00000006c001b760> (a java.io.InputStreamReader)
            at java.io.BufferedReader.readLine(BufferedReader.java:389)
            at com.intellij.rt.execution.application.AppMainV2$1.run(AppMainV2.java:64)

       Locked ownable synchronizers:
            - None

    "Signal Dispatcher" #4 daemon prio=9 os_prio=31 tid=0x00007fc9de824000 nid=0x4503 runnable [0x0000000000000000]
       java.lang.Thread.State: RUNNABLE

       Locked ownable synchronizers:
            - None

    "Finalizer" #3 daemon prio=8 os_prio=31 tid=0x00007fc9dd811800 nid=0x4f03 in Object.wait() [0x0000700005262000]
       java.lang.Thread.State: WAITING (on object monitor)
            at java.lang.Object.wait(Native Method)
            - waiting on <0x00000006c0008348> (a java.lang.ref.ReferenceQueue$Lock)
            at java.lang.ref.ReferenceQueue.remove(ReferenceQueue.java:144)
            - locked <0x00000006c0008348> (a java.lang.ref.ReferenceQueue$Lock)
            at java.lang.ref.ReferenceQueue.remove(ReferenceQueue.java:165)
            at java.lang.ref.Finalizer$FinalizerThread.run(Finalizer.java:216)

       Locked ownable synchronizers:
            - None

    "Reference Handler" #2 daemon prio=10 os_prio=31 tid=0x00007fc9de02a000 nid=0x5003 in Object.wait() [0x000070000515f000]
       java.lang.Thread.State: WAITING (on object monitor)
            at java.lang.Object.wait(Native Method)
            - waiting on <0x00000006c001b940> (a java.lang.ref.Reference$Lock)
            at java.lang.Object.wait(Object.java:502)
            at java.lang.ref.Reference.tryHandlePending(Reference.java:191)
            - locked <0x00000006c001b940> (a java.lang.ref.Reference$Lock)
            at java.lang.ref.Reference$ReferenceHandler.run(Reference.java:153)

       Locked ownable synchronizers:
            - None

    "VM Thread" os_prio=31 tid=0x00007fc9df00b800 nid=0x2c03 runnable 

    "GC task thread#0 (ParallelGC)" os_prio=31 tid=0x00007fc9de805000 nid=0x1e07 runnable 

    "GC task thread#1 (ParallelGC)" os_prio=31 tid=0x00007fc9de003800 nid=0x2a03 runnable 

    "GC task thread#2 (ParallelGC)" os_prio=31 tid=0x00007fc9df002000 nid=0x5403 runnable 

    "GC task thread#3 (ParallelGC)" os_prio=31 tid=0x00007fc9df002800 nid=0x5203 runnable 

    "VM Periodic Task Thread" os_prio=31 tid=0x00007fc9df11a800 nid=0x3a03 waiting on condition 

    JNI global references: 1087


    Found one Java-level deadlock:
    =============================
    "mythread2":
      waiting for ownable synchronizer 0x000000076f5d4330, (a java.util.concurrent.locks.ReentrantLock$NonfairSync),
      which is held by "mythread1"
    "mythread1":
      waiting for ownable synchronizer 0x000000076f5d4360, (a java.util.concurrent.locks.ReentrantLock$NonfairSync),
      which is held by "mythread2"

    Java stack information for the threads listed above:
    ===================================================
    "mythread2":
            at sun.misc.Unsafe.park(Native Method)
            - parking to wait for  <0x000000076f5d4330> (a java.util.concurrent.locks.ReentrantLock$NonfairSync)
            at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
            at java.util.concurrent.locks.AbstractQueuedSynchronizer.parkAndCheckInterrupt(AbstractQueuedSynchronizer.java:836)
            at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquireQueued(AbstractQueuedSynchronizer.java:870)
            at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquire(AbstractQueuedSynchronizer.java:1199)
            at java.util.concurrent.locks.ReentrantLock$NonfairSync.lock(ReentrantLock.java:209)
            at java.util.concurrent.locks.ReentrantLock.lock(ReentrantLock.java:285)
            at com.nicksxs.thread_dump_demo.ThreadDumpDemoApplication$2.run(ThreadDumpDemoApplication.java:34)
    "mythread1":
            at sun.misc.Unsafe.park(Native Method)
            - parking to wait for  <0x000000076f5d4360> (a java.util.concurrent.locks.ReentrantLock$NonfairSync)
            at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
            at java.util.concurrent.locks.AbstractQueuedSynchronizer.parkAndCheckInterrupt(AbstractQueuedSynchronizer.java:836)
            at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquireQueued(AbstractQueuedSynchronizer.java:870)
            at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquire(AbstractQueuedSynchronizer.java:1199)
            at java.util.concurrent.locks.ReentrantLock$NonfairSync.lock(ReentrantLock.java:209)
            at java.util.concurrent.locks.ReentrantLock.lock(ReentrantLock.java:285)
            at com.nicksxs.thread_dump_demo.ThreadDumpDemoApplication$1.run(ThreadDumpDemoApplication.java:22)

    Found 1 deadlock.
    -

    前面的信息其实上次就看过了，后面就可以发现有个死锁了，

    上面比较长，把主要的截出来，就是这边的，这点就很强大了。

    -

    jmap

    惯例还是看一下帮助信息

    这个相对命令比较多，不过因为现在 dump 下来我们可能会用文件模式，然后将文件下载下来使用 mat 进行分析，所以可以使用
    jmap -dump:live,format=b,file=heap.bin <pid>
    命令照着上面看的就是打印活着的对象，然后以二进制格式，文件名叫 heap.bin 然后最后就是进程 id，打印出来以后可以用 mat 打开

    这样就可以很清晰的看到应用里的各种信息，jmap 直接在命令中还可以看很多信息，比如使用jmap -histo <pid>打印对象的实例数和对象占用的内存

    jmap -finalizerinfo <pid> 打印正在等候回收的对象

    +
    2020-08-02 21:50:32
+Full thread dump Java HotSpot(TM) 64-Bit Server VM (25.201-b09 mixed mode):
+
+"DestroyJavaVM" #147 prio=5 os_prio=31 tid=0x00007fc9dd807000 nid=0x2603 waiting on condition [0x0000000000000000]
+   java.lang.Thread.State: RUNNABLE
+
+   Locked ownable synchronizers:
+        - None
+
+"mythread2" #140 prio=5 os_prio=31 tid=0x00007fc9dd877000 nid=0x9903 waiting on condition [0x0000700006fb9000]
+   java.lang.Thread.State: WAITING (parking)
+        at sun.misc.Unsafe.park(Native Method)
+        - parking to wait for  <0x000000076f5d4330> (a java.util.concurrent.locks.ReentrantLock$NonfairSync)
+        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
+        at java.util.concurrent.locks.AbstractQueuedSynchronizer.parkAndCheckInterrupt(AbstractQueuedSynchronizer.java:836)
+        at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquireQueued(AbstractQueuedSynchronizer.java:870)
+        at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquire(AbstractQueuedSynchronizer.java:1199)
+        at java.util.concurrent.locks.ReentrantLock$NonfairSync.lock(ReentrantLock.java:209)
+        at java.util.concurrent.locks.ReentrantLock.lock(ReentrantLock.java:285)
+        at com.nicksxs.thread_dump_demo.ThreadDumpDemoApplication$2.run(ThreadDumpDemoApplication.java:34)
+
+   Locked ownable synchronizers:
+        - <0x000000076f5d4360> (a java.util.concurrent.locks.ReentrantLock$NonfairSync)
+
+"mythread1" #139 prio=5 os_prio=31 tid=0x00007fc9de873800 nid=0x9a03 waiting on condition [0x0000700006eb6000]
+   java.lang.Thread.State: WAITING (parking)
+        at sun.misc.Unsafe.park(Native Method)
+        - parking to wait for  <0x000000076f5d4360> (a java.util.concurrent.locks.ReentrantLock$NonfairSync)
+        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
+        at java.util.concurrent.locks.AbstractQueuedSynchronizer.parkAndCheckInterrupt(AbstractQueuedSynchronizer.java:836)
+        at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquireQueued(AbstractQueuedSynchronizer.java:870)
+        at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquire(AbstractQueuedSynchronizer.java:1199)
+        at java.util.concurrent.locks.ReentrantLock$NonfairSync.lock(ReentrantLock.java:209)
+        at java.util.concurrent.locks.ReentrantLock.lock(ReentrantLock.java:285)
+        at com.nicksxs.thread_dump_demo.ThreadDumpDemoApplication$1.run(ThreadDumpDemoApplication.java:22)
+
+   Locked ownable synchronizers:
+        - <0x000000076f5d4330> (a java.util.concurrent.locks.ReentrantLock$NonfairSync)
+
+"http-nio-8080-Acceptor" #137 daemon prio=5 os_prio=31 tid=0x00007fc9de1ac000 nid=0x9b03 runnable [0x0000700006db3000]
+   java.lang.Thread.State: RUNNABLE
+        at sun.nio.ch.ServerSocketChannelImpl.accept0(Native Method)
+        at sun.nio.ch.ServerSocketChannelImpl.accept(ServerSocketChannelImpl.java:422)
+        at sun.nio.ch.ServerSocketChannelImpl.accept(ServerSocketChannelImpl.java:250)
+        - locked <0x000000076f1e4820> (a java.lang.Object)
+        at org.apache.tomcat.util.net.NioEndpoint.serverSocketAccept(NioEndpoint.java:469)
+        at org.apache.tomcat.util.net.NioEndpoint.serverSocketAccept(NioEndpoint.java:71)
+        at org.apache.tomcat.util.net.Acceptor.run(Acceptor.java:95)
+        at java.lang.Thread.run(Thread.java:748)
+
+   Locked ownable synchronizers:
+        - None
+
+"http-nio-8080-ClientPoller" #136 daemon prio=5 os_prio=31 tid=0x00007fc9dd876800 nid=0x6503 runnable [0x0000700006cb0000]
+   java.lang.Thread.State: RUNNABLE
+        at sun.nio.ch.KQueueArrayWrapper.kevent0(Native Method)
+        at sun.nio.ch.KQueueArrayWrapper.poll(KQueueArrayWrapper.java:198)
+        at sun.nio.ch.KQueueSelectorImpl.doSelect(KQueueSelectorImpl.java:117)
+        at sun.nio.ch.SelectorImpl.lockAndDoSelect(SelectorImpl.java:86)
+        - locked <0x000000076f2978c8> (a sun.nio.ch.Util$3)
+        - locked <0x000000076f2978b8> (a java.util.Collections$UnmodifiableSet)
+        - locked <0x000000076f297798> (a sun.nio.ch.KQueueSelectorImpl)
+        at sun.nio.ch.SelectorImpl.select(SelectorImpl.java:97)
+        at org.apache.tomcat.util.net.NioEndpoint$Poller.run(NioEndpoint.java:709)
+        at java.lang.Thread.run(Thread.java:748)
+
+   Locked ownable synchronizers:
+        - None
+
+"http-nio-8080-exec-10" #135 daemon prio=5 os_prio=31 tid=0x00007fc9de1af000 nid=0x9d03 waiting on condition [0x0000700006bad000]
+   java.lang.Thread.State: WAITING (parking)
+        at sun.misc.Unsafe.park(Native Method)
+        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
+        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
+        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
+        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
+        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
+        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
+        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
+        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
+        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
+        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
+        at java.lang.Thread.run(Thread.java:748)
+
+   Locked ownable synchronizers:
+        - None
+
+"http-nio-8080-exec-9" #134 daemon prio=5 os_prio=31 tid=0x00007fc9de1ab800 nid=0x6403 waiting on condition [0x0000700006aaa000]
+   java.lang.Thread.State: WAITING (parking)
+        at sun.misc.Unsafe.park(Native Method)
+        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
+        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
+        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
+        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
+        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
+        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
+        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
+        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
+        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
+        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
+        at java.lang.Thread.run(Thread.java:748)
+
+   Locked ownable synchronizers:
+        - None
+
+"http-nio-8080-exec-8" #133 daemon prio=5 os_prio=31 tid=0x00007fc9de873000 nid=0x9f03 waiting on condition [0x00007000069a7000]
+   java.lang.Thread.State: WAITING (parking)
+        at sun.misc.Unsafe.park(Native Method)
+        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
+        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
+        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
+        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
+        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
+        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
+        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
+        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
+        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
+        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
+        at java.lang.Thread.run(Thread.java:748)
+
+   Locked ownable synchronizers:
+        - None
+
+"http-nio-8080-exec-7" #132 daemon prio=5 os_prio=31 tid=0x00007fc9df0a1800 nid=0xa103 waiting on condition [0x00007000068a4000]
+   java.lang.Thread.State: WAITING (parking)
+        at sun.misc.Unsafe.park(Native Method)
+        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
+        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
+        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
+        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
+        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
+        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
+        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
+        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
+        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
+        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
+        at java.lang.Thread.run(Thread.java:748)
+
+   Locked ownable synchronizers:
+        - None
+
+"http-nio-8080-exec-6" #131 daemon prio=5 os_prio=31 tid=0x00007fc9df242800 nid=0x6103 waiting on condition [0x00007000067a1000]
+   java.lang.Thread.State: WAITING (parking)
+        at sun.misc.Unsafe.park(Native Method)
+        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
+        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
+        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
+        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
+        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
+        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
+        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
+        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
+        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
+        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
+        at java.lang.Thread.run(Thread.java:748)
+
+   Locked ownable synchronizers:
+        - None
+
+"http-nio-8080-exec-5" #130 daemon prio=5 os_prio=31 tid=0x00007fc9de872000 nid=0x5f03 waiting on condition [0x000070000669e000]
+   java.lang.Thread.State: WAITING (parking)
+        at sun.misc.Unsafe.park(Native Method)
+        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
+        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
+        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
+        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
+        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
+        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
+        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
+        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
+        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
+        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
+        at java.lang.Thread.run(Thread.java:748)
+
+   Locked ownable synchronizers:
+        - None
+
+"http-nio-8080-exec-4" #129 daemon prio=5 os_prio=31 tid=0x00007fc9de1a6000 nid=0x5e03 waiting on condition [0x000070000659b000]
+   java.lang.Thread.State: WAITING (parking)
+        at sun.misc.Unsafe.park(Native Method)
+        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
+        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
+        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
+        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
+        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
+        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
+        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
+        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
+        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
+        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
+        at java.lang.Thread.run(Thread.java:748)
+
+   Locked ownable synchronizers:
+        - None
+
+"http-nio-8080-exec-3" #128 daemon prio=5 os_prio=31 tid=0x00007fc9de871800 nid=0x5c03 waiting on condition [0x0000700006498000]
+   java.lang.Thread.State: WAITING (parking)
+        at sun.misc.Unsafe.park(Native Method)
+        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
+        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
+        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
+        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
+        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
+        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
+        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
+        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
+        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
+        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
+        at java.lang.Thread.run(Thread.java:748)
+
+   Locked ownable synchronizers:
+        - None
+
+"http-nio-8080-exec-2" #127 daemon prio=5 os_prio=31 tid=0x00007fc9dead9000 nid=0x5b03 waiting on condition [0x0000700006395000]
+   java.lang.Thread.State: WAITING (parking)
+        at sun.misc.Unsafe.park(Native Method)
+        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
+        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
+        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
+        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
+        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
+        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
+        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
+        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
+        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
+        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
+        at java.lang.Thread.run(Thread.java:748)
+
+   Locked ownable synchronizers:
+        - None
+
+"http-nio-8080-exec-1" #126 daemon prio=5 os_prio=31 tid=0x00007fc9ddb00000 nid=0x5a03 waiting on condition [0x0000700006292000]
+   java.lang.Thread.State: WAITING (parking)
+        at sun.misc.Unsafe.park(Native Method)
+        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
+        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
+        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
+        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
+        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
+        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
+        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
+        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
+        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
+        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
+        at java.lang.Thread.run(Thread.java:748)
+
+   Locked ownable synchronizers:
+        - None
+
+"http-nio-8080-BlockPoller" #125 daemon prio=5 os_prio=31 tid=0x00007fc9df242000 nid=0xa503 runnable [0x000070000618f000]
+   java.lang.Thread.State: RUNNABLE
+        at sun.nio.ch.KQueueArrayWrapper.kevent0(Native Method)
+        at sun.nio.ch.KQueueArrayWrapper.poll(KQueueArrayWrapper.java:198)
+        at sun.nio.ch.KQueueSelectorImpl.doSelect(KQueueSelectorImpl.java:117)
+        at sun.nio.ch.SelectorImpl.lockAndDoSelect(SelectorImpl.java:86)
+        - locked <0x000000076f1eea30> (a sun.nio.ch.Util$3)
+        - locked <0x000000076f1ee198> (a java.util.Collections$UnmodifiableSet)
+        - locked <0x000000076f1ee010> (a sun.nio.ch.KQueueSelectorImpl)
+        at sun.nio.ch.SelectorImpl.select(SelectorImpl.java:97)
+        at org.apache.tomcat.util.net.NioBlockingSelector$BlockPoller.run(NioBlockingSelector.java:313)
+
+   Locked ownable synchronizers:
+        - None
+
+"container-0" #124 prio=5 os_prio=31 tid=0x00007fc9df06a000 nid=0x5803 waiting on condition [0x000070000608c000]
+   java.lang.Thread.State: TIMED_WAITING (sleeping)
+        at java.lang.Thread.sleep(Native Method)
+        at org.apache.catalina.core.StandardServer.await(StandardServer.java:570)
+        at org.springframework.boot.web.embedded.tomcat.TomcatWebServer$1.run(TomcatWebServer.java:197)
+
+   Locked ownable synchronizers:
+        - None
+
+"Catalina-utility-2" #123 prio=1 os_prio=31 tid=0x00007fc9de886000 nid=0xa80f waiting on condition [0x0000700005f89000]
+   java.lang.Thread.State: WAITING (parking)
+        at sun.misc.Unsafe.park(Native Method)
+        - parking to wait for  <0x000000076c88ab58> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
+        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
+        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
+        at java.util.concurrent.ScheduledThreadPoolExecutor$DelayedWorkQueue.take(ScheduledThreadPoolExecutor.java:1088)
+        at java.util.concurrent.ScheduledThreadPoolExecutor$DelayedWorkQueue.take(ScheduledThreadPoolExecutor.java:809)
+        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
+        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
+        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
+        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
+        at java.lang.Thread.run(Thread.java:748)
+
+   Locked ownable synchronizers:
+        - None
+
+"Catalina-utility-1" #122 prio=1 os_prio=31 tid=0x00007fc9de884000 nid=0x5667 waiting on condition [0x0000700005e86000]
+   java.lang.Thread.State: TIMED_WAITING (parking)
+        at sun.misc.Unsafe.park(Native Method)
+        - parking to wait for  <0x000000076c88ab58> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
+        at java.util.concurrent.locks.LockSupport.parkNanos(LockSupport.java:215)
+        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.awaitNanos(AbstractQueuedSynchronizer.java:2078)
+        at java.util.concurrent.ScheduledThreadPoolExecutor$DelayedWorkQueue.take(ScheduledThreadPoolExecutor.java:1093)
+        at java.util.concurrent.ScheduledThreadPoolExecutor$DelayedWorkQueue.take(ScheduledThreadPoolExecutor.java:809)
+        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
+        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
+        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
+        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
+        at java.lang.Thread.run(Thread.java:748)
+
+   Locked ownable synchronizers:
+        - None
+
+"RMI Scheduler(0)" #15 daemon prio=5 os_prio=31 tid=0x00007fc9de9ee000 nid=0x5503 waiting on condition [0x0000700005d83000]
+   java.lang.Thread.State: TIMED_WAITING (parking)
+        at sun.misc.Unsafe.park(Native Method)
+        - parking to wait for  <0x00000006c0015410> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
+        at java.util.concurrent.locks.LockSupport.parkNanos(LockSupport.java:215)
+        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.awaitNanos(AbstractQueuedSynchronizer.java:2078)
+        at java.util.concurrent.ScheduledThreadPoolExecutor$DelayedWorkQueue.take(ScheduledThreadPoolExecutor.java:1093)
+        at java.util.concurrent.ScheduledThreadPoolExecutor$DelayedWorkQueue.take(ScheduledThreadPoolExecutor.java:809)
+        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
+        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
+        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
+        at java.lang.Thread.run(Thread.java:748)
+
+   Locked ownable synchronizers:
+        - None
+
+"Attach Listener" #13 daemon prio=9 os_prio=31 tid=0x00007fc9df149800 nid=0x3c07 waiting on condition [0x0000000000000000]
+   java.lang.Thread.State: RUNNABLE
+
+   Locked ownable synchronizers:
+        - None
+
+"RMI TCP Accept-0" #11 daemon prio=5 os_prio=31 tid=0x00007fc9df100000 nid=0x4003 runnable [0x0000700005977000]
+   java.lang.Thread.State: RUNNABLE
+        at java.net.PlainSocketImpl.socketAccept(Native Method)
+        at java.net.AbstractPlainSocketImpl.accept(AbstractPlainSocketImpl.java:409)
+        at java.net.ServerSocket.implAccept(ServerSocket.java:545)
+        at java.net.ServerSocket.accept(ServerSocket.java:513)
+        at sun.management.jmxremote.LocalRMIServerSocketFactory$1.accept(LocalRMIServerSocketFactory.java:52)
+        at sun.rmi.transport.tcp.TCPTransport$AcceptLoop.executeAcceptLoop(TCPTransport.java:405)
+        at sun.rmi.transport.tcp.TCPTransport$AcceptLoop.run(TCPTransport.java:377)
+        at java.lang.Thread.run(Thread.java:748)
+
+   Locked ownable synchronizers:
+        - None
+
+"Service Thread" #9 daemon prio=9 os_prio=31 tid=0x00007fc9df0ce800 nid=0x4103 runnable [0x0000000000000000]
+   java.lang.Thread.State: RUNNABLE
+
+   Locked ownable synchronizers:
+        - None
+
+"C1 CompilerThread2" #8 daemon prio=9 os_prio=31 tid=0x00007fc9df0ce000 nid=0x4203 waiting on condition [0x0000000000000000]
+   java.lang.Thread.State: RUNNABLE
+
+   Locked ownable synchronizers:
+        - None
+
+"C2 CompilerThread1" #7 daemon prio=9 os_prio=31 tid=0x00007fc9de0a3800 nid=0x3503 waiting on condition [0x0000000000000000]
+   java.lang.Thread.State: RUNNABLE
+
+   Locked ownable synchronizers:
+        - None
+
+"C2 CompilerThread0" #6 daemon prio=9 os_prio=31 tid=0x00007fc9de89b000 nid=0x3403 waiting on condition [0x0000000000000000]
+   java.lang.Thread.State: RUNNABLE
+
+   Locked ownable synchronizers:
+        - None
+
+"Monitor Ctrl-Break" #5 daemon prio=5 os_prio=31 tid=0x00007fc9df0ca000 nid=0x3303 runnable [0x0000700005468000]
+   java.lang.Thread.State: RUNNABLE
+        at java.net.SocketInputStream.socketRead0(Native Method)
+        at java.net.SocketInputStream.socketRead(SocketInputStream.java:116)
+        at java.net.SocketInputStream.read(SocketInputStream.java:171)
+        at java.net.SocketInputStream.read(SocketInputStream.java:141)
+        at sun.nio.cs.StreamDecoder.readBytes(StreamDecoder.java:284)
+        at sun.nio.cs.StreamDecoder.implRead(StreamDecoder.java:326)
+        at sun.nio.cs.StreamDecoder.read(StreamDecoder.java:178)
+        - locked <0x00000006c001b760> (a java.io.InputStreamReader)
+        at java.io.InputStreamReader.read(InputStreamReader.java:184)
+        at java.io.BufferedReader.fill(BufferedReader.java:161)
+        at java.io.BufferedReader.readLine(BufferedReader.java:324)
+        - locked <0x00000006c001b760> (a java.io.InputStreamReader)
+        at java.io.BufferedReader.readLine(BufferedReader.java:389)
+        at com.intellij.rt.execution.application.AppMainV2$1.run(AppMainV2.java:64)
+
+   Locked ownable synchronizers:
+        - None
+
+"Signal Dispatcher" #4 daemon prio=9 os_prio=31 tid=0x00007fc9de824000 nid=0x4503 runnable [0x0000000000000000]
+   java.lang.Thread.State: RUNNABLE
+
+   Locked ownable synchronizers:
+        - None
+
+"Finalizer" #3 daemon prio=8 os_prio=31 tid=0x00007fc9dd811800 nid=0x4f03 in Object.wait() [0x0000700005262000]
+   java.lang.Thread.State: WAITING (on object monitor)
+        at java.lang.Object.wait(Native Method)
+        - waiting on <0x00000006c0008348> (a java.lang.ref.ReferenceQueue$Lock)
+        at java.lang.ref.ReferenceQueue.remove(ReferenceQueue.java:144)
+        - locked <0x00000006c0008348> (a java.lang.ref.ReferenceQueue$Lock)
+        at java.lang.ref.ReferenceQueue.remove(ReferenceQueue.java:165)
+        at java.lang.ref.Finalizer$FinalizerThread.run(Finalizer.java:216)
+
+   Locked ownable synchronizers:
+        - None
+
+"Reference Handler" #2 daemon prio=10 os_prio=31 tid=0x00007fc9de02a000 nid=0x5003 in Object.wait() [0x000070000515f000]
+   java.lang.Thread.State: WAITING (on object monitor)
+        at java.lang.Object.wait(Native Method)
+        - waiting on <0x00000006c001b940> (a java.lang.ref.Reference$Lock)
+        at java.lang.Object.wait(Object.java:502)
+        at java.lang.ref.Reference.tryHandlePending(Reference.java:191)
+        - locked <0x00000006c001b940> (a java.lang.ref.Reference$Lock)
+        at java.lang.ref.Reference$ReferenceHandler.run(Reference.java:153)
+
+   Locked ownable synchronizers:
+        - None
+
+"VM Thread" os_prio=31 tid=0x00007fc9df00b800 nid=0x2c03 runnable 
+
+"GC task thread#0 (ParallelGC)" os_prio=31 tid=0x00007fc9de805000 nid=0x1e07 runnable 
+
+"GC task thread#1 (ParallelGC)" os_prio=31 tid=0x00007fc9de003800 nid=0x2a03 runnable 
+
+"GC task thread#2 (ParallelGC)" os_prio=31 tid=0x00007fc9df002000 nid=0x5403 runnable 
+
+"GC task thread#3 (ParallelGC)" os_prio=31 tid=0x00007fc9df002800 nid=0x5203 runnable 
+
+"VM Periodic Task Thread" os_prio=31 tid=0x00007fc9df11a800 nid=0x3a03 waiting on condition 
+
+JNI global references: 1087
+
+
+Found one Java-level deadlock:
+=============================
+"mythread2":
+  waiting for ownable synchronizer 0x000000076f5d4330, (a java.util.concurrent.locks.ReentrantLock$NonfairSync),
+  which is held by "mythread1"
+"mythread1":
+  waiting for ownable synchronizer 0x000000076f5d4360, (a java.util.concurrent.locks.ReentrantLock$NonfairSync),
+  which is held by "mythread2"
+
+Java stack information for the threads listed above:
+===================================================
+"mythread2":
+        at sun.misc.Unsafe.park(Native Method)
+        - parking to wait for  <0x000000076f5d4330> (a java.util.concurrent.locks.ReentrantLock$NonfairSync)
+        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
+        at java.util.concurrent.locks.AbstractQueuedSynchronizer.parkAndCheckInterrupt(AbstractQueuedSynchronizer.java:836)
+        at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquireQueued(AbstractQueuedSynchronizer.java:870)
+        at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquire(AbstractQueuedSynchronizer.java:1199)
+        at java.util.concurrent.locks.ReentrantLock$NonfairSync.lock(ReentrantLock.java:209)
+        at java.util.concurrent.locks.ReentrantLock.lock(ReentrantLock.java:285)
+        at com.nicksxs.thread_dump_demo.ThreadDumpDemoApplication$2.run(ThreadDumpDemoApplication.java:34)
+"mythread1":
+        at sun.misc.Unsafe.park(Native Method)
+        - parking to wait for  <0x000000076f5d4360> (a java.util.concurrent.locks.ReentrantLock$NonfairSync)
+        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
+        at java.util.concurrent.locks.AbstractQueuedSynchronizer.parkAndCheckInterrupt(AbstractQueuedSynchronizer.java:836)
+        at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquireQueued(AbstractQueuedSynchronizer.java:870)
+        at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquire(AbstractQueuedSynchronizer.java:1199)
+        at java.util.concurrent.locks.ReentrantLock$NonfairSync.lock(ReentrantLock.java:209)
+        at java.util.concurrent.locks.ReentrantLock.lock(ReentrantLock.java:285)
+        at com.nicksxs.thread_dump_demo.ThreadDumpDemoApplication$1.run(ThreadDumpDemoApplication.java:22)
+
+Found 1 deadlock.
    +

    前面的信息其实上次就看过了，后面就可以发现有个死锁了，

    上面比较长，把主要的截出来，就是这边的，这点就很强大了。

    +

    jmap

    惯例还是看一下帮助信息

    这个相对命令比较多，不过因为现在 dump 下来我们可能会用文件模式，然后将文件下载下来使用 mat 进行分析，所以可以使用
    jmap -dump:live,format=b,file=heap.bin <pid>
    命令照着上面看的就是打印活着的对象，然后以二进制格式，文件名叫 heap.bin 然后最后就是进程 id，打印出来以后可以用 mat 打开

    这样就可以很清晰的看到应用里的各种信息，jmap 直接在命令中还可以看很多信息，比如使用jmap -histo <pid>打印对象的实例数和对象占用的内存

    jmap -finalizerinfo <pid> 打印正在等候回收的对象

    小tips

    对于一些应用内存已经占满了，jstack 和 jmap 可能会连不上的情况，可以使用-F参数强制打印线程或者 dump 文件，但是要注意这两者使用的用户必须与 java 进程启动用户一致，并且使用的 jdk 也要一致

    @@ -472,7 +959,7 @@
    -
    1. 1. jstack & jps
    2. 2. jmap
      1. 2.1. 小tips
    +
    1. 1. jstack & jps
    2. 2. jmap
      1. 2.1. 小tips
    diff --git a/2020/08/06/Linux-下-grep-命令的一点小技巧/index.html b/2020/08/06/Linux-下-grep-命令的一点小技巧/index.html index adb0c972d6..9fc942f355 100644 --- a/2020/08/06/Linux-下-grep-命令的一点小技巧/index.html +++ b/2020/08/06/Linux-下-grep-命令的一点小技巧/index.html @@ -4,7 +4,7 @@ - + @@ -26,22 +26,20 @@ var CONFIG = {"hostname":"nicksxs.me","root":"/","scheme":"Pisces","version":"7.8.0","exturl":false,"sidebar":{"position":"left","display":"post","padding":18,"offset":12,"onmobile":false},"copycode":{"enable":true,"show_result":false,"style":null},"back2top":{"enable":true,"sidebar":false,"scrollpercent":false},"bookmark":{"enable":false,"color":"#222","save":"auto"},"fancybox":true,"mediumzoom":false,"lazyload":true,"pangu":false,"comments":{"style":"tabs","active":null,"storage":true,"lazyload":false,"nav":null},"algolia":{"hits":{"per_page":10},"labels":{"input_placeholder":"Search for Posts","hits_empty":"We didn't find any results for the search: ${query}","hits_stats":"${hits} results found in ${time} ms"}},"localsearch":{"enable":false,"trigger":"auto","top_n_per_article":1,"unescape":false,"preload":false},"motion":{"enable":true,"async":false,"transition":{"post_block":"fadeIn","post_header":"slideDownIn","post_body":"slideDownIn","coll_header":"slideLeftIn","sidebar":"slideUpIn"}}}; - + - + + - + - + - - - @@ -232,9 +230,8 @@     Posted on - - +     @@ -307,16 +304,20 @@

    用了比较久的 grep 命令，其实都只是用了最最基本的功能来查日志，

    譬如

    -
    1
    2

    grep 'xxx' xxxx.log
    +
    
+grep 'xxx' xxxx.log
+

    然后有挺多情况比如想要找日志里带一些符号什么的，就需要用到一些特殊的

    比如这样\"userId\":\"123456\"，因为比如用户 ID 有时候会跟其他的 id 一样，只用具体的值 123456 来查的话干扰信息太多了，如果直接这样

    -
    1
    2

    grep '\"userId\":\"123456\"' xxxx.log
    +
    
+grep '\"userId\":\"123456\"' xxxx.log
+

    好像不行，盲猜就是符号的问题，特别是\和"这两个，

    之前一直是想试一下，但是没成功，昨天在排查一个问题的时候发现了，只要把这些都转义了就行了

    grep '\\\"userId\\\":\\\"123456\\\"' xxxx.log

    -

    +

    diff --git a/2020/08/16/周末我在老丈人家打了天小工/index.html b/2020/08/16/周末我在老丈人家打了天小工/index.html index 4f0e83b6bf..8c975160f2 100644 --- a/2020/08/16/周末我在老丈人家打了天小工/index.html +++ b/2020/08/16/周末我在老丈人家打了天小工/index.html @@ -4,7 +4,7 @@ - + @@ -32,8 +32,9 @@ + - + @@ -229,9 +230,8 @@     Posted on - - +     diff --git a/2020/08/22/Filter-Intercepter-Aop-啥-啥-啥-这些都是啥/index.html b/2020/08/22/Filter-Intercepter-Aop-啥-啥-啥-这些都是啥/index.html index 192246102c..f21125c48b 100644 --- a/2020/08/22/Filter-Intercepter-Aop-啥-啥-啥-这些都是啥/index.html +++ b/2020/08/22/Filter-Intercepter-Aop-啥-啥-啥-这些都是啥/index.html @@ -4,7 +4,7 @@ - + @@ -32,10 +32,11 @@ + - + @@ -44,6 +45,7 @@ + @@ -237,13 +239,6 @@ - - - - - Edited on - - @@ -318,18 +313,448 @@

    本来是想取个像现在那些公众号转了又转的文章标题，”面试官再问你xxxxx，就把这篇文章甩给他看”这种标题，但是觉得实在太 low 了，还是用一部我比较喜欢的电影里的一句台词，《人在囧途》里王宝强对着那张老板给他的欠条，看不懂字时候说的那句，这些都是些啥（第四声）
    当我刚开始面 Java 的时候，其实我真的没注意这方面的东西，实话说就是不知道这些是啥，开发中用过 Interceptor和 Aop，了解 aop 的实现原理，但是不知道 Java web 中的 Filter 是怎么回事，知道 dubbo 的 filter，就这样，所以被问到了的确是回答不出来，可能就觉得这个渣渣，这么简单的都不会，所以还是花点时间来看看这个是个啥，为了避免我口吐芬芳，还是耐下性子来简单说下这几个东西
    首先是 servlet，怎么去解释这个呢，因为之前是 PHPer，所以比较喜欢用它来举例子，在普通的 PHP 的 web 应用中一般有几部分组成，接受 HTTP 请求的是前置的 nginx 或者 apache，但是这俩玩意都是只能处理静态的请求，远古时代 PHP 和 HTML 混编是通过 apache 的 php module，跟后来 nginx 使用 php-fpm 其实道理类似，就是把请求中需要 PHP 处理的转发给 PHP，在 Java 中呢，是有个比较牛叉的叫 Tomcat 的，它可以把请求转成 servlet，而 servlet 其实就是一种实现了特定接口的 Java 代码，

    -
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    package javax.servlet;

    import java.io.IOException;

    /**
     * Defines methods that all servlets must implement.
     *
     * <p>
     * A servlet is a small Java program that runs within a Web server. Servlets
     * receive and respond to requests from Web clients, usually across HTTP, the
     * HyperText Transfer Protocol.
     *
     * <p>
     * To implement this interface, you can write a generic servlet that extends
     * <code>javax.servlet.GenericServlet</code> or an HTTP servlet that extends
     * <code>javax.servlet.http.HttpServlet</code>.
     *
     * <p>
     * This interface defines methods to initialize a servlet, to service requests,
     * and to remove a servlet from the server. These are known as life-cycle
     * methods and are called in the following sequence:
     * <ol>
     * <li>The servlet is constructed, then initialized with the <code>init</code>
     * method.
     * <li>Any calls from clients to the <code>service</code> method are handled.
     * <li>The servlet is taken out of service, then destroyed with the
     * <code>destroy</code> method, then garbage collected and finalized.
     * </ol>
     *
     * <p>
     * In addition to the life-cycle methods, this interface provides the
     * <code>getServletConfig</code> method, which the servlet can use to get any
     * startup information, and the <code>getServletInfo</code> method, which allows
     * the servlet to return basic information about itself, such as author,
     * version, and copyright.
     *
     * @see GenericServlet
     * @see javax.servlet.http.HttpServlet
     */
    public interface Servlet {

        /**
         * Called by the servlet container to indicate to a servlet that the servlet
         * is being placed into service.
         *
         * <p>
         * The servlet container calls the <code>init</code> method exactly once
         * after instantiating the servlet. The <code>init</code> method must
         * complete successfully before the servlet can receive any requests.
         *
         * <p>
         * The servlet container cannot place the servlet into service if the
         * <code>init</code> method
         * <ol>
         * <li>Throws a <code>ServletException</code>
         * <li>Does not return within a time period defined by the Web server
         * </ol>
         *
         *
         * @param config
         *            a <code>ServletConfig</code> object containing the servlet's
         *            configuration and initialization parameters
         *
         * @exception ServletException
         *                if an exception has occurred that interferes with the
         *                servlet's normal operation
         *
         * @see UnavailableException
         * @see #getServletConfig
         */
        public void init(ServletConfig config) throws ServletException;

        /**
         *
         * Returns a {@link ServletConfig} object, which contains initialization and
         * startup parameters for this servlet. The <code>ServletConfig</code>
         * object returned is the one passed to the <code>init</code> method.
         *
         * <p>
         * Implementations of this interface are responsible for storing the
         * <code>ServletConfig</code> object so that this method can return it. The
         * {@link GenericServlet} class, which implements this interface, already
         * does this.
         *
         * @return the <code>ServletConfig</code> object that initializes this
         *         servlet
         *
         * @see #init
         */
        public ServletConfig getServletConfig();

        /**
         * Called by the servlet container to allow the servlet to respond to a
         * request.
         *
         * <p>
         * This method is only called after the servlet's <code>init()</code> method
         * has completed successfully.
         *
         * <p>
         * The status code of the response always should be set for a servlet that
         * throws or sends an error.
         *
         *
         * <p>
         * Servlets typically run inside multithreaded servlet containers that can
         * handle multiple requests concurrently. Developers must be aware to
         * synchronize access to any shared resources such as files, network
         * connections, and as well as the servlet's class and instance variables.
         * More information on multithreaded programming in Java is available in <a
         * href
         * ="http://java.sun.com/Series/Tutorial/java/threads/multithreaded.html">
         * the Java tutorial on multi-threaded programming</a>.
         *
         *
         * @param req
         *            the <code>ServletRequest</code> object that contains the
         *            client's request
         *
         * @param res
         *            the <code>ServletResponse</code> object that contains the
         *            servlet's response
         *
         * @exception ServletException
         *                if an exception occurs that interferes with the servlet's
         *                normal operation
         *
         * @exception IOException
         *                if an input or output exception occurs
         */
        public void service(ServletRequest req, ServletResponse res)
                throws ServletException, IOException;

        /**
         * Returns information about the servlet, such as author, version, and
         * copyright.
         *
         * <p>
         * The string that this method returns should be plain text and not markup
         * of any kind (such as HTML, XML, etc.).
         *
         * @return a <code>String</code> containing servlet information
         */
        public String getServletInfo();

        /**
         * Called by the servlet container to indicate to a servlet that the servlet
         * is being taken out of service. This method is only called once all
         * threads within the servlet's <code>service</code> method have exited or
         * after a timeout period has passed. After the servlet container calls this
         * method, it will not call the <code>service</code> method again on this
         * servlet.
         *
         * <p>
         * This method gives the servlet an opportunity to clean up any resources
         * that are being held (for example, memory, file handles, threads) and make
         * sure that any persistent state is synchronized with the servlet's current
         * state in memory.
         */
        public void destroy();
    }
    -

    重点看 servlet 的 service方法，就是接受请求，处理完了给响应，不说细节，不然光 Tomcat 的能说半年，所以呢再进一步去理解，其实就能知道，就是一个先后的问题，盗个图

    filter 跟后两者最大的不一样其实是一个基于 servlet，在非常外层做的处理，然后是 interceptor 的 prehandle 跟 posthandle，接着才是我们常规的 aop，就这么点事情，做个小试验吧(还是先补段代码吧)

    -

    Filter

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    // ---------------------------------------------------- FilterChain Methods

        /**
         * Invoke the next filter in this chain, passing the specified request
         * and response.  If there are no more filters in this chain, invoke
         * the <code>service()</code> method of the servlet itself.
         *
         * @param request The servlet request we are processing
         * @param response The servlet response we are creating
         *
         * @exception IOException if an input/output error occurs
         * @exception ServletException if a servlet exception occurs
         */
        @Override
        public void doFilter(ServletRequest request, ServletResponse response)
            throws IOException, ServletException {

            if( Globals.IS_SECURITY_ENABLED ) {
                final ServletRequest req = request;
                final ServletResponse res = response;
                try {
                    java.security.AccessController.doPrivileged(
                        new java.security.PrivilegedExceptionAction<Void>() {
                            @Override
                            public Void run()
                                throws ServletException, IOException {
                                internalDoFilter(req,res);
                                return null;
                            }
                        }
                    );
                } catch( PrivilegedActionException pe) {
                    Exception e = pe.getException();
                    if (e instanceof ServletException)
                        throw (ServletException) e;
                    else if (e instanceof IOException)
                        throw (IOException) e;
                    else if (e instanceof RuntimeException)
                        throw (RuntimeException) e;
                    else
                        throw new ServletException(e.getMessage(), e);
                }
            } else {
                internalDoFilter(request,response);
            }
        }
        private void internalDoFilter(ServletRequest request,
                                      ServletResponse response)
            throws IOException, ServletException {

            // Call the next filter if there is one
            if (pos < n) {
                ApplicationFilterConfig filterConfig = filters[pos++];
                try {
                    Filter filter = filterConfig.getFilter();

                    if (request.isAsyncSupported() && "false".equalsIgnoreCase(
                            filterConfig.getFilterDef().getAsyncSupported())) {
                        request.setAttribute(Globals.ASYNC_SUPPORTED_ATTR, Boolean.FALSE);
                    }
                    if( Globals.IS_SECURITY_ENABLED ) {
                        final ServletRequest req = request;
                        final ServletResponse res = response;
                        Principal principal =
                            ((HttpServletRequest) req).getUserPrincipal();

                        Object[] args = new Object[]{req, res, this};
                        SecurityUtil.doAsPrivilege ("doFilter", filter, classType, args, principal);
                    } else {
                        filter.doFilter(request, response, this);
                    }
                } catch (IOException | ServletException | RuntimeException e) {
                    throw e;
                } catch (Throwable e) {
                    e = ExceptionUtils.unwrapInvocationTargetException(e);
                    ExceptionUtils.handleThrowable(e);
                    throw new ServletException(sm.getString("filterChain.filter"), e);
                }
                return;
            }

            // We fell off the end of the chain -- call the servlet instance
            try {
                if (ApplicationDispatcher.WRAP_SAME_OBJECT) {
                    lastServicedRequest.set(request);
                    lastServicedResponse.set(response);
                }

                if (request.isAsyncSupported() && !servletSupportsAsync) {
                    request.setAttribute(Globals.ASYNC_SUPPORTED_ATTR,
                            Boolean.FALSE);
                }
                // Use potentially wrapped request from this point
                if ((request instanceof HttpServletRequest) &&
                        (response instanceof HttpServletResponse) &&
                        Globals.IS_SECURITY_ENABLED ) {
                    final ServletRequest req = request;
                    final ServletResponse res = response;
                    Principal principal =
                        ((HttpServletRequest) req).getUserPrincipal();
                    Object[] args = new Object[]{req, res};
                    SecurityUtil.doAsPrivilege("service",
                                               servlet,
                                               classTypeUsedInService,
                                               args,
                                               principal);
                } else {
                    servlet.service(request, response);
                }
            } catch (IOException | ServletException | RuntimeException e) {
                throw e;
            } catch (Throwable e) {
                e = ExceptionUtils.unwrapInvocationTargetException(e);
                ExceptionUtils.handleThrowable(e);
                throw new ServletException(sm.getString("filterChain.servlet"), e);
            } finally {
                if (ApplicationDispatcher.WRAP_SAME_OBJECT) {
                    lastServicedRequest.set(null);
                    lastServicedResponse.set(null);
                }
            }
        }
    +
    
+package javax.servlet;
+
+import java.io.IOException;
+
+/**
+ * Defines methods that all servlets must implement.
+ *
+ * <p>
+ * A servlet is a small Java program that runs within a Web server. Servlets
+ * receive and respond to requests from Web clients, usually across HTTP, the
+ * HyperText Transfer Protocol.
+ *
+ * <p>
+ * To implement this interface, you can write a generic servlet that extends
+ * <code>javax.servlet.GenericServlet</code> or an HTTP servlet that extends
+ * <code>javax.servlet.http.HttpServlet</code>.
+ *
+ * <p>
+ * This interface defines methods to initialize a servlet, to service requests,
+ * and to remove a servlet from the server. These are known as life-cycle
+ * methods and are called in the following sequence:
+ * <ol>
+ * <li>The servlet is constructed, then initialized with the <code>init</code>
+ * method.
+ * <li>Any calls from clients to the <code>service</code> method are handled.
+ * <li>The servlet is taken out of service, then destroyed with the
+ * <code>destroy</code> method, then garbage collected and finalized.
+ * </ol>
+ *
+ * <p>
+ * In addition to the life-cycle methods, this interface provides the
+ * <code>getServletConfig</code> method, which the servlet can use to get any
+ * startup information, and the <code>getServletInfo</code> method, which allows
+ * the servlet to return basic information about itself, such as author,
+ * version, and copyright.
+ *
+ * @see GenericServlet
+ * @see javax.servlet.http.HttpServlet
+ */
+public interface Servlet {
+
+    /**
+     * Called by the servlet container to indicate to a servlet that the servlet
+     * is being placed into service.
+     *
+     * <p>
+     * The servlet container calls the <code>init</code> method exactly once
+     * after instantiating the servlet. The <code>init</code> method must
+     * complete successfully before the servlet can receive any requests.
+     *
+     * <p>
+     * The servlet container cannot place the servlet into service if the
+     * <code>init</code> method
+     * <ol>
+     * <li>Throws a <code>ServletException</code>
+     * <li>Does not return within a time period defined by the Web server
+     * </ol>
+     *
+     *
+     * @param config
+     *            a <code>ServletConfig</code> object containing the servlet's
+     *            configuration and initialization parameters
+     *
+     * @exception ServletException
+     *                if an exception has occurred that interferes with the
+     *                servlet's normal operation
+     *
+     * @see UnavailableException
+     * @see #getServletConfig
+     */
+    public void init(ServletConfig config) throws ServletException;
+
+    /**
+     *
+     * Returns a {@link ServletConfig} object, which contains initialization and
+     * startup parameters for this servlet. The <code>ServletConfig</code>
+     * object returned is the one passed to the <code>init</code> method.
+     *
+     * <p>
+     * Implementations of this interface are responsible for storing the
+     * <code>ServletConfig</code> object so that this method can return it. The
+     * {@link GenericServlet} class, which implements this interface, already
+     * does this.
+     *
+     * @return the <code>ServletConfig</code> object that initializes this
+     *         servlet
+     *
+     * @see #init
+     */
+    public ServletConfig getServletConfig();
+
+    /**
+     * Called by the servlet container to allow the servlet to respond to a
+     * request.
+     *
+     * <p>
+     * This method is only called after the servlet's <code>init()</code> method
+     * has completed successfully.
+     *
+     * <p>
+     * The status code of the response always should be set for a servlet that
+     * throws or sends an error.
+     *
+     *
+     * <p>
+     * Servlets typically run inside multithreaded servlet containers that can
+     * handle multiple requests concurrently. Developers must be aware to
+     * synchronize access to any shared resources such as files, network
+     * connections, and as well as the servlet's class and instance variables.
+     * More information on multithreaded programming in Java is available in <a
+     * href
+     * ="http://java.sun.com/Series/Tutorial/java/threads/multithreaded.html">
+     * the Java tutorial on multi-threaded programming</a>.
+     *
+     *
+     * @param req
+     *            the <code>ServletRequest</code> object that contains the
+     *            client's request
+     *
+     * @param res
+     *            the <code>ServletResponse</code> object that contains the
+     *            servlet's response
+     *
+     * @exception ServletException
+     *                if an exception occurs that interferes with the servlet's
+     *                normal operation
+     *
+     * @exception IOException
+     *                if an input or output exception occurs
+     */
+    public void service(ServletRequest req, ServletResponse res)
+            throws ServletException, IOException;
+
+    /**
+     * Returns information about the servlet, such as author, version, and
+     * copyright.
+     *
+     * <p>
+     * The string that this method returns should be plain text and not markup
+     * of any kind (such as HTML, XML, etc.).
+     *
+     * @return a <code>String</code> containing servlet information
+     */
+    public String getServletInfo();
+
+    /**
+     * Called by the servlet container to indicate to a servlet that the servlet
+     * is being taken out of service. This method is only called once all
+     * threads within the servlet's <code>service</code> method have exited or
+     * after a timeout period has passed. After the servlet container calls this
+     * method, it will not call the <code>service</code> method again on this
+     * servlet.
+     *
+     * <p>
+     * This method gives the servlet an opportunity to clean up any resources
+     * that are being held (for example, memory, file handles, threads) and make
+     * sure that any persistent state is synchronized with the servlet's current
+     * state in memory.
+     */
+    public void destroy();
+}
+
    +

    重点看 servlet 的 service方法，就是接受请求，处理完了给响应，不说细节，不然光 Tomcat 的能说半年，所以呢再进一步去理解，其实就能知道，就是一个先后的问题，盗个图

    filter 跟后两者最大的不一样其实是一个基于 servlet，在非常外层做的处理，然后是 interceptor 的 prehandle 跟 posthandle，接着才是我们常规的 aop，就这么点事情，做个小试验吧(还是先补段代码吧)

    +

    Filter

    // ---------------------------------------------------- FilterChain Methods
+
+    /**
+     * Invoke the next filter in this chain, passing the specified request
+     * and response.  If there are no more filters in this chain, invoke
+     * the <code>service()</code> method of the servlet itself.
+     *
+     * @param request The servlet request we are processing
+     * @param response The servlet response we are creating
+     *
+     * @exception IOException if an input/output error occurs
+     * @exception ServletException if a servlet exception occurs
+     */
+    @Override
+    public void doFilter(ServletRequest request, ServletResponse response)
+        throws IOException, ServletException {
+
+        if( Globals.IS_SECURITY_ENABLED ) {
+            final ServletRequest req = request;
+            final ServletResponse res = response;
+            try {
+                java.security.AccessController.doPrivileged(
+                    new java.security.PrivilegedExceptionAction<Void>() {
+                        @Override
+                        public Void run()
+                            throws ServletException, IOException {
+                            internalDoFilter(req,res);
+                            return null;
+                        }
+                    }
+                );
+            } catch( PrivilegedActionException pe) {
+                Exception e = pe.getException();
+                if (e instanceof ServletException)
+                    throw (ServletException) e;
+                else if (e instanceof IOException)
+                    throw (IOException) e;
+                else if (e instanceof RuntimeException)
+                    throw (RuntimeException) e;
+                else
+                    throw new ServletException(e.getMessage(), e);
+            }
+        } else {
+            internalDoFilter(request,response);
+        }
+    }
+    private void internalDoFilter(ServletRequest request,
+                                  ServletResponse response)
+        throws IOException, ServletException {
+
+        // Call the next filter if there is one
+        if (pos < n) {
+            ApplicationFilterConfig filterConfig = filters[pos++];
+            try {
+                Filter filter = filterConfig.getFilter();
+
+                if (request.isAsyncSupported() && "false".equalsIgnoreCase(
+                        filterConfig.getFilterDef().getAsyncSupported())) {
+                    request.setAttribute(Globals.ASYNC_SUPPORTED_ATTR, Boolean.FALSE);
+                }
+                if( Globals.IS_SECURITY_ENABLED ) {
+                    final ServletRequest req = request;
+                    final ServletResponse res = response;
+                    Principal principal =
+                        ((HttpServletRequest) req).getUserPrincipal();
+
+                    Object[] args = new Object[]{req, res, this};
+                    SecurityUtil.doAsPrivilege ("doFilter", filter, classType, args, principal);
+                } else {
+                    filter.doFilter(request, response, this);
+                }
+            } catch (IOException | ServletException | RuntimeException e) {
+                throw e;
+            } catch (Throwable e) {
+                e = ExceptionUtils.unwrapInvocationTargetException(e);
+                ExceptionUtils.handleThrowable(e);
+                throw new ServletException(sm.getString("filterChain.filter"), e);
+            }
+            return;
+        }
+
+        // We fell off the end of the chain -- call the servlet instance
+        try {
+            if (ApplicationDispatcher.WRAP_SAME_OBJECT) {
+                lastServicedRequest.set(request);
+                lastServicedResponse.set(response);
+            }
+
+            if (request.isAsyncSupported() && !servletSupportsAsync) {
+                request.setAttribute(Globals.ASYNC_SUPPORTED_ATTR,
+                        Boolean.FALSE);
+            }
+            // Use potentially wrapped request from this point
+            if ((request instanceof HttpServletRequest) &&
+                    (response instanceof HttpServletResponse) &&
+                    Globals.IS_SECURITY_ENABLED ) {
+                final ServletRequest req = request;
+                final ServletResponse res = response;
+                Principal principal =
+                    ((HttpServletRequest) req).getUserPrincipal();
+                Object[] args = new Object[]{req, res};
+                SecurityUtil.doAsPrivilege("service",
+                                           servlet,
+                                           classTypeUsedInService,
+                                           args,
+                                           principal);
+            } else {
+                servlet.service(request, response);
+            }
+        } catch (IOException | ServletException | RuntimeException e) {
+            throw e;
+        } catch (Throwable e) {
+            e = ExceptionUtils.unwrapInvocationTargetException(e);
+            ExceptionUtils.handleThrowable(e);
+            throw new ServletException(sm.getString("filterChain.servlet"), e);
+        } finally {
+            if (ApplicationDispatcher.WRAP_SAME_OBJECT) {
+                lastServicedRequest.set(null);
+                lastServicedResponse.set(null);
+            }
+        }
+    }

    注意看这一行
    filter.doFilter(request, response, this);
    是不是看懂了，就是个 filter 链，但是这个代码在哪呢，org.apache.catalina.core.ApplicationFilterChain#doFilter
    然后是interceptor，

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    protected void doDispatch(HttpServletRequest request, HttpServletResponse response) throws Exception {
            HttpServletRequest processedRequest = request;
            HandlerExecutionChain mappedHandler = null;
            boolean multipartRequestParsed = false;
            WebAsyncManager asyncManager = WebAsyncUtils.getAsyncManager(request);

            try {
                try {
                    ModelAndView mv = null;
                    Object dispatchException = null;

                    try {
                        processedRequest = this.checkMultipart(request);
                        multipartRequestParsed = processedRequest != request;
                        mappedHandler = this.getHandler(processedRequest);
                        if (mappedHandler == null) {
                            this.noHandlerFound(processedRequest, response);
                            return;
                        }

                        HandlerAdapter ha = this.getHandlerAdapter(mappedHandler.getHandler());
                        String method = request.getMethod();
                        boolean isGet = "GET".equals(method);
                        if (isGet || "HEAD".equals(method)) {
                            long lastModified = ha.getLastModified(request, mappedHandler.getHandler());
                            if ((new ServletWebRequest(request, response)).checkNotModified(lastModified) && isGet) {
                                return;
                            }
                        }

                        /** 
                         * 看这里看这里‼️
                         */
                        if (!mappedHandler.applyPreHandle(processedRequest, response)) {
                            return;
                        }

                        mv = ha.handle(processedRequest, response, mappedHandler.getHandler());
                        if (asyncManager.isConcurrentHandlingStarted()) {
                            return;
                        }

                        this.applyDefaultViewName(processedRequest, mv);
                        /** 
                         * 再看这里看这里‼️
                         */
                        mappedHandler.applyPostHandle(processedRequest, response, mv);
                    } catch (Exception var20) {
                        dispatchException = var20;
                    } catch (Throwable var21) {
                        dispatchException = new NestedServletException("Handler dispatch failed", var21);
                    }

                    this.processDispatchResult(processedRequest, response, mappedHandler, mv, (Exception)dispatchException);
                } catch (Exception var22) {
                    this.triggerAfterCompletion(processedRequest, response, mappedHandler, var22);
                } catch (Throwable var23) {
                    this.triggerAfterCompletion(processedRequest, response, mappedHandler, new NestedServletException("Handler processing failed", var23));
                }

            } finally {
                if (asyncManager.isConcurrentHandlingStarted()) {
                    if (mappedHandler != null) {
                        mappedHandler.applyAfterConcurrentHandlingStarted(processedRequest, response);
                    }
                } else if (multipartRequestParsed) {
                    this.cleanupMultipart(processedRequest);
                }

            }
        }
    +
    protected void doDispatch(HttpServletRequest request, HttpServletResponse response) throws Exception {
+        HttpServletRequest processedRequest = request;
+        HandlerExecutionChain mappedHandler = null;
+        boolean multipartRequestParsed = false;
+        WebAsyncManager asyncManager = WebAsyncUtils.getAsyncManager(request);
+
+        try {
+            try {
+                ModelAndView mv = null;
+                Object dispatchException = null;
+
+                try {
+                    processedRequest = this.checkMultipart(request);
+                    multipartRequestParsed = processedRequest != request;
+                    mappedHandler = this.getHandler(processedRequest);
+                    if (mappedHandler == null) {
+                        this.noHandlerFound(processedRequest, response);
+                        return;
+                    }
+
+                    HandlerAdapter ha = this.getHandlerAdapter(mappedHandler.getHandler());
+                    String method = request.getMethod();
+                    boolean isGet = "GET".equals(method);
+                    if (isGet || "HEAD".equals(method)) {
+                        long lastModified = ha.getLastModified(request, mappedHandler.getHandler());
+                        if ((new ServletWebRequest(request, response)).checkNotModified(lastModified) && isGet) {
+                            return;
+                        }
+                    }
+
+                    /** 
+                     * 看这里看这里‼️
+                     */
+                    if (!mappedHandler.applyPreHandle(processedRequest, response)) {
+                        return;
+                    }
+
+                    mv = ha.handle(processedRequest, response, mappedHandler.getHandler());
+                    if (asyncManager.isConcurrentHandlingStarted()) {
+                        return;
+                    }
+
+                    this.applyDefaultViewName(processedRequest, mv);
+                    /** 
+                     * 再看这里看这里‼️
+                     */
+                    mappedHandler.applyPostHandle(processedRequest, response, mv);
+                } catch (Exception var20) {
+                    dispatchException = var20;
+                } catch (Throwable var21) {
+                    dispatchException = new NestedServletException("Handler dispatch failed", var21);
+                }
+
+                this.processDispatchResult(processedRequest, response, mappedHandler, mv, (Exception)dispatchException);
+            } catch (Exception var22) {
+                this.triggerAfterCompletion(processedRequest, response, mappedHandler, var22);
+            } catch (Throwable var23) {
+                this.triggerAfterCompletion(processedRequest, response, mappedHandler, new NestedServletException("Handler processing failed", var23));
+            }
+
+        } finally {
+            if (asyncManager.isConcurrentHandlingStarted()) {
+                if (mappedHandler != null) {
+                    mappedHandler.applyAfterConcurrentHandlingStarted(processedRequest, response);
+                }
+            } else if (multipartRequestParsed) {
+                this.cleanupMultipart(processedRequest);
+            }
+
+        }
+    }

    代码在哪呢，org.springframework.web.servlet.DispatcherServlet#doDispatch，然后才是我们自己写的 aop，是不是差不多明白了，嗯，接下来是例子
    写个 filter

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    public class DemoFilter extends HttpServlet implements Filter {
        @Override
        public void init(FilterConfig filterConfig) throws ServletException {
            System.out.println("==>DemoFilter启动");
        }

        @Override
        public void doFilter(ServletRequest servletRequest, ServletResponse servletResponse, FilterChain filterChain) throws IOException, ServletException {
            // 将请求转换成HttpServletRequest 请求
            HttpServletRequest req = (HttpServletRequest) servletRequest;
            HttpServletResponse resp = (HttpServletResponse) servletResponse;
            System.out.println("before filter");
            filterChain.doFilter(req, resp);
            System.out.println("after filter");
        }

        @Override
        public void destroy() {

        }
    }
    +
    public class DemoFilter extends HttpServlet implements Filter {
+    @Override
+    public void init(FilterConfig filterConfig) throws ServletException {
+        System.out.println("==>DemoFilter启动");
+    }
+
+    @Override
+    public void doFilter(ServletRequest servletRequest, ServletResponse servletResponse, FilterChain filterChain) throws IOException, ServletException {
+        // 将请求转换成HttpServletRequest 请求
+        HttpServletRequest req = (HttpServletRequest) servletRequest;
+        HttpServletResponse resp = (HttpServletResponse) servletResponse;
+        System.out.println("before filter");
+        filterChain.doFilter(req, resp);
+        System.out.println("after filter");
+    }
+
+    @Override
+    public void destroy() {
+
+    }
+}

    因为用的springboot，所以就不写 web.xml 了，写个配置类

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    @Configuration
    public class FilterConfiguration {
        @Bean
        public FilterRegistrationBean filterDemo4Registration() {
            FilterRegistrationBean registration = new FilterRegistrationBean();
            //注入过滤器
            registration.setFilter(new DemoFilter());
            //拦截规则
            registration.addUrlPatterns("/*");
            //过滤器名称
            registration.setName("DemoFilter");
            //是否自动注册 false 取消Filter的自动注册
            registration.setEnabled(true);
            //过滤器顺序
            registration.setOrder(1);
            return registration;
        }

    }
    +
    @Configuration
+public class FilterConfiguration {
+    @Bean
+    public FilterRegistrationBean filterDemo4Registration() {
+        FilterRegistrationBean registration = new FilterRegistrationBean();
+        //注入过滤器
+        registration.setFilter(new DemoFilter());
+        //拦截规则
+        registration.addUrlPatterns("/*");
+        //过滤器名称
+        registration.setName("DemoFilter");
+        //是否自动注册 false 取消Filter的自动注册
+        registration.setEnabled(true);
+        //过滤器顺序
+        registration.setOrder(1);
+        return registration;
+    }
+
+}

    然后再来个 interceptor 和 aop,以及一个简单的请求处理

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    public class DemoInterceptor extends HandlerInterceptorAdapter {
        @Override
        public boolean preHandle(HttpServletRequest request, HttpServletResponse response, Object handler) throws Exception {
            System.out.println("preHandle test");
            return true;
        }

        @Override
        public void postHandle(HttpServletRequest request, HttpServletResponse response, Object handler, ModelAndView modelAndView) throws Exception {
            System.out.println("postHandle test");
        }
    }
    @Aspect
    @Component
    public class DemoAspect {

        @Pointcut("execution( public * com.nicksxs.springbootdemo.demo.DemoController.*())")
        public void point() {

        }

        @Before("point()")
        public void doBefore(){
            System.out.println("==doBefore==");
        }

        @After("point()")
        public void doAfter(){
            System.out.println("==doAfter==");
        }
    }
    @RestController
    public class DemoController {

        @RequestMapping("/hello")
        @ResponseBody
        public String hello() {
            return "hello world";
        }
    }
    -

    好了，请求一下，看看 stdout，

    搞定完事儿~

    +
    public class DemoInterceptor extends HandlerInterceptorAdapter {
+    @Override
+    public boolean preHandle(HttpServletRequest request, HttpServletResponse response, Object handler) throws Exception {
+        System.out.println("preHandle test");
+        return true;
+    }
+
+    @Override
+    public void postHandle(HttpServletRequest request, HttpServletResponse response, Object handler, ModelAndView modelAndView) throws Exception {
+        System.out.println("postHandle test");
+    }
+}
+@Aspect
+@Component
+public class DemoAspect {
+
+    @Pointcut("execution( public * com.nicksxs.springbootdemo.demo.DemoController.*())")
+    public void point() {
+
+    }
+
+    @Before("point()")
+    public void doBefore(){
+        System.out.println("==doBefore==");
+    }
+
+    @After("point()")
+    public void doAfter(){
+        System.out.println("==doAfter==");
+    }
+}
+@RestController
+public class DemoController {
+
+    @RequestMapping("/hello")
+    @ResponseBody
+    public String hello() {
+        return "hello world";
+    }
+}
    +

    好了，请求一下，看看 stdout，

    搞定完事儿~

    diff --git a/2020/08/30/这周末我又在老丈人家打了天小工/index.html b/2020/08/30/这周末我又在老丈人家打了天小工/index.html index 22b33de2b7..24f185a111 100644 --- a/2020/08/30/这周末我又在老丈人家打了天小工/index.html +++ b/2020/08/30/这周末我又在老丈人家打了天小工/index.html @@ -4,7 +4,7 @@ - + @@ -32,8 +32,9 @@ + - + @@ -229,9 +230,8 @@     Posted on - - +     diff --git a/2020/09/06/mybatis-的-和-是有啥区别/index.html b/2020/09/06/mybatis-的-和-是有啥区别/index.html index 18be061ac3..af516261c7 100644 --- a/2020/09/06/mybatis-的-和-是有啥区别/index.html +++ b/2020/09/06/mybatis-的-和-是有啥区别/index.html @@ -4,7 +4,7 @@ - + @@ -26,12 +26,13 @@ var CONFIG = {"hostname":"nicksxs.me","root":"/","scheme":"Pisces","version":"7.8.0","exturl":false,"sidebar":{"position":"left","display":"post","padding":18,"offset":12,"onmobile":false},"copycode":{"enable":true,"show_result":false,"style":null},"back2top":{"enable":true,"sidebar":false,"scrollpercent":false},"bookmark":{"enable":false,"color":"#222","save":"auto"},"fancybox":true,"mediumzoom":false,"lazyload":true,"pangu":false,"comments":{"style":"tabs","active":null,"storage":true,"lazyload":false,"nav":null},"algolia":{"hits":{"per_page":10},"labels":{"input_placeholder":"Search for Posts","hits_empty":"We didn't find any results for the search: ${query}","hits_stats":"${hits} results found in ${time} ms"}},"localsearch":{"enable":false,"trigger":"auto","top_n_per_article":1,"unescape":false,"preload":false},"motion":{"enable":true,"async":false,"transition":{"post_block":"fadeIn","post_header":"slideDownIn","post_body":"slideDownIn","coll_header":"slideLeftIn","sidebar":"slideUpIn"}}}; - + - + + @@ -42,17 +43,12 @@ - + - - - - - - + @@ -243,9 +239,8 @@ Posted on - - + @@ -316,11 +311,82 @@
    -

    这个问题也是面试中常被问到的，就抽空来了解下这个，跳过一大段前面初始化的逻辑，
    对于一条select * from t1 where id = #{id}这样的 sql，在初始化扫描 mapper 的xml文件的时候会根据是否是 dynamic 来判断生成 DynamicSqlSource 还是 RawSqlSource，这里它是一条 RawSqlSource，
    在这里做了替换，将#{}替换成了?

    前面说的是否 dynamic 就是在这里进行判断

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    // org.apache.ibatis.scripting.xmltags.XMLScriptBuilder#parseScriptNode
    public SqlSource parseScriptNode() {
        MixedSqlNode rootSqlNode = parseDynamicTags(context);
        SqlSource sqlSource;
        if (isDynamic) {
          sqlSource = new DynamicSqlSource(configuration, rootSqlNode);
        } else {
          sqlSource = new RawSqlSource(configuration, rootSqlNode, parameterType);
        }
        return sqlSource;
      }
    // org.apache.ibatis.scripting.xmltags.XMLScriptBuilder#parseDynamicTags
    protected MixedSqlNode parseDynamicTags(XNode node) {
        List<SqlNode> contents = new ArrayList<>();
        NodeList children = node.getNode().getChildNodes();
        for (int i = 0; i < children.getLength(); i++) {
          XNode child = node.newXNode(children.item(i));
          if (child.getNode().getNodeType() == Node.CDATA_SECTION_NODE || child.getNode().getNodeType() == Node.TEXT_NODE) {
            String data = child.getStringBody("");
            TextSqlNode textSqlNode = new TextSqlNode(data);
            if (textSqlNode.isDynamic()) {
              contents.add(textSqlNode);
              isDynamic = true;
            } else {
              contents.add(new StaticTextSqlNode(data));
            }
          } else if (child.getNode().getNodeType() == Node.ELEMENT_NODE) { // issue #628
            String nodeName = child.getNode().getNodeName();
            NodeHandler handler = nodeHandlerMap.get(nodeName);
            if (handler == null) {
              throw new BuilderException("Unknown element <" + nodeName + "> in SQL statement.");
            }
            handler.handleNode(child, contents);
            isDynamic = true;
          }
        }
        return new MixedSqlNode(contents);
      }
    // org.apache.ibatis.scripting.xmltags.TextSqlNode#isDynamic
      public boolean isDynamic() {
        DynamicCheckerTokenParser checker = new DynamicCheckerTokenParser();
        GenericTokenParser parser = createParser(checker);
        parser.parse(text);
        return checker.isDynamic();
      }
        private GenericTokenParser createParser(TokenHandler handler) {
        return new GenericTokenParser("${", "}", handler);
      }
    -

    可以看到其中一个条件就是是否有${}这种占位符，假如说上面的 sql 换成 ${}，那么可以看到它会在这里创建一个 dynamicSqlSource,

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    // org.apache.ibatis.scripting.xmltags.DynamicSqlSource
    public class DynamicSqlSource implements SqlSource {

      private final Configuration configuration;
      private final SqlNode rootSqlNode;

      public DynamicSqlSource(Configuration configuration, SqlNode rootSqlNode) {
        this.configuration = configuration;
        this.rootSqlNode = rootSqlNode;
      }

      @Override
      public BoundSql getBoundSql(Object parameterObject) {
        DynamicContext context = new DynamicContext(configuration, parameterObject);
        rootSqlNode.apply(context);
        SqlSourceBuilder sqlSourceParser = new SqlSourceBuilder(configuration);
        Class<?> parameterType = parameterObject == null ? Object.class : parameterObject.getClass();
        SqlSource sqlSource = sqlSourceParser.parse(context.getSql(), parameterType, context.getBindings());
        BoundSql boundSql = sqlSource.getBoundSql(parameterObject);
        context.getBindings().forEach(boundSql::setAdditionalParameter);
        return boundSql;
      }

    }
    -

    这里眼尖的同学可能就可以看出来了，RawSqlSource 在初始化的时候已经经过了 parse，把#{}替换成了?占位符，但是 DynamicSqlSource 并没有
    再看这个图，我们发现在这的时候还没有进行替换
    然后往里跟
    好像是这里了

    这里 rootSqlNode.apply 其实是一个对原来 sql 的解析结果的一个循环调用，不同类型的标签会构成不同的 node，像这里就是一个 textSqlNode

    可以发现到这我们的 sql 已经被替换了，而且是直接作为 string 类型替换的，所以可以明白了这个问题所在，就是注入，不过细心的同学发现其实这里是有个

    理论上还是可以做过滤的，不过好像现在没用起来。
    我们前面可以发现对于#{}是在启动扫描 mapper的 xml 文件就替换成了 ?,然后是在什么时候变成实际的值的呢

    发现到这的时候还是没有替换，其实说白了也就是 prepareStatement 那一套，

    在这里进行替换，会拿到 org.apache.ibatis.mapping.ParameterMapping，然后进行替换，因为会带着类型信息，所以不用担心注入咯

    +

    这个问题也是面试中常被问到的，就抽空来了解下这个，跳过一大段前面初始化的逻辑，
    对于一条select * from t1 where id = #{id}这样的 sql，在初始化扫描 mapper 的xml文件的时候会根据是否是 dynamic 来判断生成 DynamicSqlSource 还是 RawSqlSource，这里它是一条 RawSqlSource，
    在这里做了替换，将#{}替换成了?

    前面说的是否 dynamic 就是在这里进行判断

    +
    // org.apache.ibatis.scripting.xmltags.XMLScriptBuilder#parseScriptNode
+public SqlSource parseScriptNode() {
+    MixedSqlNode rootSqlNode = parseDynamicTags(context);
+    SqlSource sqlSource;
+    if (isDynamic) {
+      sqlSource = new DynamicSqlSource(configuration, rootSqlNode);
+    } else {
+      sqlSource = new RawSqlSource(configuration, rootSqlNode, parameterType);
+    }
+    return sqlSource;
+  }
+// org.apache.ibatis.scripting.xmltags.XMLScriptBuilder#parseDynamicTags
+protected MixedSqlNode parseDynamicTags(XNode node) {
+    List<SqlNode> contents = new ArrayList<>();
+    NodeList children = node.getNode().getChildNodes();
+    for (int i = 0; i < children.getLength(); i++) {
+      XNode child = node.newXNode(children.item(i));
+      if (child.getNode().getNodeType() == Node.CDATA_SECTION_NODE || child.getNode().getNodeType() == Node.TEXT_NODE) {
+        String data = child.getStringBody("");
+        TextSqlNode textSqlNode = new TextSqlNode(data);
+        if (textSqlNode.isDynamic()) {
+          contents.add(textSqlNode);
+          isDynamic = true;
+        } else {
+          contents.add(new StaticTextSqlNode(data));
+        }
+      } else if (child.getNode().getNodeType() == Node.ELEMENT_NODE) { // issue #628
+        String nodeName = child.getNode().getNodeName();
+        NodeHandler handler = nodeHandlerMap.get(nodeName);
+        if (handler == null) {
+          throw new BuilderException("Unknown element <" + nodeName + "> in SQL statement.");
+        }
+        handler.handleNode(child, contents);
+        isDynamic = true;
+      }
+    }
+    return new MixedSqlNode(contents);
+  }
+// org.apache.ibatis.scripting.xmltags.TextSqlNode#isDynamic
+  public boolean isDynamic() {
+    DynamicCheckerTokenParser checker = new DynamicCheckerTokenParser();
+    GenericTokenParser parser = createParser(checker);
+    parser.parse(text);
+    return checker.isDynamic();
+  }
+    private GenericTokenParser createParser(TokenHandler handler) {
+    return new GenericTokenParser("${", "}", handler);
+  }
    +

    可以看到其中一个条件就是是否有${}这种占位符，假如说上面的 sql 换成 ${}，那么可以看到它会在这里创建一个 dynamicSqlSource,

    +
    // org.apache.ibatis.scripting.xmltags.DynamicSqlSource
+public class DynamicSqlSource implements SqlSource {
+
+  private final Configuration configuration;
+  private final SqlNode rootSqlNode;
+
+  public DynamicSqlSource(Configuration configuration, SqlNode rootSqlNode) {
+    this.configuration = configuration;
+    this.rootSqlNode = rootSqlNode;
+  }
+
+  @Override
+  public BoundSql getBoundSql(Object parameterObject) {
+    DynamicContext context = new DynamicContext(configuration, parameterObject);
+    rootSqlNode.apply(context);
+    SqlSourceBuilder sqlSourceParser = new SqlSourceBuilder(configuration);
+    Class<?> parameterType = parameterObject == null ? Object.class : parameterObject.getClass();
+    SqlSource sqlSource = sqlSourceParser.parse(context.getSql(), parameterType, context.getBindings());
+    BoundSql boundSql = sqlSource.getBoundSql(parameterObject);
+    context.getBindings().forEach(boundSql::setAdditionalParameter);
+    return boundSql;
+  }
+
+}
+
    +

    这里眼尖的同学可能就可以看出来了，RawSqlSource 在初始化的时候已经经过了 parse，把#{}替换成了?占位符，但是 DynamicSqlSource 并没有
    再看这个图，我们发现在这的时候还没有进行替换
    然后往里跟
    好像是这里了

    这里 rootSqlNode.apply 其实是一个对原来 sql 的解析结果的一个循环调用，不同类型的标签会构成不同的 node，像这里就是一个 textSqlNode

    可以发现到这我们的 sql 已经被替换了，而且是直接作为 string 类型替换的，所以可以明白了这个问题所在，就是注入，不过细心的同学发现其实这里是有个

    理论上还是可以做过滤的，不过好像现在没用起来。
    我们前面可以发现对于#{}是在启动扫描 mapper的 xml 文件就替换成了 ?,然后是在什么时候变成实际的值的呢

    发现到这的时候还是没有替换，其实说白了也就是 prepareStatement 那一套，

    在这里进行替换，会拿到 org.apache.ibatis.mapping.ParameterMapping，然后进行替换，因为会带着类型信息，所以不用担心注入咯

    @@ -334,7 +400,7 @@
    mybatis 的缓存是怎么回事
  • -
    聊聊我刚学会的应用诊断方法
    +
    聊聊 Dubbo 的 SPI 续之自适应拓展
  • G1收集器概述
    @@ -343,7 +409,7 @@
    Maven实用小技巧
  • -
    聊聊 Dubbo 的 SPI 续之自适应拓展
    +
    Apollo 的 value 注解是怎么自动更新的
    • diff --git a/2020/09/13/在老丈人家的小工记三/index.html b/2020/09/13/在老丈人家的小工记三/index.html index edecbcff4f..3a5d51d22f 100644 --- a/2020/09/13/在老丈人家的小工记三/index.html +++ b/2020/09/13/在老丈人家的小工记三/index.html @@ -4,7 +4,7 @@ - + @@ -32,14 +32,16 @@ + - + + @@ -229,9 +231,8 @@     Posted on - - +     @@ -447,7 +448,7 @@
    -
    1. 1. 小工记三
    +
    1. 1. 小工记三
    diff --git a/2020/09/20/Leetcode-3-Longest-Substring-Without-Repeating-Characters-题解分析/index.html b/2020/09/20/Leetcode-3-Longest-Substring-Without-Repeating-Characters-题解分析/index.html index 323bc3e35d..1ff36e8199 100644 --- a/2020/09/20/Leetcode-3-Longest-Substring-Without-Repeating-Characters-题解分析/index.html +++ b/2020/09/20/Leetcode-3-Longest-Substring-Without-Repeating-Characters-题解分析/index.html @@ -4,7 +4,7 @@ - + @@ -26,19 +26,20 @@ var CONFIG = {"hostname":"nicksxs.me","root":"/","scheme":"Pisces","version":"7.8.0","exturl":false,"sidebar":{"position":"left","display":"post","padding":18,"offset":12,"onmobile":false},"copycode":{"enable":true,"show_result":false,"style":null},"back2top":{"enable":true,"sidebar":false,"scrollpercent":false},"bookmark":{"enable":false,"color":"#222","save":"auto"},"fancybox":true,"mediumzoom":false,"lazyload":true,"pangu":false,"comments":{"style":"tabs","active":null,"storage":true,"lazyload":false,"nav":null},"algolia":{"hits":{"per_page":10},"labels":{"input_placeholder":"Search for Posts","hits_empty":"We didn't find any results for the search: ${query}","hits_stats":"${hits} results found in ${time} ms"}},"localsearch":{"enable":false,"trigger":"auto","top_n_per_article":1,"unescape":false,"preload":false},"motion":{"enable":true,"async":false,"transition":{"post_block":"fadeIn","post_header":"slideDownIn","post_body":"slideDownIn","coll_header":"slideLeftIn","sidebar":"slideUpIn"}}}; - + - + + - + - + + - @@ -228,9 +229,8 @@     Posted on - - +     @@ -246,11 +246,11 @@ , - + , - + , @@ -299,14 +299,54 @@

    又做了个题，看记录是以前用 C++写过的，现在捋一捋思路，用 Java 再写了一下，思路还是比较清晰的，但是边界细节处理得比较差

    简要介绍

    Given a string s, find the length of the longest substring without repeating characters.

    -

    样例

    Example 1:

    1
    2
    3
    Input: s = "abcabcbb"
    Output: 3
    Explanation: The answer is "abc", with the length of 3.
    - -

    Example 2:

    1
    2
    3
    Input: s = "bbbbb"
    Output: 1
    Explanation: The answer is "b", with the length of 1.
    -

    Example 3:

    1
    2
    3
    4
    Input: s = "pwwkew"
    Output: 3
    Explanation: The answer is "wke", with the length of 3.
    Notice that the answer must be a substring, "pwke" is a subsequence and not a substring.
    -

    Example 4:

    1
    2
    Input: s = ""
    Output: 0
    +

    样例

    Example 1:

    Input: s = "abcabcbb"
+Output: 3
+Explanation: The answer is "abc", with the length of 3.
    + +

    Example 2:

    Input: s = "bbbbb"
+Output: 1
+Explanation: The answer is "b", with the length of 1.
    +

    Example 3:

    Input: s = "pwwkew"
+Output: 3
+Explanation: The answer is "wke", with the length of 3.
+Notice that the answer must be a substring, "pwke" is a subsequence and not a substring.
    +

    Example 4:

    Input: s = ""
+Output: 0

    就是一个最长不重复的字符串长度，因为也是中等难度的题，不太需要特别复杂的思考，最基本的就是O(N*N)两重循环，不过显然不太好，万一超时间，还有一种就是线性复杂度的了，这个就是需要搞定一个思路，比如字符串时 abcdefgaqwrty，比如遍历到第二个a的时候其实不用再从头去遍历了，只要把前面那个a给排除掉，继续往下算就好了

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    class Solution {
        Map<String, Integer> counter = new HashMap<>();
        public int lengthOfLongestSubstring(String s) {
            int length = s.length();
            // 当前的长度
            int subStringLength = 0;
            // 最长的长度
            int maxSubStringLength = 0;
            // 考虑到重复的位置已经被跳过的情况，即已经在当前长度的字符串范围之前的重复字符不需要回溯
            int lastDuplicatePos = -1;
            for (int i = 0; i < length; i++) {
                // 使用 map 存储字符和上一次出现的位置，如果存在并且大于上一次重复位置
                if (counter.get(String.valueOf(s.charAt(i))) != null && counter.get(String.valueOf(s.charAt(i))) > lastDuplicatePos) {
                    // 记录重复位置
                    lastDuplicatePos = counter.get(String.valueOf(s.charAt(i)));
                    // 重置不重复子串的长度，减去重复起点
                    subStringLength = i - counter.get(String.valueOf(s.charAt(i))) - 1;
                    // 替换当前位置
                    counter.replace(String.valueOf(s.charAt(i)), i);
                } else {
                    // 如果不存在就直接 put
                    counter.put(String.valueOf(s.charAt(i)), i);
                }
                // 长度累加
                subStringLength++;
                if (subStringLength > maxSubStringLength) {
                    // 简单替换
                    maxSubStringLength = subStringLength;
                }
            }
            return maxSubStringLength;
        }
    }
    +
    class Solution {
+    Map<String, Integer> counter = new HashMap<>();
+    public int lengthOfLongestSubstring(String s) {
+        int length = s.length();
+        // 当前的长度
+        int subStringLength = 0;
+        // 最长的长度
+        int maxSubStringLength = 0;
+        // 考虑到重复的位置已经被跳过的情况，即已经在当前长度的字符串范围之前的重复字符不需要回溯
+        int lastDuplicatePos = -1;
+        for (int i = 0; i < length; i++) {
+            // 使用 map 存储字符和上一次出现的位置，如果存在并且大于上一次重复位置
+            if (counter.get(String.valueOf(s.charAt(i))) != null && counter.get(String.valueOf(s.charAt(i))) > lastDuplicatePos) {
+                // 记录重复位置
+                lastDuplicatePos = counter.get(String.valueOf(s.charAt(i)));
+                // 重置不重复子串的长度，减去重复起点
+                subStringLength = i - counter.get(String.valueOf(s.charAt(i))) - 1;
+                // 替换当前位置
+                counter.replace(String.valueOf(s.charAt(i)), i);
+            } else {
+                // 如果不存在就直接 put
+                counter.put(String.valueOf(s.charAt(i)), i);
+            }
+            // 长度累加
+            subStringLength++;
+            if (subStringLength > maxSubStringLength) {
+                // 简单替换
+                maxSubStringLength = subStringLength;
+            }
+        }
+        return maxSubStringLength;
+    }
+}

    注释应该写的比较清楚了。

    @@ -318,19 +358,19 @@
    Related Posts
    @@ -458,7 +498,7 @@
    -
    1. 1. 简要介绍
    2. 2. 样例
      1. 2.0.1. Example 1:
      2. 2.0.2. Example 2:
      3. 2.0.3. Example 3:
      4. 2.0.4. Example 4:
    +
    1. 1. 简要介绍
    2. 2. 样例
      1. 2.0.1. Example 1:
      2. 2.0.2. Example 2:
      3. 2.0.3. Example 3:
      4. 2.0.4. Example 4:
    diff --git a/2020/09/26/在老丈人家的小工记四/index.html b/2020/09/26/在老丈人家的小工记四/index.html index 27399be32f..9bdf49ae5b 100644 --- a/2020/09/26/在老丈人家的小工记四/index.html +++ b/2020/09/26/在老丈人家的小工记四/index.html @@ -4,7 +4,7 @@ - + @@ -32,6 +32,7 @@ + @@ -40,6 +41,7 @@ + @@ -446,7 +448,7 @@
    -
    1. 1. 小工记四
    +
    1. 1. 小工记四
    diff --git a/2020/10/03/mybatis-的缓存是怎么回事/index.html b/2020/10/03/mybatis-的缓存是怎么回事/index.html index 20527b77d6..55b3bd277a 100644 --- a/2020/10/03/mybatis-的缓存是怎么回事/index.html +++ b/2020/10/03/mybatis-的缓存是怎么回事/index.html @@ -4,7 +4,7 @@ - + @@ -32,15 +32,14 @@ + - - - + @@ -247,19 +246,19 @@     , - + , - + , - + , - +     @@ -304,31 +303,230 @@

    Java 真的是任何一个中间件，比较常用的那种，都有很多内容值得深挖，比如这个缓存，慢慢有过一些感悟，比如如何提升性能，缓存无疑是一大重要手段，最底层开始 CPU 就有缓存，而且又小又贵，再往上一点内存一般作为硬盘存储在运行时的存储，一般在代码里也会用内存作为一些本地缓存，譬如数据库，像 mysql 这种也是有innodb_buffer_pool来提升查询效率，本质上理解就是用更快的存储作为相对慢存储的缓存，减少查询直接访问较慢的存储，并且这个都是相对的，比起 cpu 的缓存，那内存也是渣，但是与普通机械硬盘相比，那也是两个次元的水平。

    闲扯这么多来说说 mybatis 的缓存，mybatis 一般作为一个轻量级的 orm 使用，相对应的就是比较重量级的 hibernate，不过不在这次讨论范围，上一次是主要讲了 mybatis 在解析 sql 过程中，对于两种占位符的不同替换实现策略，这次主要聊下 mybatis 的缓存，前面其实得了解下前置的东西，比如 sqlsession，先当做我们知道 sqlsession 是个什么玩意，可能或多或少的知道 mybatis 是有两级缓存，

    -

    一级缓存

    第一级的缓存是在 BaseExecutor 中的 PerpetualCache，它是个最基本的缓存实现类，使用了 HashMap 实现缓存功能，代码其实没几十行

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    public class PerpetualCache implements Cache {

      private final String id;

      private final Map<Object, Object> cache = new HashMap<>();

      public PerpetualCache(String id) {
        this.id = id;
      }

      @Override
      public String getId() {
        return id;
      }

      @Override
      public int getSize() {
        return cache.size();
      }

      @Override
      public void putObject(Object key, Object value) {
        cache.put(key, value);
      }

      @Override
      public Object getObject(Object key) {
        return cache.get(key);
      }

      @Override
      public Object removeObject(Object key) {
        return cache.remove(key);
      }

      @Override
      public void clear() {
        cache.clear();
      }

      @Override
      public boolean equals(Object o) {
        if (getId() == null) {
          throw new CacheException("Cache instances require an ID.");
        }
        if (this == o) {
          return true;
        }
        if (!(o instanceof Cache)) {
          return false;
        }

        Cache otherCache = (Cache) o;
        return getId().equals(otherCache.getId());
      }

      @Override
      public int hashCode() {
        if (getId() == null) {
          throw new CacheException("Cache instances require an ID.");
        }
        return getId().hashCode();
      }

    }
    +

    一级缓存

    第一级的缓存是在 BaseExecutor 中的 PerpetualCache，它是个最基本的缓存实现类，使用了 HashMap 实现缓存功能，代码其实没几十行

    +
    public class PerpetualCache implements Cache {
+
+  private final String id;
+
+  private final Map<Object, Object> cache = new HashMap<>();
+
+  public PerpetualCache(String id) {
+    this.id = id;
+  }
+
+  @Override
+  public String getId() {
+    return id;
+  }
+
+  @Override
+  public int getSize() {
+    return cache.size();
+  }
+
+  @Override
+  public void putObject(Object key, Object value) {
+    cache.put(key, value);
+  }
+
+  @Override
+  public Object getObject(Object key) {
+    return cache.get(key);
+  }
+
+  @Override
+  public Object removeObject(Object key) {
+    return cache.remove(key);
+  }
+
+  @Override
+  public void clear() {
+    cache.clear();
+  }
+
+  @Override
+  public boolean equals(Object o) {
+    if (getId() == null) {
+      throw new CacheException("Cache instances require an ID.");
+    }
+    if (this == o) {
+      return true;
+    }
+    if (!(o instanceof Cache)) {
+      return false;
+    }
+
+    Cache otherCache = (Cache) o;
+    return getId().equals(otherCache.getId());
+  }
+
+  @Override
+  public int hashCode() {
+    if (getId() == null) {
+      throw new CacheException("Cache instances require an ID.");
+    }
+    return getId().hashCode();
+  }
+
+}

    可以看一下BaseExecutor 的构造函数

    -
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    protected BaseExecutor(Configuration configuration, Transaction transaction) {
        this.transaction = transaction;
        this.deferredLoads = new ConcurrentLinkedQueue<>();
        this.localCache = new PerpetualCache("LocalCache");
        this.localOutputParameterCache = new PerpetualCache("LocalOutputParameterCache");
        this.closed = false;
        this.configuration = configuration;
        this.wrapper = this;
      }
    +
    protected BaseExecutor(Configuration configuration, Transaction transaction) {
+    this.transaction = transaction;
+    this.deferredLoads = new ConcurrentLinkedQueue<>();
+    this.localCache = new PerpetualCache("LocalCache");
+    this.localOutputParameterCache = new PerpetualCache("LocalOutputParameterCache");
+    this.closed = false;
+    this.configuration = configuration;
+    this.wrapper = this;
+  }

    就是把 PerpetualCache 作为 localCache，然后怎么使用我看简单看一下，BaseExecutor 的查询首先是调用这个函数

    -
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    @Override
      public <E> List<E> query(MappedStatement ms, Object parameter, RowBounds rowBounds, ResultHandler resultHandler) throws SQLException {
        BoundSql boundSql = ms.getBoundSql(parameter);
        CacheKey key = createCacheKey(ms, parameter, rowBounds, boundSql);
        return query(ms, parameter, rowBounds, resultHandler, key, boundSql);
      }
    -

    可以看到首先是调用了 createCacheKey 方法，这个方法呢，先不看怎么写的，如果我们自己要实现这么个缓存，首先这个缓存 key 的设计也是个问题，如果是以表名加主键作为 key，那么分页查询，或者没有主键的时候就不行，来看看 mybatis 是怎么设计的

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    @Override
      public CacheKey createCacheKey(MappedStatement ms, Object parameterObject, RowBounds rowBounds, BoundSql boundSql) {
        if (closed) {
          throw new ExecutorException("Executor was closed.");
        }
        CacheKey cacheKey = new CacheKey();
        cacheKey.update(ms.getId());
        cacheKey.update(rowBounds.getOffset());
        cacheKey.update(rowBounds.getLimit());
        cacheKey.update(boundSql.getSql());
        List<ParameterMapping> parameterMappings = boundSql.getParameterMappings();
        TypeHandlerRegistry typeHandlerRegistry = ms.getConfiguration().getTypeHandlerRegistry();
        // mimic DefaultParameterHandler logic
        for (ParameterMapping parameterMapping : parameterMappings) {
          if (parameterMapping.getMode() != ParameterMode.OUT) {
            Object value;
            String propertyName = parameterMapping.getProperty();
            if (boundSql.hasAdditionalParameter(propertyName)) {
              value = boundSql.getAdditionalParameter(propertyName);
            } else if (parameterObject == null) {
              value = null;
            } else if (typeHandlerRegistry.hasTypeHandler(parameterObject.getClass())) {
              value = parameterObject;
            } else {
              MetaObject metaObject = configuration.newMetaObject(parameterObject);
              value = metaObject.getValue(propertyName);
            }
            cacheKey.update(value);
          }
        }
        if (configuration.getEnvironment() != null) {
          // issue #176
          cacheKey.update(configuration.getEnvironment().getId());
        }
        return cacheKey;
      }
    +
    @Override
+  public <E> List<E> query(MappedStatement ms, Object parameter, RowBounds rowBounds, ResultHandler resultHandler) throws SQLException {
+    BoundSql boundSql = ms.getBoundSql(parameter);
+    CacheKey key = createCacheKey(ms, parameter, rowBounds, boundSql);
+    return query(ms, parameter, rowBounds, resultHandler, key, boundSql);
+  }
    +

    可以看到首先是调用了 createCacheKey 方法，这个方法呢，先不看怎么写的，如果我们自己要实现这么个缓存，首先这个缓存 key 的设计也是个问题，如果是以表名加主键作为 key，那么分页查询，或者没有主键的时候就不行，来看看 mybatis 是怎么设计的

    +
    @Override
+  public CacheKey createCacheKey(MappedStatement ms, Object parameterObject, RowBounds rowBounds, BoundSql boundSql) {
+    if (closed) {
+      throw new ExecutorException("Executor was closed.");
+    }
+    CacheKey cacheKey = new CacheKey();
+    cacheKey.update(ms.getId());
+    cacheKey.update(rowBounds.getOffset());
+    cacheKey.update(rowBounds.getLimit());
+    cacheKey.update(boundSql.getSql());
+    List<ParameterMapping> parameterMappings = boundSql.getParameterMappings();
+    TypeHandlerRegistry typeHandlerRegistry = ms.getConfiguration().getTypeHandlerRegistry();
+    // mimic DefaultParameterHandler logic
+    for (ParameterMapping parameterMapping : parameterMappings) {
+      if (parameterMapping.getMode() != ParameterMode.OUT) {
+        Object value;
+        String propertyName = parameterMapping.getProperty();
+        if (boundSql.hasAdditionalParameter(propertyName)) {
+          value = boundSql.getAdditionalParameter(propertyName);
+        } else if (parameterObject == null) {
+          value = null;
+        } else if (typeHandlerRegistry.hasTypeHandler(parameterObject.getClass())) {
+          value = parameterObject;
+        } else {
+          MetaObject metaObject = configuration.newMetaObject(parameterObject);
+          value = metaObject.getValue(propertyName);
+        }
+        cacheKey.update(value);
+      }
+    }
+    if (configuration.getEnvironment() != null) {
+      // issue #176
+      cacheKey.update(configuration.getEnvironment().getId());
+    }
+    return cacheKey;
+  }
+

    首先需要 id，这个 id 是 mapper 里方法的 id， 然后是偏移量跟返回行数，再就是 sql，然后是参数，基本上是会有影响的都加进去了，在这个 update 里面

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    public void update(Object object) {
        int baseHashCode = object == null ? 1 : ArrayUtil.hashCode(object);

        count++;
        checksum += baseHashCode;
        baseHashCode *= count;

        hashcode = multiplier * hashcode + baseHashCode;

        updateList.add(object);
      }
    +
    public void update(Object object) {
+    int baseHashCode = object == null ? 1 : ArrayUtil.hashCode(object);
+
+    count++;
+    checksum += baseHashCode;
+    baseHashCode *= count;
+
+    hashcode = multiplier * hashcode + baseHashCode;
+
+    updateList.add(object);
+  }

    其实是一个 hash 转换，具体不纠结，就是提高特异性，然后回来就是继续调用 query

    -
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    @Override
      public <E> List<E> query(MappedStatement ms, Object parameter, RowBounds rowBounds, ResultHandler resultHandler, CacheKey key, BoundSql boundSql) throws SQLException {
        ErrorContext.instance().resource(ms.getResource()).activity("executing a query").object(ms.getId());
        if (closed) {
          throw new ExecutorException("Executor was closed.");
        }
        if (queryStack == 0 && ms.isFlushCacheRequired()) {
          clearLocalCache();
        }
        List<E> list;
        try {
          queryStack++;
          list = resultHandler == null ? (List<E>) localCache.getObject(key) : null;
          if (list != null) {
            handleLocallyCachedOutputParameters(ms, key, parameter, boundSql);
          } else {
            list = queryFromDatabase(ms, parameter, rowBounds, resultHandler, key, boundSql);
          }
        } finally {
          queryStack--;
        }
        if (queryStack == 0) {
          for (DeferredLoad deferredLoad : deferredLoads) {
            deferredLoad.load();
          }
          // issue #601
          deferredLoads.clear();
          if (configuration.getLocalCacheScope() == LocalCacheScope.STATEMENT) {
            // issue #482
            clearLocalCache();
          }
        }
        return list;
      }
    +
    @Override
+  public <E> List<E> query(MappedStatement ms, Object parameter, RowBounds rowBounds, ResultHandler resultHandler, CacheKey key, BoundSql boundSql) throws SQLException {
+    ErrorContext.instance().resource(ms.getResource()).activity("executing a query").object(ms.getId());
+    if (closed) {
+      throw new ExecutorException("Executor was closed.");
+    }
+    if (queryStack == 0 && ms.isFlushCacheRequired()) {
+      clearLocalCache();
+    }
+    List<E> list;
+    try {
+      queryStack++;
+      list = resultHandler == null ? (List<E>) localCache.getObject(key) : null;
+      if (list != null) {
+        handleLocallyCachedOutputParameters(ms, key, parameter, boundSql);
+      } else {
+        list = queryFromDatabase(ms, parameter, rowBounds, resultHandler, key, boundSql);
+      }
+    } finally {
+      queryStack--;
+    }
+    if (queryStack == 0) {
+      for (DeferredLoad deferredLoad : deferredLoads) {
+        deferredLoad.load();
+      }
+      // issue #601
+      deferredLoads.clear();
+      if (configuration.getLocalCacheScope() == LocalCacheScope.STATEMENT) {
+        // issue #482
+        clearLocalCache();
+      }
+    }
+    return list;
+  }

    可以看到是先从 localCache 里取，取不到再 queryFromDatabase，其实比较简单，这是一级缓存，考虑到 sqlsession 跟 BaseExecutor 的关系，其实是随着 sqlsession 来保证这个缓存不会出现脏数据幻读的情况，当然事务相关的后面可能再单独聊。

    二级缓存

    其实这个一级二级顺序有点反过来，其实查询的是先走的二级缓存，当然二级的需要配置开启，默认不开，
    需要通过

    -
    1
    <setting name="cacheEnabled" value="true"/>
    +
    <setting name="cacheEnabled" value="true"/>

    来开启，然后我们的查询就会走到

    -
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    public class CachingExecutor implements Executor {

      private final Executor delegate;
      private final TransactionalCacheManager tcm = new TransactionalCacheManager();
    +
    public class CachingExecutor implements Executor {
+
+  private final Executor delegate;
+  private final TransactionalCacheManager tcm = new TransactionalCacheManager();

    这个 Executor 中，这里我放了类里面的元素，发现没有一个 Cache 类，这就是一个特点了，往下看查询过程

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    @Override
      public <E> List<E> query(MappedStatement ms, Object parameterObject, RowBounds rowBounds, ResultHandler resultHandler) throws SQLException {
        BoundSql boundSql = ms.getBoundSql(parameterObject);
        CacheKey key = createCacheKey(ms, parameterObject, rowBounds, boundSql);
        return query(ms, parameterObject, rowBounds, resultHandler, key, boundSql);
      }

      @Override
      public <E> List<E> query(MappedStatement ms, Object parameterObject, RowBounds rowBounds, ResultHandler resultHandler, CacheKey key, BoundSql boundSql)
          throws SQLException {
        Cache cache = ms.getCache();
        if (cache != null) {
          flushCacheIfRequired(ms);
          if (ms.isUseCache() && resultHandler == null) {
            ensureNoOutParams(ms, boundSql);
            @SuppressWarnings("unchecked")
            List<E> list = (List<E>) tcm.getObject(cache, key);
            if (list == null) {
              list = delegate.query(ms, parameterObject, rowBounds, resultHandler, key, boundSql);
              tcm.putObject(cache, key, list); // issue #578 and #116
            }
            return list;
          }
        }
        return delegate.query(ms, parameterObject, rowBounds, resultHandler, key, boundSql);
      }
    +
    @Override
+  public <E> List<E> query(MappedStatement ms, Object parameterObject, RowBounds rowBounds, ResultHandler resultHandler) throws SQLException {
+    BoundSql boundSql = ms.getBoundSql(parameterObject);
+    CacheKey key = createCacheKey(ms, parameterObject, rowBounds, boundSql);
+    return query(ms, parameterObject, rowBounds, resultHandler, key, boundSql);
+  }
+
+  @Override
+  public <E> List<E> query(MappedStatement ms, Object parameterObject, RowBounds rowBounds, ResultHandler resultHandler, CacheKey key, BoundSql boundSql)
+      throws SQLException {
+    Cache cache = ms.getCache();
+    if (cache != null) {
+      flushCacheIfRequired(ms);
+      if (ms.isUseCache() && resultHandler == null) {
+        ensureNoOutParams(ms, boundSql);
+        @SuppressWarnings("unchecked")
+        List<E> list = (List<E>) tcm.getObject(cache, key);
+        if (list == null) {
+          list = delegate.query(ms, parameterObject, rowBounds, resultHandler, key, boundSql);
+          tcm.putObject(cache, key, list); // issue #578 and #116
+        }
+        return list;
+      }
+    }
+    return delegate.query(ms, parameterObject, rowBounds, resultHandler, key, boundSql);
+  }

    看到没，其实缓存是从 tcm 这个成员变量里取，而这个是什么呢，事务性缓存(直译下)，因为这个其实是用 MappedStatement 里的 Cache 作为key 从 tcm 的 map 取出来的

    -
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    public class TransactionalCacheManager {

      private final Map<Cache, TransactionalCache> transactionalCaches = new HashMap<>();
    +
    public class TransactionalCacheManager {
+
+  private final Map<Cache, TransactionalCache> transactionalCaches = new HashMap<>();

    MappedStatement是被全局使用的，所以其实二级缓存是跟着 mapper 的 namespace 走的，可以被多个 CachingExecutor 获取到，就会出现线程安全问题，线程安全问题可以用SynchronizedCache来解决，就是加锁，但是对于事务中的脏读，使用了TransactionalCache来解决这个问题，

    -
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    public class TransactionalCache implements Cache {

      private static final Log log = LogFactory.getLog(TransactionalCache.class);

      private final Cache delegate;
      private boolean clearOnCommit;
      private final Map<Object, Object> entriesToAddOnCommit;
      private final Set<Object> entriesMissedInCache;
    +
    public class TransactionalCache implements Cache {
+
+  private static final Log log = LogFactory.getLog(TransactionalCache.class);
+
+  private final Cache delegate;
+  private boolean clearOnCommit;
+  private final Map<Object, Object> entriesToAddOnCommit;
+  private final Set<Object> entriesMissedInCache;

    在事务还没提交的时候，会把中间状态的数据放在 entriesToAddOnCommit 中，只有在提交后会放进共享缓存中，

    -
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    public void commit() {
        if (clearOnCommit) {
          delegate.clear();
        }
        flushPendingEntries();
        reset();
      }
    +
    public void commit() {
+    if (clearOnCommit) {
+      delegate.clear();
+    }
+    flushPendingEntries();
+    reset();
+  }
    @@ -341,7 +539,7 @@
    mybatis 的 $ 和 # 是有啥区别
  • -
    聊聊 Dubbo 的 SPI
    +
    聊聊 Dubbo 的 SPI 续之自适应拓展
  • G1收集器概述
    @@ -478,7 +676,7 @@
    -
    1. 1. 一级缓存
    2. 2. 二级缓存
    +
    1. 1. 一级缓存
    2. 2. 二级缓存
    diff --git a/2020/10/11/Leetcode-2-Add-Two-Numbers-题解分析/index.html b/2020/10/11/Leetcode-2-Add-Two-Numbers-题解分析/index.html index fd9e06d74d..e1a1677b8e 100644 --- a/2020/10/11/Leetcode-2-Add-Two-Numbers-题解分析/index.html +++ b/2020/10/11/Leetcode-2-Add-Two-Numbers-题解分析/index.html @@ -4,7 +4,7 @@ - + @@ -32,15 +32,14 @@ + - + - + + - - - @@ -230,9 +229,8 @@ Posted on - - + @@ -248,11 +246,11 @@ , - + , - + , @@ -302,13 +300,45 @@

    又 roll 到了一个以前做过的题，不过现在用 Java 也来写一下，是 easy 级别的，所以就简单说下

    简要介绍

    You are given two non-empty linked lists representing two non-negative integers. The digits are stored in reverse order, and each of their nodes contains a single digit. Add the two numbers and return the sum as a linked list.

    You may assume the two numbers do not contain any leading zero, except the number 0 itself.
    就是给了两个链表，用来表示两个非负的整数，在链表中倒序放着，每个节点包含一位的数字，把他们加起来以后也按照原来的链表结构输出

    -

    样例

    example 1

    1
    2
    3
    Input: l1 = [2,4,3], l2 = [5,6,4]
    Output: [7,0,8]
    Explanation: 342 + 465 = 807.
    - -

    example 2

    1
    2
    Input: l1 = [0], l2 = [0]
    Output: [0]
    - -

    example 3

    1
    2
    Input: l1 = [9,9,9,9,9,9,9], l2 = [9,9,9,9]
    Output: [8,9,9,9,0,0,0,1]
    - -

    题解

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    public ListNode addTwoNumbers(ListNode l1, ListNode l2) {
            ListNode root = new ListNode();
            if (l1 == null && l2 == null) {
                return root;
            }
            ListNode tail = root;
            int entered = 0;
            // 这个条件加了 entered，就是还有进位的数
            while (l1 != null || l2 != null || entered != 0) {
                int temp = entered;
                if (l1 != null) {
                    temp += l1.val;
                    l1 = l1.next;
                }
                if (l2 != null) {
                    temp += l2.val;
                    l2 = l2.next;
                }
                entered = (temp - temp % 10) / 10;
                tail.val = temp % 10;
                // 循环内部的控制是为了排除最后的空节点
                if (l1 != null || l2 != null || entered != 0) {
                    tail.next = new ListNode();
                    tail = tail.next;
                }
            }
    //        tail = null;
            return root;
        }
    +

    样例

    example 1

    Input: l1 = [2,4,3], l2 = [5,6,4]
+Output: [7,0,8]
+Explanation: 342 + 465 = 807.
    + +

    example 2

    Input: l1 = [0], l2 = [0]
+Output: [0]
    + +

    example 3

    Input: l1 = [9,9,9,9,9,9,9], l2 = [9,9,9,9]
+Output: [8,9,9,9,0,0,0,1]
    + +

    题解

    public ListNode addTwoNumbers(ListNode l1, ListNode l2) {
+        ListNode root = new ListNode();
+        if (l1 == null && l2 == null) {
+            return root;
+        }
+        ListNode tail = root;
+        int entered = 0;
+        // 这个条件加了 entered，就是还有进位的数
+        while (l1 != null || l2 != null || entered != 0) {
+            int temp = entered;
+            if (l1 != null) {
+                temp += l1.val;
+                l1 = l1.next;
+            }
+            if (l2 != null) {
+                temp += l2.val;
+                l2 = l2.next;
+            }
+            entered = (temp - temp % 10) / 10;
+            tail.val = temp % 10;
+            // 循环内部的控制是为了排除最后的空节点
+            if (l1 != null || l2 != null || entered != 0) {
+                tail.next = new ListNode();
+                tail = tail.next;
+            }
+        }
+//        tail = null;
+        return root;
+    }

    这里唯二需要注意的就是两个点，一个是循环条件需要包含进位值还存在的情况，还有一个是最后一个节点，如果是空的了，就不要在 new 一个出来了，写的比较挫

    @@ -320,19 +350,19 @@
    Related Posts
    @@ -460,7 +490,7 @@
    -
    1. 1. 简要介绍
    2. 2. 样例
      1. 2.0.1. example 1
      2. 2.0.2. example 2
      3. 2.0.3. example 3
  • 3. 题解
    • +
    1. 1. 简要介绍
    2. 2. 样例
      1. 2.0.1. example 1
      2. 2.0.2. example 2
      3. 2.0.3. example 3
  • 3. 题解
    • diff --git a/2020/10/18/在老丈人家的小工记五/index.html b/2020/10/18/在老丈人家的小工记五/index.html index 39969e334b..2666e87ad8 100644 --- a/2020/10/18/在老丈人家的小工记五/index.html +++ b/2020/10/18/在老丈人家的小工记五/index.html @@ -4,7 +4,7 @@ - + @@ -32,14 +32,16 @@ + - + + @@ -229,9 +231,8 @@     Posted on - - +     diff --git a/2020/10/25/Leetcode-104-二叉树的最大深度-Maximum-Depth-of-Binary-Tree-题解分析/index.html b/2020/10/25/Leetcode-104-二叉树的最大深度-Maximum-Depth-of-Binary-Tree-题解分析/index.html index 5506bb2dfb..dd9033e344 100644 --- a/2020/10/25/Leetcode-104-二叉树的最大深度-Maximum-Depth-of-Binary-Tree-题解分析/index.html +++ b/2020/10/25/Leetcode-104-二叉树的最大深度-Maximum-Depth-of-Binary-Tree-题解分析/index.html @@ -4,7 +4,7 @@ - + @@ -26,21 +26,22 @@ var CONFIG = {"hostname":"nicksxs.me","root":"/","scheme":"Pisces","version":"7.8.0","exturl":false,"sidebar":{"position":"left","display":"post","padding":18,"offset":12,"onmobile":false},"copycode":{"enable":true,"show_result":false,"style":null},"back2top":{"enable":true,"sidebar":false,"scrollpercent":false},"bookmark":{"enable":false,"color":"#222","save":"auto"},"fancybox":true,"mediumzoom":false,"lazyload":true,"pangu":false,"comments":{"style":"tabs","active":null,"storage":true,"lazyload":false,"nav":null},"algolia":{"hits":{"per_page":10},"labels":{"input_placeholder":"Search for Posts","hits_empty":"We didn't find any results for the search: ${query}","hits_stats":"${hits} results found in ${time} ms"}},"localsearch":{"enable":false,"trigger":"auto","top_n_per_article":1,"unescape":false,"preload":false},"motion":{"enable":true,"async":false,"transition":{"post_block":"fadeIn","post_header":"slideDownIn","post_body":"slideDownIn","coll_header":"slideLeftIn","sidebar":"slideUpIn"}}}; - + - + + - + - - - + + + @@ -304,11 +305,33 @@

    题目介绍

    给定一个二叉树，找出其最大深度。

    二叉树的深度为根节点到最远叶子节点的最长路径上的节点数。

    -

    说明: 叶子节点是指没有子节点的节点。

    +

    说明: 叶子节点是指没有子节点的节点。

    示例：
    给定二叉树 [3,9,20,null,null,15,7]，

    -
    1
    2
    3
    4
    5
      3
     / \
    9  20
      /  \
     15   7
    -

    返回它的最大深度 3 。

    -

    代码

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    // 主体是个递归的应用
    public int maxDepth(TreeNode root) {
        // 节点的退出条件之一
        if (root == null) {
            return 0;
        }
        int left = 0;
        int right = 0;
        // 存在左子树，就递归左子树
        if (root.left != null) {
            left = maxDepth(root.left);
        }
        // 存在右子树，就递归右子树
        if (root.right != null) {
            right = maxDepth(root.right);
        }
        // 前面返回后，左右取大者
        return Math.max(left + 1, right + 1);
    }
    +
      3
+ / \
+9  20
+  /  \
+ 15   7
    +

    返回它的最大深度 3 。

    +

    代码

    // 主体是个递归的应用
+public int maxDepth(TreeNode root) {
+    // 节点的退出条件之一
+    if (root == null) {
+        return 0;
+    }
+    int left = 0;
+    int right = 0;
+    // 存在左子树，就递归左子树
+    if (root.left != null) {
+        left = maxDepth(root.left);
+    }
+    // 存在右子树，就递归右子树
+    if (root.right != null) {
+        right = maxDepth(root.right);
+    }
+    // 前面返回后，左右取大者
+    return Math.max(left + 1, right + 1);
+}

    分析

    其实对于树这类题，一般是以递归形式比较方便，只是要注意退出条件

    @@ -320,19 +343,19 @@
    Related Posts
    @@ -462,7 +485,7 @@
    -
    1. 1. 题目介绍
    2. 2. 代码
    3. 3. 分析
    +
    1. 1. 题目介绍
    2. 2. 代码
    3. 3. 分析
    diff --git a/2020/11/01/Apollo-的-value-注解是怎么自动更新的/index.html b/2020/11/01/Apollo-的-value-注解是怎么自动更新的/index.html index 2908ed1c01..7eb799fbcb 100644 --- a/2020/11/01/Apollo-的-value-注解是怎么自动更新的/index.html +++ b/2020/11/01/Apollo-的-value-注解是怎么自动更新的/index.html @@ -4,7 +4,7 @@ - + @@ -32,8 +32,9 @@ + - + @@ -229,9 +230,8 @@     Posted on - - +     @@ -291,11 +291,74 @@

    在前司和目前公司，用的配置中心都是使用的 Apollo，经过了业界验证，比较强大的配置管理系统，特别是在0.10 后开始支持对使用 value 注解的配置值进行自动更新，今天刚好有个同学问到我，就顺便写篇文章记录下，其实也是借助于 spring 强大的 bean 生命周期管理，可以实现BeanPostProcessor接口，使用postProcessBeforeInitialization方法，来对bean 内部的属性和方法进行判断，是否有 value 注解，如果有就是将它注册到一个 map 中，可以看到这个方法com.ctrip.framework.apollo.spring.annotation.SpringValueProcessor#processField

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    @Override
      protected void processField(Object bean, String beanName, Field field) {
        // register @Value on field
        Value value = field.getAnnotation(Value.class);
        if (value == null) {
          return;
        }
        Set<String> keys = placeholderHelper.extractPlaceholderKeys(value.value());

        if (keys.isEmpty()) {
          return;
        }

        for (String key : keys) {
          SpringValue springValue = new SpringValue(key, value.value(), bean, beanName, field, false);
          springValueRegistry.register(beanFactory, key, springValue);
          logger.debug("Monitoring {}", springValue);
        }
      }
    +
    @Override
+  protected void processField(Object bean, String beanName, Field field) {
+    // register @Value on field
+    Value value = field.getAnnotation(Value.class);
+    if (value == null) {
+      return;
+    }
+    Set<String> keys = placeholderHelper.extractPlaceholderKeys(value.value());
+
+    if (keys.isEmpty()) {
+      return;
+    }
+
+    for (String key : keys) {
+      SpringValue springValue = new SpringValue(key, value.value(), bean, beanName, field, false);
+      springValueRegistry.register(beanFactory, key, springValue);
+      logger.debug("Monitoring {}", springValue);
+    }
+  }

    然后我们看下这个springValueRegistry是啥玩意

    -
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    public class SpringValueRegistry {
      private static final long CLEAN_INTERVAL_IN_SECONDS = 5;
      private final Map<BeanFactory, Multimap<String, SpringValue>> registry = Maps.newConcurrentMap();
      private final AtomicBoolean initialized = new AtomicBoolean(false);
      private final Object LOCK = new Object();

      public void register(BeanFactory beanFactory, String key, SpringValue springValue) {
        if (!registry.containsKey(beanFactory)) {
          synchronized (LOCK) {
            if (!registry.containsKey(beanFactory)) {
              registry.put(beanFactory, LinkedListMultimap.<String, SpringValue>create());
            }
          }
        }

        registry.get(beanFactory).put(key, springValue);

        // lazy initialize
        if (initialized.compareAndSet(false, true)) {
          initialize();
        }
      }
    +
    public class SpringValueRegistry {
+  private static final long CLEAN_INTERVAL_IN_SECONDS = 5;
+  private final Map<BeanFactory, Multimap<String, SpringValue>> registry = Maps.newConcurrentMap();
+  private final AtomicBoolean initialized = new AtomicBoolean(false);
+  private final Object LOCK = new Object();
+
+  public void register(BeanFactory beanFactory, String key, SpringValue springValue) {
+    if (!registry.containsKey(beanFactory)) {
+      synchronized (LOCK) {
+        if (!registry.containsKey(beanFactory)) {
+          registry.put(beanFactory, LinkedListMultimap.<String, SpringValue>create());
+        }
+      }
+    }
+
+    registry.get(beanFactory).put(key, springValue);
+
+    // lazy initialize
+    if (initialized.compareAndSet(false, true)) {
+      initialize();
+    }
+  }

    这类其实就是个 map 来存放 springvalue，然后有com.ctrip.framework.apollo.spring.property.AutoUpdateConfigChangeListener来监听更新操作，当有变更时

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    @Override
     public void onChange(ConfigChangeEvent changeEvent) {
       Set<String> keys = changeEvent.changedKeys();
       if (CollectionUtils.isEmpty(keys)) {
         return;
       }
       for (String key : keys) {
         // 1. check whether the changed key is relevant
         Collection<SpringValue> targetValues = springValueRegistry.get(beanFactory, key);
         if (targetValues == null || targetValues.isEmpty()) {
           continue;
         }

         // 2. check whether the value is really changed or not (since spring property sources have hierarchies)
         // 这里其实有一点比较绕，是因为 Apollo 里的 namespace 划分，会出现 key 相同，但是 namespace 不同的情况，所以会有个优先级存在，所以需要去校验 environment 里面的是否已经更新，如果未更新则表示不需要更新
         if (!shouldTriggerAutoUpdate(changeEvent, key)) {
           continue;
         }

         // 3. update the value
         for (SpringValue val : targetValues) {
           updateSpringValue(val);
         }
       }
     }
    +
    @Override
+ public void onChange(ConfigChangeEvent changeEvent) {
+   Set<String> keys = changeEvent.changedKeys();
+   if (CollectionUtils.isEmpty(keys)) {
+     return;
+   }
+   for (String key : keys) {
+     // 1. check whether the changed key is relevant
+     Collection<SpringValue> targetValues = springValueRegistry.get(beanFactory, key);
+     if (targetValues == null || targetValues.isEmpty()) {
+       continue;
+     }
+
+     // 2. check whether the value is really changed or not (since spring property sources have hierarchies)
+     // 这里其实有一点比较绕，是因为 Apollo 里的 namespace 划分，会出现 key 相同，但是 namespace 不同的情况，所以会有个优先级存在，所以需要去校验 environment 里面的是否已经更新，如果未更新则表示不需要更新
+     if (!shouldTriggerAutoUpdate(changeEvent, key)) {
+       continue;
+     }
+
+     // 3. update the value
+     for (SpringValue val : targetValues) {
+       updateSpringValue(val);
+     }
+   }
+ }

    其实原理很简单，就是得了解知道下

    @@ -307,7 +370,7 @@
    Related Posts
    diff --git a/2020/11/08/聊聊-Java-的类加载机制/index.html b/2020/11/08/聊聊-Java-的类加载机制/index.html index f62e1b2ac4..d629b181bb 100644 --- a/2020/11/08/聊聊-Java-的类加载机制/index.html +++ b/2020/11/08/聊聊-Java-的类加载机制/index.html @@ -4,7 +4,7 @@ - + @@ -32,17 +32,11 @@ + - + - - - - - - - - + @@ -232,9 +226,8 @@     Posted on - - +     @@ -313,7 +306,7 @@

  • 解析

    解析阶段是 Java 虚拟机将常量池内的符号引用替换为直接引用的过程

    • -

    以上验证、准备、解析 三个阶段又合称为链接阶段，链接阶段要做的是将加载到JVM中的二进制字节流的类数据信息合并到JVM的运行时状态中。

    +

    以上验证、准备、解析 三个阶段又合称为链接阶段，链接阶段要做的是将加载到JVM中的二进制字节流的类数据信息合并到JVM的运行时状态中。

    • 初始化

      类的初始化阶段是类加载过程的最后一个步骤，也是除了自定义类加载器之外将主动权交给了应用程序，其实就是执行类构造器()方法的过程，()并不是我们在 Java 代码中直接编写的方法，它是 Javac编译器的自动生成物，()方法是由编译器自动收集类中的所有类变量的复制动作和静态句块(static{}块)中的语句合并产生的，编译器收集的顺序是由语句在原文件中出现的顺序决定的，静态语句块中只能访问定义在静态语句块之前的变量，定义在它之后的变量，在前面的静态语句块可以复制，但是不能访问，同时还要保证父类的执行先于子类，然后保证多线程下的并发问题
    @@ -444,7 +437,7 @@
    -
    1. 1. 加载
    2. 2. 验证
    3. 3. 准备
    4. 4. 解析
    5. 5. 初始化
    +
    1. 1. 加载
    2. 2. 验证
    3. 3. 准备
    4. 4. 解析
    5. 5. 初始化
    diff --git a/2020/11/15/Leetcode-234-回文联表-Palindrome-Linked-List-题解分析/index.html b/2020/11/15/Leetcode-234-回文联表-Palindrome-Linked-List-题解分析/index.html index dbf994365d..80bc34ce0a 100644 --- a/2020/11/15/Leetcode-234-回文联表-Palindrome-Linked-List-题解分析/index.html +++ b/2020/11/15/Leetcode-234-回文联表-Palindrome-Linked-List-题解分析/index.html @@ -4,7 +4,7 @@ - + @@ -32,15 +32,14 @@ + - + - + + - - - @@ -233,13 +232,6 @@     - - - - - Edited on - - @@ -310,7 +302,40 @@

    例二 Example 2:

    Input: 1->2->2->1
    Output: true

    挑战下自己

    Follow up:
    Could you do it in O(n) time and O(1) space?

    简要分析

    首先这是个单向链表，如果是双向的就可以一个从头到尾，一个从尾到头，显然那样就没啥意思了，然后想过要不找到中点，然后用一个栈，把前一半塞进栈里，但是这种其实也比较麻烦，比如长度是奇偶数，然后如何找到中点，这倒是可以借助于双指针，还是比较麻烦，再想一想，回文链表，就跟最开始的一样，链表只有单向的，我用个栈不就可以逆向了么，先把链表整个塞进栈里，然后在一个个 pop 出来跟链表从头开始比较，全对上了就是回文了

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    /**
     * Definition for singly-linked list.
     * public class ListNode {
     *     int val;
     *     ListNode next;
     *     ListNode() {}
     *     ListNode(int val) { this.val = val; }
     *     ListNode(int val, ListNode next) { this.val = val; this.next = next; }
     * }
     */
    class Solution {
        public boolean isPalindrome(ListNode head) {
            if (head == null) {
                return true;
            }
            ListNode tail = head;
            LinkedList<Integer> stack = new LinkedList<>();
            // 这里就是一个循环，将所有元素依次压入栈
            while (tail != null) {
                stack.push(tail.val);
                tail = tail.next;
            }
            // 在逐个 pop 出来，其实这个出来的顺序就等于链表从尾到头遍历，同时跟链表从头到尾遍历进行逐对对比
            while (!stack.isEmpty()) {
                if (stack.peekFirst() == head.val) {
                    stack.pollFirst();
                    head = head.next;
                } else {
                    return false;
                }
            }
            return true;
        }
    }
    +
    /**
+ * Definition for singly-linked list.
+ * public class ListNode {
+ *     int val;
+ *     ListNode next;
+ *     ListNode() {}
+ *     ListNode(int val) { this.val = val; }
+ *     ListNode(int val, ListNode next) { this.val = val; this.next = next; }
+ * }
+ */
+class Solution {
+    public boolean isPalindrome(ListNode head) {
+        if (head == null) {
+            return true;
+        }
+        ListNode tail = head;
+        LinkedList<Integer> stack = new LinkedList<>();
+        // 这里就是一个循环，将所有元素依次压入栈
+        while (tail != null) {
+            stack.push(tail.val);
+            tail = tail.next;
+        }
+        // 在逐个 pop 出来，其实这个出来的顺序就等于链表从尾到头遍历，同时跟链表从头到尾遍历进行逐对对比
+        while (!stack.isEmpty()) {
+            if (stack.peekFirst() == head.val) {
+                stack.pollFirst();
+                head = head.next;
+            } else {
+                return false;
+            }
+        }
+        return true;
+    }
+}
    @@ -326,13 +351,13 @@
    Leetcode 104 二叉树的最大深度(Maximum Depth of Binary Tree) 题解分析
  • -
    Leetcode 124 二叉树中的最大路径和(Binary Tree Maximum Path Sum) 题解分析
    +
    Leetcode 105 从前序与中序遍历序列构造二叉树(Construct Binary Tree from Preorder and Inorder Traversal) 题解分析
  • -
    Leetcode 105 从前序与中序遍历序列构造二叉树(Construct Binary Tree from Preorder and Inorder Traversal) 题解分析
    +
    Leetcode 124 二叉树中的最大路径和(Binary Tree Maximum Path Sum) 题解分析
  • -
    Leetcode 2 Add Two Numbers 题解分析
    +
    Leetcode 155 最小栈(Min Stack) 题解分析
    • @@ -460,7 +485,7 @@
    -
    1. 1. 题目介绍
      1. 1.1. 例一 Example 1:
      2. 1.2. 例二 Example 2:
      3. 1.3. 挑战下自己
    2. 2. 简要分析
    +
    1. 1. 题目介绍
      1. 1.1. 例一 Example 1:
      2. 1.2. 例二 Example 2:
      3. 1.3. 挑战下自己
    2. 2. 简要分析
    diff --git a/2020/11/22/聊聊-Dubbo-的容错机制/index.html b/2020/11/22/聊聊-Dubbo-的容错机制/index.html index 8e8e166c21..8ffd889f95 100644 --- a/2020/11/22/聊聊-Dubbo-的容错机制/index.html +++ b/2020/11/22/聊聊-Dubbo-的容错机制/index.html @@ -4,7 +4,7 @@ - + @@ -32,13 +32,14 @@ + - + + - @@ -243,11 +244,11 @@     , - + , - + , @@ -305,11 +306,106 @@

    集群容错模式

    Failover Cluster

    失败自动切换，当出现失败，重试其它服务器 1。通常用于读操作，但重试会带来更长延迟。可通过 retries=”2” 来设置重试次数(不含第一次)。

    重试次数配置如下：

    <dubbo:service retries=”2” />
    这里重点看下 Failover Cluster集群模式的实现

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    public class FailoverCluster implements Cluster {

        public final static String NAME = "failover";

        public <T> Invoker<T> join(Directory<T> directory) throws RpcException {
            return new FailoverClusterInvoker<T>(directory);
        }

    }
    +
    public class FailoverCluster implements Cluster {
+
+    public final static String NAME = "failover";
+
+    public <T> Invoker<T> join(Directory<T> directory) throws RpcException {
+        return new FailoverClusterInvoker<T>(directory);
+    }
+
+}

    这个代码就非常简单，重点需要看FailoverClusterInvoker里的代码，FailoverClusterInvoker继承了AbstractClusterInvoker类，其中invoke 方法是在抽象类里实现的

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    @Override
    public Result invoke(final Invocation invocation) throws RpcException {
        checkWhetherDestroyed();
        // binding attachments into invocation.
        // 绑定 attachments 到 invocation 中.
        Map<String, Object> contextAttachments = RpcContext.getContext().getObjectAttachments();
        if (contextAttachments != null && contextAttachments.size() != 0) {
            ((RpcInvocation) invocation).addObjectAttachments(contextAttachments);
        }
        // 列举 Invoker
        List<Invoker<T>> invokers = list(invocation);
        // 加载 LoadBalance 负载均衡器
        LoadBalance loadbalance = initLoadBalance(invokers, invocation);
        RpcUtils.attachInvocationIdIfAsync(getUrl(), invocation);
        // 调用 实际的 doInvoke 进行后续操作
        return doInvoke(invocation, invokers, loadbalance);
    }
    // 这是个抽象方法，实际是由子类实现的
     protected abstract Result doInvoke(Invocation invocation, List<Invoker<T>> invokers,
                                           LoadBalance loadbalance) throws RpcException;
    +
    @Override
+public Result invoke(final Invocation invocation) throws RpcException {
+    checkWhetherDestroyed();
+    // binding attachments into invocation.
+    // 绑定 attachments 到 invocation 中.
+    Map<String, Object> contextAttachments = RpcContext.getContext().getObjectAttachments();
+    if (contextAttachments != null && contextAttachments.size() != 0) {
+        ((RpcInvocation) invocation).addObjectAttachments(contextAttachments);
+    }
+    // 列举 Invoker
+    List<Invoker<T>> invokers = list(invocation);
+    // 加载 LoadBalance 负载均衡器
+    LoadBalance loadbalance = initLoadBalance(invokers, invocation);
+    RpcUtils.attachInvocationIdIfAsync(getUrl(), invocation);
+    // 调用 实际的 doInvoke 进行后续操作
+    return doInvoke(invocation, invokers, loadbalance);
+}
+// 这是个抽象方法，实际是由子类实现的
+ protected abstract Result doInvoke(Invocation invocation, List<Invoker<T>> invokers,
+                                       LoadBalance loadbalance) throws RpcException;

    然后重点就是FailoverClusterInvoker中的doInvoke方法了，其实它里面也就这么一个方法

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    @Override
        @SuppressWarnings({"unchecked", "rawtypes"})
        public Result doInvoke(Invocation invocation, final List<Invoker<T>> invokers, LoadBalance loadbalance) throws RpcException {
            List<Invoker<T>> copyInvokers = invokers;
            checkInvokers(copyInvokers, invocation);
            String methodName = RpcUtils.getMethodName(invocation);
            // 获取重试次数，这里默认是 2 次，还有可以注意下后面的+1
            int len = getUrl().getMethodParameter(methodName, RETRIES_KEY, DEFAULT_RETRIES) + 1;
            if (len <= 0) {
                len = 1;
            }
            // retry loop.
            RpcException le = null; // last exception.
            List<Invoker<T>> invoked = new ArrayList<Invoker<T>>(copyInvokers.size()); // invoked invokers.
            Set<String> providers = new HashSet<String>(len);
            // 循环调用，失败重试
            for (int i = 0; i < len; i++) {
                //Reselect before retry to avoid a change of candidate `invokers`.
                //NOTE: if `invokers` changed, then `invoked` also lose accuracy.
                if (i > 0) {
                    checkWhetherDestroyed();
                    // 在进行重试前重新列举 Invoker，这样做的好处是，如果某个服务挂了，
                    // 通过调用 list 可得到最新可用的 Invoker 列表
                    copyInvokers = list(invocation);
                    // check again
                    // 对 copyinvokers 进行判空检查
                    checkInvokers(copyInvokers, invocation);
                }
                // 通过负载均衡来选择 invoker
                Invoker<T> invoker = select(loadbalance, invocation, copyInvokers, invoked);
                // 将其添加到 invoker 到 invoked 列表中
                invoked.add(invoker);
                // 设置上下文
                RpcContext.getContext().setInvokers((List) invoked);
                try {
                    // 正式调用
                    Result result = invoker.invoke(invocation);
                    if (le != null && logger.isWarnEnabled()) {
                        logger.warn("Although retry the method " + methodName
                                + " in the service " + getInterface().getName()
                                + " was successful by the provider " + invoker.getUrl().getAddress()
                                + ", but there have been failed providers " + providers
                                + " (" + providers.size() + "/" + copyInvokers.size()
                                + ") from the registry " + directory.getUrl().getAddress()
                                + " on the consumer " + NetUtils.getLocalHost()
                                + " using the dubbo version " + Version.getVersion() + ". Last error is: "
                                + le.getMessage(), le);
                    }
                    return result;
                } catch (RpcException e) {
                    if (e.isBiz()) { // biz exception.
                        throw e;
                    }
                    le = e;
                } catch (Throwable e) {
                    le = new RpcException(e.getMessage(), e);
                } finally {
                    providers.add(invoker.getUrl().getAddress());
                }
            }
            throw new RpcException(le.getCode(), "Failed to invoke the method "
                    + methodName + " in the service " + getInterface().getName()
                    + ". Tried " + len + " times of the providers " + providers
                    + " (" + providers.size() + "/" + copyInvokers.size()
                    + ") from the registry " + directory.getUrl().getAddress()
                    + " on the consumer " + NetUtils.getLocalHost() + " using the dubbo version "
                    + Version.getVersion() + ". Last error is: "
                    + le.getMessage(), le.getCause() != null ? le.getCause() : le);
        }
    +
    @Override
+    @SuppressWarnings({"unchecked", "rawtypes"})
+    public Result doInvoke(Invocation invocation, final List<Invoker<T>> invokers, LoadBalance loadbalance) throws RpcException {
+        List<Invoker<T>> copyInvokers = invokers;
+        checkInvokers(copyInvokers, invocation);
+        String methodName = RpcUtils.getMethodName(invocation);
+        // 获取重试次数，这里默认是 2 次，还有可以注意下后面的+1
+        int len = getUrl().getMethodParameter(methodName, RETRIES_KEY, DEFAULT_RETRIES) + 1;
+        if (len <= 0) {
+            len = 1;
+        }
+        // retry loop.
+        RpcException le = null; // last exception.
+        List<Invoker<T>> invoked = new ArrayList<Invoker<T>>(copyInvokers.size()); // invoked invokers.
+        Set<String> providers = new HashSet<String>(len);
+        // 循环调用，失败重试
+        for (int i = 0; i < len; i++) {
+            //Reselect before retry to avoid a change of candidate `invokers`.
+            //NOTE: if `invokers` changed, then `invoked` also lose accuracy.
+            if (i > 0) {
+                checkWhetherDestroyed();
+                // 在进行重试前重新列举 Invoker，这样做的好处是，如果某个服务挂了，
+                // 通过调用 list 可得到最新可用的 Invoker 列表
+                copyInvokers = list(invocation);
+                // check again
+                // 对 copyinvokers 进行判空检查
+                checkInvokers(copyInvokers, invocation);
+            }
+            // 通过负载均衡来选择 invoker
+            Invoker<T> invoker = select(loadbalance, invocation, copyInvokers, invoked);
+            // 将其添加到 invoker 到 invoked 列表中
+            invoked.add(invoker);
+            // 设置上下文
+            RpcContext.getContext().setInvokers((List) invoked);
+            try {
+                // 正式调用
+                Result result = invoker.invoke(invocation);
+                if (le != null && logger.isWarnEnabled()) {
+                    logger.warn("Although retry the method " + methodName
+                            + " in the service " + getInterface().getName()
+                            + " was successful by the provider " + invoker.getUrl().getAddress()
+                            + ", but there have been failed providers " + providers
+                            + " (" + providers.size() + "/" + copyInvokers.size()
+                            + ") from the registry " + directory.getUrl().getAddress()
+                            + " on the consumer " + NetUtils.getLocalHost()
+                            + " using the dubbo version " + Version.getVersion() + ". Last error is: "
+                            + le.getMessage(), le);
+                }
+                return result;
+            } catch (RpcException e) {
+                if (e.isBiz()) { // biz exception.
+                    throw e;
+                }
+                le = e;
+            } catch (Throwable e) {
+                le = new RpcException(e.getMessage(), e);
+            } finally {
+                providers.add(invoker.getUrl().getAddress());
+            }
+        }
+        throw new RpcException(le.getCode(), "Failed to invoke the method "
+                + methodName + " in the service " + getInterface().getName()
+                + ". Tried " + len + " times of the providers " + providers
+                + " (" + providers.size() + "/" + copyInvokers.size()
+                + ") from the registry " + directory.getUrl().getAddress()
+                + " on the consumer " + NetUtils.getLocalHost() + " using the dubbo version "
+                + Version.getVersion() + ". Last error is: "
+                + le.getMessage(), le.getCause() != null ? le.getCause() : le);
+    }

    Failfast Cluster

    快速失败，只发起一次调用，失败立即报错。通常用于非幂等性的写操作，比如新增记录。

    @@ -467,7 +563,7 @@
    -
    1. 1. 集群容错模式
      1. 1.1. Failover Cluster
      2. 1.2. Failfast Cluster
      3. 1.3. Failsafe Cluster
      4. 1.4. Failback Cluster
      5. 1.5. Forking Cluster
      6. 1.6. Broadcast Cluster
    +
    1. 1. 集群容错模式
      1. 1.1. Failover Cluster
      2. 1.2. Failfast Cluster
      3. 1.3. Failsafe Cluster
      4. 1.4. Failback Cluster
      5. 1.5. Forking Cluster
      6. 1.6. Broadcast Cluster
    diff --git a/2020/11/29/从清华美院学姐聊聊我们身边的恶人/index.html b/2020/11/29/从清华美院学姐聊聊我们身边的恶人/index.html index 4c11332c53..21f41458cd 100644 --- a/2020/11/29/从清华美院学姐聊聊我们身边的恶人/index.html +++ b/2020/11/29/从清华美院学姐聊聊我们身边的恶人/index.html @@ -4,7 +4,7 @@ - + @@ -32,10 +32,11 @@ + - + @@ -297,7 +298,7 @@
    -

    前几天清华美院学姐的热点火了，然后仔细看了下，其实是个学姐诬陷以为其貌不扬的男同学摸她屁股

    然后还在朋友圈发文想让他社死，我也是挺晚才知道这个词什么意思，然后后面我看到了这个图片，挺有意思的

    本来其实也没什么想聊这个的，是在 B 站看了个吐槽这个的，然后刚好晚上乘公交的时候又碰到了有点类似的问题
    故事描述下，我们从始发站做了公交，这辆公交司机上次碰到过一回，就是会比较关注乘客的佩戴情况，主要考虑到目前国内疫情，然后这次在差不多人都坐满的情况下，可能在提示了三次让车内乘客戴好口罩，但是他指的那个中年女性还是没有反应，司机就转头比较大声指着这个乘客（中年女性）让戴好口罩，然后这个乘客（中年女性）就大声的说“我口罩是滑下来了，你指着我干嘛，你态度这么差，要吃了我一样，我要投诉你”等等，然后可能跟她一块的一个中年女性也是这么帮腔指责司机，比较基本的理解，车子里这么多乘客，假如是处于这位乘客口罩滑下来了而不自知的情况下，司机在提示了三次以后回头指着她说，我想的是没什么问题的，但是这位却反而指责这位司机指着她，并且说是态度差，要吃了她，完全是不可理喻的，并且一直喋喋不休说她口罩滑掉了有什么错，要投诉这个司机，让他可以提前退休了，在其他乘客的劝说下司机准备继续开车时，又口吐芬芳“你个傻，你来打我呀”，真的是让我再次体会到了所谓的恶人先告状的又一完美呈现，后面还有个乘客还是表示要打死司机这个傻，让我有点不明所以，俗话说有人是得理不饶人，前提是得理，这种理亏不饶人真的是挺让人长见识的，试想下，司机在提示三次后，这位乘客还是没有把口罩戴好，如何在不指着这位乘客的情况下能准确的提示到她呢，并且觉得语气态度不好，司机要载着一车的人，因为你这一个乘客不戴好口罩而不能正常出发，有些着急应该很正常吧，可能是平时自己在家里耀武扬威的使唤别人习惯了吧，别人不敢这么大声跟她说话，其实想想这位中年女性应该年纪不会很大，还比较时髦的吧，像一些常见的中年杭州本地人可能是不会说傻*这个词的吧。
    杭州的公交可能是在二月份疫情还比较严重的时候是要求上车出示健康码，后面比较缓和以后只要求佩戴好口罩，但是在我们小绍兴，目前还是一律要求检验健康码和佩戴口罩，对于疫情中，并且目前阶段国内也时有报出小范围的疫情的情况下，司机尽职要求佩戴好口罩其实也是为了乘客着想，另一种情况如果司机不严格要求，万一车上有个感染者，这位中年女性被传染了，如果能找到这个司机的话，是不是想“打死”这个司机，竟然让感染者上了车，反正她自己是不可能有错的，上来就是对方态度差，要投诉，自己不戴好口罩啥都没错，我就想知道如果因为自己没戴好口罩被感染了，是不是也是司机的错，毕竟没有像仆人那样点头哈腰求着她戴好口罩。
    再说回来，整个车就她一个人没戴好口罩，并且还有个细节，其实这个乘客是上了车之后就没戴好了，本来上车的时候是戴好的，这种比较有可能是觉得上车的时候司机那看一眼就好了，如果好好戴着口罩，一点事情都没有，唉，纯粹是太气愤了，调理逻辑什么的就忽略吧

    +

    前几天清华美院学姐的热点火了，然后仔细看了下，其实是个学姐诬陷以为其貌不扬的男同学摸她屁股

    然后还在朋友圈发文想让他社死，我也是挺晚才知道这个词什么意思，然后后面我看到了这个图片，挺有意思的

    本来其实也没什么想聊这个的，是在 B 站看了个吐槽这个的，然后刚好晚上乘公交的时候又碰到了有点类似的问题
    故事描述下，我们从始发站做了公交，这辆公交司机上次碰到过一回，就是会比较关注乘客的佩戴情况，主要考虑到目前国内疫情，然后这次在差不多人都坐满的情况下，可能在提示了三次让车内乘客戴好口罩，但是他指的那个中年女性还是没有反应，司机就转头比较大声指着这个乘客（中年女性）让戴好口罩，然后这个乘客（中年女性）就大声的说“我口罩是滑下来了，你指着我干嘛，你态度这么差，要吃了我一样，我要投诉你”等等，然后可能跟她一块的一个中年女性也是这么帮腔指责司机，比较基本的理解，车子里这么多乘客，假如是处于这位乘客口罩滑下来了而不自知的情况下，司机在提示了三次以后回头指着她说，我想的是没什么问题的，但是这位却反而指责这位司机指着她，并且说是态度差，要吃了她，完全是不可理喻的，并且一直喋喋不休说她口罩滑掉了有什么错，要投诉这个司机，让他可以提前退休了，在其他乘客的劝说下司机准备继续开车时，又口吐芬芳“你个傻，你来打我呀”，真的是让我再次体会到了所谓的恶人先告状的又一完美呈现，后面还有个乘客还是表示要打死司机这个傻，让我有点不明所以，俗话说有人是得理不饶人，前提是得理，这种理亏不饶人真的是挺让人长见识的，试想下，司机在提示三次后，这位乘客还是没有把口罩戴好，如何在不指着这位乘客的情况下能准确的提示到她呢，并且觉得语气态度不好，司机要载着一车的人，因为你这一个乘客不戴好口罩而不能正常出发，有些着急应该很正常吧，可能是平时自己在家里耀武扬威的使唤别人习惯了吧，别人不敢这么大声跟她说话，其实想想这位中年女性应该年纪不会很大，还比较时髦的吧，像一些常见的中年杭州本地人可能是不会说傻*这个词的吧。
    杭州的公交可能是在二月份疫情还比较严重的时候是要求上车出示健康码，后面比较缓和以后只要求佩戴好口罩，但是在我们小绍兴，目前还是一律要求检验健康码和佩戴口罩，对于疫情中，并且目前阶段国内也时有报出小范围的疫情的情况下，司机尽职要求佩戴好口罩其实也是为了乘客着想，另一种情况如果司机不严格要求，万一车上有个感染者，这位中年女性被传染了，如果能找到这个司机的话，是不是想“打死”这个司机，竟然让感染者上了车，反正她自己是不可能有错的，上来就是对方态度差，要投诉，自己不戴好口罩啥都没错，我就想知道如果因为自己没戴好口罩被感染了，是不是也是司机的错，毕竟没有像仆人那样点头哈腰求着她戴好口罩。
    再说回来，整个车就她一个人没戴好口罩，并且还有个细节，其实这个乘客是上了车之后就没戴好了，本来上车的时候是戴好的，这种比较有可能是觉得上车的时候司机那看一眼就好了，如果好好戴着口罩，一点事情都没有，唉，纯粹是太气愤了，调理逻辑什么的就忽略吧

    @@ -311,16 +312,16 @@
    从丁仲礼被美国制裁聊点啥
  • -
    在老丈人家的小工记四
    +
    在老丈人家的小工记五
  • 2020 年终总结
  • -
    周末我在老丈人家打了天小工
    +
    2020年中总结
  • -
    在老丈人家的小工记三
    +
    关于公共交通再吐个槽
    • diff --git a/2020/12/06/Leetcode-155-最小栈-Min-Stack-题解分析/index.html b/2020/12/06/Leetcode-155-最小栈-Min-Stack-题解分析/index.html index 3f43749f09..5e3fb028ff 100644 --- a/2020/12/06/Leetcode-155-最小栈-Min-Stack-题解分析/index.html +++ b/2020/12/06/Leetcode-155-最小栈-Min-Stack-题解分析/index.html @@ -4,7 +4,7 @@ - + @@ -32,14 +32,15 @@ + - + - + + - - + @@ -248,11 +249,11 @@     , - + , - + , @@ -307,10 +308,63 @@
  • getMin() – Retrieve the minimum element in the stack.

    • 示例

    Example 1:

    -
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    Input
    ["MinStack","push","push","push","getMin","pop","top","getMin"]
    [[],[-2],[0],[-3],[],[],[],[]]

    Output
    [null,null,null,null,-3,null,0,-2]

    Explanation
    MinStack minStack = new MinStack();
    minStack.push(-2);
    minStack.push(0);
    minStack.push(-3);
    minStack.getMin(); // return -3
    minStack.pop();
    minStack.top();    // return 0
    minStack.getMin(); // return -2
    +
    Input
+["MinStack","push","push","push","getMin","pop","top","getMin"]
+[[],[-2],[0],[-3],[],[],[],[]]
+
+Output
+[null,null,null,null,-3,null,0,-2]
+
+Explanation
+MinStack minStack = new MinStack();
+minStack.push(-2);
+minStack.push(0);
+minStack.push(-3);
+minStack.getMin(); // return -3
+minStack.pop();
+minStack.top();    // return 0
+minStack.getMin(); // return -2

    简要分析

    其实现在大部分语言都自带类栈的数据结构，Java 也自带 stack 这个数据结构，所以这个题的主要难点的就是常数级的获取最小元素，最开始的想法是就一个栈外加一个记录最小值的变量就行了，但是仔细一想是不行的，因为随着元素被 pop 出去，这个最小值也可能需要梗着变化，就不太好判断了，所以后面是用了一个辅助栈。

    -

    代码

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    class MinStack {
            // 这个作为主栈
            Stack<Integer> s1 = new Stack<>();
            // 这个作为辅助栈，放最小值的栈
            Stack<Integer> s2 = new Stack<>();
            /** initialize your data structure here. */
            public MinStack() {

            }

            public void push(int x) {
                // 放入主栈
                s1.push(x);
                // 当 s2 是空或者当前值是小于"等于" s2 栈顶时，压入辅助最小值的栈
                // 注意这里的"等于"非常必要，因为当最小值有多个的情况下，也需要压入栈，否则在 pop 的时候就会不对等
                if (s2.isEmpty() || x <= s2.peek()) {
                    s2.push(x);
                }
            }

            public void pop() {
                // 首先就是主栈要 pop，然后就是第二个了，跟上面的"等于"很有关系，
                // 因为如果有两个最小值，如果前面等于的情况没有压栈，那这边相等的时候 pop 就会少一个了，可能就导致最小值不对了
                int x = s1.pop();
                if (x == s2.peek())  {
                    s2.pop();
                }
            }

            public int top() {
                // 栈顶的元素
                return s1.peek();
            }

            public int getMin() {
                // 辅助最小栈的栈顶
                return s2.peek();
            }
        }
    +

    代码

    class MinStack {
+        // 这个作为主栈
+        Stack<Integer> s1 = new Stack<>();
+        // 这个作为辅助栈，放最小值的栈
+        Stack<Integer> s2 = new Stack<>();
+        /** initialize your data structure here. */
+        public MinStack() {
+
+        }
+
+        public void push(int x) {
+            // 放入主栈
+            s1.push(x);
+            // 当 s2 是空或者当前值是小于"等于" s2 栈顶时，压入辅助最小值的栈
+            // 注意这里的"等于"非常必要，因为当最小值有多个的情况下，也需要压入栈，否则在 pop 的时候就会不对等
+            if (s2.isEmpty() || x <= s2.peek()) {
+                s2.push(x);
+            }
+        }
+
+        public void pop() {
+            // 首先就是主栈要 pop，然后就是第二个了，跟上面的"等于"很有关系，
+            // 因为如果有两个最小值，如果前面等于的情况没有压栈，那这边相等的时候 pop 就会少一个了，可能就导致最小值不对了
+            int x = s1.pop();
+            if (x == s2.peek())  {
+                s2.pop();
+            }
+        }
+
+        public int top() {
+            // 栈顶的元素
+            return s1.peek();
+        }
+
+        public int getMin() {
+            // 辅助最小栈的栈顶
+            return s2.peek();
+        }
+    }
    @@ -322,19 +376,19 @@
    Related Posts
    @@ -465,7 +519,7 @@
    -
    1. 1. 题目介绍
    2. 2. 示例
    3. 3. 简要分析
    4. 4. 代码
    +
    1. 1. 题目介绍
    2. 2. 示例
    3. 3. 简要分析
    4. 4. 代码
    diff --git a/2020/12/13/Leetcode-105-从前序与中序遍历序列构造二叉树-Construct-Binary-Tree-from-Preorder-and-Inorder-Traversal-题解分析/index.html b/2020/12/13/Leetcode-105-从前序与中序遍历序列构造二叉树-Construct-Binary-Tree-from-Preorder-and-Inorder-Traversal-题解分析/index.html index 1f17c97b63..bcbbf47a51 100644 --- a/2020/12/13/Leetcode-105-从前序与中序遍历序列构造二叉树-Construct-Binary-Tree-from-Preorder-and-Inorder-Traversal-题解分析/index.html +++ b/2020/12/13/Leetcode-105-从前序与中序遍历序列构造二叉树-Construct-Binary-Tree-from-Preorder-and-Inorder-Traversal-题解分析/index.html @@ -4,7 +4,7 @@ - + @@ -26,26 +26,26 @@ var CONFIG = {"hostname":"nicksxs.me","root":"/","scheme":"Pisces","version":"7.8.0","exturl":false,"sidebar":{"position":"left","display":"post","padding":18,"offset":12,"onmobile":false},"copycode":{"enable":true,"show_result":false,"style":null},"back2top":{"enable":true,"sidebar":false,"scrollpercent":false},"bookmark":{"enable":false,"color":"#222","save":"auto"},"fancybox":true,"mediumzoom":false,"lazyload":true,"pangu":false,"comments":{"style":"tabs","active":null,"storage":true,"lazyload":false,"nav":null},"algolia":{"hits":{"per_page":10},"labels":{"input_placeholder":"Search for Posts","hits_empty":"We didn't find any results for the search: ${query}","hits_stats":"${hits} results found in ${time} ms"}},"localsearch":{"enable":false,"trigger":"auto","top_n_per_article":1,"unescape":false,"preload":false},"motion":{"enable":true,"async":false,"transition":{"post_block":"fadeIn","post_header":"slideDownIn","post_body":"slideDownIn","coll_header":"slideLeftIn","sidebar":"slideUpIn"}}}; - + - + + - + - + - - - + + + - @@ -309,13 +309,47 @@

    题目介绍

    Given preorder and inorder traversal of a tree, construct the binary tree.
    给定一棵树的前序和中序遍历，构造出一棵二叉树

    注意

    You may assume that duplicates do not exist in the tree.
    你可以假设树中没有重复的元素。(PS: 不然就没法做了呀)

    -

    例子:

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    preorder = [3,9,20,15,7]
    inorder = [9,3,15,20,7]
    +

    例子:

    preorder = [3,9,20,15,7]
+inorder = [9,3,15,20,7]

    返回的二叉树

    -
    1
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      3
     / \
    9  20
      /  \
     15   7
    +
      3
+ / \
+9  20
+  /  \
+ 15   7

    简要分析

    看到这个题可以想到一个比较常规的解法就是递归拆树，前序就是根左右，中序就是左根右，然后就是通过前序已经确定的根在中序中找到，然后去划分左右子树，这个例子里是 3，找到中序中的位置，那么就可以确定，9 是左子树，15,20,7是右子树，然后对应的可以根据左右子树的元素数量在前序中划分左右子树，再继续递归就行

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    class Solution {
        public TreeNode buildTree(int[] preorder, int[] inorder) {
          // 获取下数组长度
            int n = preorder.length;
            // 排除一下异常和边界
            if (n != inorder.length) {
                return null;
            }
            if (n == 0) {
                return null;
            }
            if (n == 1) {
                return new TreeNode(preorder[0]);
            }
            // 获得根节点
            TreeNode node = new TreeNode(preorder[0]);
            int pos = 0;
            // 找到中序中的位置
            for (int i = 0; i < inorder.length; i++) {
                if (node.val == inorder[i]) {
                    pos = i;
                    break;
                }
            }
            // 划分左右再进行递归，注意下`Arrays.copyOfRange`的用法
            node.left = buildTree(Arrays.copyOfRange(preorder, 1, pos + 1), Arrays.copyOfRange(inorder, 0, pos));
            node.right = buildTree(Arrays.copyOfRange(preorder, pos + 1, n), Arrays.copyOfRange(inorder, pos + 1, n));
            return node;
        }
    }
    +
    class Solution {
+    public TreeNode buildTree(int[] preorder, int[] inorder) {
+      // 获取下数组长度
+        int n = preorder.length;
+        // 排除一下异常和边界
+        if (n != inorder.length) {
+            return null;
+        }
+        if (n == 0) {
+            return null;
+        }
+        if (n == 1) {
+            return new TreeNode(preorder[0]);
+        }
+        // 获得根节点
+        TreeNode node = new TreeNode(preorder[0]);
+        int pos = 0;
+        // 找到中序中的位置
+        for (int i = 0; i < inorder.length; i++) {
+            if (node.val == inorder[i]) {
+                pos = i;
+                break;
+            }
+        }
+        // 划分左右再进行递归，注意下`Arrays.copyOfRange`的用法
+        node.left = buildTree(Arrays.copyOfRange(preorder, 1, pos + 1), Arrays.copyOfRange(inorder, 0, pos));
+        node.right = buildTree(Arrays.copyOfRange(preorder, pos + 1, n), Arrays.copyOfRange(inorder, pos + 1, n));
+        return node;
+    }
+}
    @@ -334,10 +368,10 @@
    Leetcode 160 相交链表(intersection-of-two-linked-lists) 题解分析
  • -
    Leetcode 2 Add Two Numbers 题解分析
    +
    Leetcode 155 最小栈(Min Stack) 题解分析
  • -
    Leetcode 48 旋转图像(Rotate Image) 题解分析
    +
    Leetcode 121 买卖股票的最佳时机(Best Time to Buy and Sell Stock) 题解分析
    • @@ -471,7 +505,7 @@
    -
    1. 1. 题目介绍
      1. 1.1. 注意
      2. 1.2. 例子:
    2. 2. 简要分析
    +
    1. 1. 题目介绍
      1. 1.1. 注意
      2. 1.2. 例子:
    2. 2. 简要分析
    diff --git a/2020/12/20/从丁仲礼被美国制裁聊点啥/index.html b/2020/12/20/从丁仲礼被美国制裁聊点啥/index.html index c3cb25acf8..516459f9f0 100644 --- a/2020/12/20/从丁仲礼被美国制裁聊点啥/index.html +++ b/2020/12/20/从丁仲礼被美国制裁聊点啥/index.html @@ -4,7 +4,7 @@ - + @@ -32,8 +32,9 @@ + - + @@ -314,10 +315,10 @@
    2020 年终总结
  • -
    周末我在老丈人家打了天小工
    +
    关于公共交通再吐个槽
  • -
    2019年终总结
    +
    周末我在老丈人家打了天小工
    • diff --git a/2020/12/27/聊聊-mysql-索引的一些细节/index.html b/2020/12/27/聊聊-mysql-索引的一些细节/index.html index a42a455a3f..300493642f 100644 --- a/2020/12/27/聊聊-mysql-索引的一些细节/index.html +++ b/2020/12/27/聊聊-mysql-索引的一些细节/index.html @@ -4,7 +4,7 @@ - + @@ -26,21 +26,22 @@ var CONFIG = {"hostname":"nicksxs.me","root":"/","scheme":"Pisces","version":"7.8.0","exturl":false,"sidebar":{"position":"left","display":"post","padding":18,"offset":12,"onmobile":false},"copycode":{"enable":true,"show_result":false,"style":null},"back2top":{"enable":true,"sidebar":false,"scrollpercent":false},"bookmark":{"enable":false,"color":"#222","save":"auto"},"fancybox":true,"mediumzoom":false,"lazyload":true,"pangu":false,"comments":{"style":"tabs","active":null,"storage":true,"lazyload":false,"nav":null},"algolia":{"hits":{"per_page":10},"labels":{"input_placeholder":"Search for Posts","hits_empty":"We didn't find any results for the search: ${query}","hits_stats":"${hits} results found in ${time} ms"}},"localsearch":{"enable":false,"trigger":"auto","top_n_per_article":1,"unescape":false,"preload":false},"motion":{"enable":true,"async":false,"transition":{"post_block":"fadeIn","post_header":"slideDownIn","post_body":"slideDownIn","coll_header":"slideLeftIn","sidebar":"slideUpIn"}}}; - + - + + - + - + @@ -238,13 +239,6 @@     - - - - - Edited on - - @@ -307,19 +301,52 @@

    前几天同事问了我个 mysql 索引的问题，虽然大概知道，但是还是想来实践下，就是 is null，is not null 这类查询是否能用索引，可能之前有些网上的文章说都是不能用索引，但是其实不是，我们来看个小试验

    -
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    CREATE TABLE `null_index_t` (
      `id` int(10) unsigned NOT NULL AUTO_INCREMENT,
      `null_key` varchar(255) DEFAULT NULL,
      `null_key1` varchar(255) DEFAULT NULL,
      `null_key2` varchar(255) DEFAULT NULL,
      PRIMARY KEY (`id`),
      KEY `idx_1` (`null_key`) USING BTREE,
      KEY `idx_2` (`null_key1`) USING BTREE,
      KEY `idx_3` (`null_key2`) USING BTREE
    ) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;
    +
    CREATE TABLE `null_index_t` (
+  `id` int(10) unsigned NOT NULL AUTO_INCREMENT,
+  `null_key` varchar(255) DEFAULT NULL,
+  `null_key1` varchar(255) DEFAULT NULL,
+  `null_key2` varchar(255) DEFAULT NULL,
+  PRIMARY KEY (`id`),
+  KEY `idx_1` (`null_key`) USING BTREE,
+  KEY `idx_2` (`null_key1`) USING BTREE,
+  KEY `idx_3` (`null_key2`) USING BTREE
+) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;

    用个存储过程来插入数据

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    delimiter $	#以delimiter来标记用$表示存储过程结束
    create procedure nullIndex1()
    begin
    declare i int;	
    declare j int;	
    set i=1;
    set j=1;
    while(i<=100) do	
    	while(j<=100) do	
    		IF (i % 3 = 0) THEN
    	     INSERT INTO null_index_t ( `null_key`, `null_key1`, `null_key2` ) VALUES (null , LEFT(MD5(RAND()), 8), LEFT(MD5(RAND()), 8));
        ELSEIF (i % 3 = 1) THEN
    			 INSERT INTO null_index_t ( `null_key`, `null_key1`, `null_key2` ) VALUES (LEFT(MD5(RAND()), 8), NULL, LEFT(MD5(RAND()), 8));
    	  ELSE
    			 INSERT INTO null_index_t ( `null_key`, `null_key1`, `null_key2` ) VALUES (LEFT(MD5(RAND()), 8), LEFT(MD5(RAND()), 8), NULL);
        END IF;
    		set j=j+1;
    	end while;
    	set i=i+1;
    	set j=1;	
    end while;
    end 
    $
    call nullIndex1();
    +
    
+delimiter $	#以delimiter来标记用$表示存储过程结束
+create procedure nullIndex1()
+begin
+declare i int;	
+declare j int;	
+set i=1;
+set j=1;
+while(i<=100) do	
+	while(j<=100) do	
+		IF (i % 3 = 0) THEN
+	     INSERT INTO null_index_t ( `null_key`, `null_key1`, `null_key2` ) VALUES (null , LEFT(MD5(RAND()), 8), LEFT(MD5(RAND()), 8));
+    ELSEIF (i % 3 = 1) THEN
+			 INSERT INTO null_index_t ( `null_key`, `null_key1`, `null_key2` ) VALUES (LEFT(MD5(RAND()), 8), NULL, LEFT(MD5(RAND()), 8));
+	  ELSE
+			 INSERT INTO null_index_t ( `null_key`, `null_key1`, `null_key2` ) VALUES (LEFT(MD5(RAND()), 8), LEFT(MD5(RAND()), 8), NULL);
+    END IF;
+		set j=j+1;
+	end while;
+	set i=i+1;
+	set j=1;	
+end while;
+end 
+$
+call nullIndex1();

    然后看下我们的 is null 查询

    -
    1
    EXPLAIN select * from null_index_t WHERE null_key is null;
    -


    再来看看另一个

    -
    1
    EXPLAIN select * from null_index_t WHERE null_key is not null;
    -


    从这里能看出来啥呢，可以思考下

    -

    从上面可以发现，is null应该是用上了索引了，所以至少不是一刀切不能用，但是看着is not null好像不太行额
    我们在做一点小改动，把这个表里的数据改成 9100 条是 null，剩下 900 条是有值的，然后再执行下

    然后再来看看执行结果

    -
    1
    EXPLAIN select * from null_index_t WHERE null_key is null;
    -

    -
    1
    EXPLAIN select * from null_index_t WHERE null_key is not null;
    -


    是不是不一样了，这里再补充下我试验使用的 mysql 是 5.7 的，不保证在其他版本的一致性，
    其实可以看出随着数据量的变化，mysql 会不会使用索引是会变化的，不是说 is not null 一定会使用，也不是一定不会使用，而是优化器会根据查询成本做个预判，这个预判尽可能会减小查询成本，主要包括回表啥的，但是也不一定完全准确。

    +
    EXPLAIN select * from null_index_t WHERE null_key is null;
    +


    再来看看另一个

    +
    EXPLAIN select * from null_index_t WHERE null_key is not null;
    +


    从这里能看出来啥呢，可以思考下

    +

    从上面可以发现，is null应该是用上了索引了，所以至少不是一刀切不能用，但是看着is not null好像不太行额
    我们在做一点小改动，把这个表里的数据改成 9100 条是 null，剩下 900 条是有值的，然后再执行下

    然后再来看看执行结果

    +
    EXPLAIN select * from null_index_t WHERE null_key is null;
    +

    +
    EXPLAIN select * from null_index_t WHERE null_key is not null;
    +


    是不是不一样了，这里再补充下我试验使用的 mysql 是 5.7 的，不保证在其他版本的一致性，
    其实可以看出随着数据量的变化，mysql 会不会使用索引是会变化的，不是说 is not null 一定会使用，也不是一定不会使用，而是优化器会根据查询成本做个预判，这个预判尽可能会减小查询成本，主要包括回表啥的，但是也不一定完全准确。

    diff --git a/2021/01/03/聊聊-Java-的-equals-和-hashCode-方法/index.html b/2021/01/03/聊聊-Java-的-equals-和-hashCode-方法/index.html index 37d45dc06b..f54bda7304 100644 --- a/2021/01/03/聊聊-Java-的-equals-和-hashCode-方法/index.html +++ b/2021/01/03/聊聊-Java-的-equals-和-hashCode-方法/index.html @@ -4,7 +4,7 @@ - + @@ -26,20 +26,17 @@ var CONFIG = {"hostname":"nicksxs.me","root":"/","scheme":"Pisces","version":"7.8.0","exturl":false,"sidebar":{"position":"left","display":"post","padding":18,"offset":12,"onmobile":false},"copycode":{"enable":true,"show_result":false,"style":null},"back2top":{"enable":true,"sidebar":false,"scrollpercent":false},"bookmark":{"enable":false,"color":"#222","save":"auto"},"fancybox":true,"mediumzoom":false,"lazyload":true,"pangu":false,"comments":{"style":"tabs","active":null,"storage":true,"lazyload":false,"nav":null},"algolia":{"hits":{"per_page":10},"labels":{"input_placeholder":"Search for Posts","hits_empty":"We didn't find any results for the search: ${query}","hits_stats":"${hits} results found in ${time} ms"}},"localsearch":{"enable":false,"trigger":"auto","top_n_per_article":1,"unescape":false,"preload":false},"motion":{"enable":true,"async":false,"transition":{"post_block":"fadeIn","post_header":"slideDownIn","post_body":"slideDownIn","coll_header":"slideLeftIn","sidebar":"slideUpIn"}}}; - + - + + - + - - - - - + @@ -273,9 +270,31 @@

    Java 中的这个话题也是比较常遇到的，关于这块原先也是比较忽略的，但是仔细想想又有点遗忘了就在这里记一下
    简单看下代码
    java.lang.Object#equals

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    public boolean equals(Object obj) {
            return (this == obj);
        }
    +
    public boolean equals(Object obj) {
+        return (this == obj);
+    }

    对于所有对象的父类，equals 方法其实对比的就是对象的地址，也就是是否是同一个对象，试想如果像 Integer 或者 String 这种，我们没有重写 equals，那其实就等于是在用==，可能就没法达到我们的目的，所以像 String 这种常用的 jdk 类都是默认重写了
    java.lang.String#equals

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    public boolean equals(Object anObject) {
            if (this == anObject) {
                return true;
            }
            if (anObject instanceof String) {
                String anotherString = (String)anObject;
                int n = value.length;
                if (n == anotherString.value.length) {
                    char v1[] = value;
                    char v2[] = anotherString.value;
                    int i = 0;
                    while (n-- != 0) {
                        if (v1[i] != v2[i])
                            return false;
                        i++;
                    }
                    return true;
                }
            }
            return false;
        }
    +
    public boolean equals(Object anObject) {
+        if (this == anObject) {
+            return true;
+        }
+        if (anObject instanceof String) {
+            String anotherString = (String)anObject;
+            int n = value.length;
+            if (n == anotherString.value.length) {
+                char v1[] = value;
+                char v2[] = anotherString.value;
+                int i = 0;
+                while (n-- != 0) {
+                    if (v1[i] != v2[i])
+                        return false;
+                    i++;
+                }
+                return true;
+            }
+        }
+        return false;
+    }

    然后呢就是为啥一些书或者 effective java 中写了 equals 跟 hashCode 要一起重写，这里涉及到当对象作为 HashMap 的 key 的时候
    首先 HashMap 会使用 hashCode 去判断是否在同一个槽里，然后在通过 equals 去判断是否是同一个 key，是的话就替换，不是的话就链表接下去，如果不重写 hashCode 的话，默认的 object 的hashCode 是 native 方法，根据对象的地址生成的，这样其实对象的值相同的话，因为地址不同，HashMap 也会出现异常，所以需要重写，同时也需要重写 equals 方法，才能确认是同一个 key，而不是落在同一个槽的不同 key.

    diff --git a/2021/01/10/Leetcode-160-相交链表-intersection-of-two-linked-lists-题解分析/index.html b/2021/01/10/Leetcode-160-相交链表-intersection-of-two-linked-lists-题解分析/index.html index 07ec23803e..600fb07785 100644 --- a/2021/01/10/Leetcode-160-相交链表-intersection-of-two-linked-lists-题解分析/index.html +++ b/2021/01/10/Leetcode-160-相交链表-intersection-of-two-linked-lists-题解分析/index.html @@ -4,7 +4,7 @@ - + @@ -32,17 +32,16 @@ + - + - + + - - - @@ -236,13 +235,6 @@     - - - - - Edited on - - @@ -309,11 +301,55 @@

    题目介绍

    写一个程序找出两个单向链表的交叉起始点，可能是我英语不好，图里画的其实还有一点是交叉以后所有节点都是相同的
    Write a program to find the node at which the intersection of two singly linked lists begins.

    -

    For example, the following two linked lists:

    begin to intersect at node c1.

    -

    Example 1:

    -
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    Input: intersectVal = 8, listA = [4,1,8,4,5], listB = [5,6,1,8,4,5], skipA = 2, skipB = 3
    Output: Reference of the node with value = 8
    Input Explanation: The intersected node's value is 8 (note that this must not be 0 if the two lists intersect). From the head of A, it reads as [4,1,8,4,5]. From the head of B, it reads as [5,6,1,8,4,5]. There are 2 nodes before the intersected node in A; There are 3 nodes before the intersected node in B.
    +

    For example, the following two linked lists:

    begin to intersect at node c1.

    +

    Example 1:

    +
    Input: intersectVal = 8, listA = [4,1,8,4,5], listB = [5,6,1,8,4,5], skipA = 2, skipB = 3
+Output: Reference of the node with value = 8
+Input Explanation: The intersected node's value is 8 (note that this must not be 0 if the two lists intersect). From the head of A, it reads as [4,1,8,4,5]. From the head of B, it reads as [5,6,1,8,4,5]. There are 2 nodes before the intersected node in A; There are 3 nodes before the intersected node in B.

    分析题解

    一开始没什么头绪，感觉只能最原始的遍历，后来看了一些文章，发现比较简单的方式就是先找两个链表的长度差，因为从相交点开始肯定是长度一致的，这是个很好的解题突破口，找到长度差以后就是先跳过长链表的较长部分，然后开始同步遍历比较 A，B 链表；

    -

    代码

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    public ListNode getIntersectionNode(ListNode headA, ListNode headB) {
            if (headA == null || headB == null) {
                return null;
            }
            // 算 A 的长度
            int countA = 0;
            ListNode tailA = headA;
            while (tailA != null) {
                tailA = tailA.next;
                countA++;
            }
            // 算 B 的长度
            int countB = 0;
            ListNode tailB = headB;
            while (tailB != null) {
                tailB = tailB.next;
                countB++;
            }
            tailA = headA;
            tailB = headB;
            // 依据长度差，先让长的链表 tail 指针往后移
            if (countA > countB) {
                while (countA > countB) {
                    tailA = tailA.next;
                    countA--;
                }
            } else if (countA < countB) {
                while (countA < countB) {
                    tailB = tailB.next;
                    countB--;
                }
            }
            // 然后以相同速度遍历两个链表比较
            while (tailA != null) {
                if (tailA == tailB) {
                    return tailA;
                } else {
                    tailA = tailA.next;
                    tailB = tailB.next;
                }
            }
            return null;
        }
    +

    代码

    public ListNode getIntersectionNode(ListNode headA, ListNode headB) {
+        if (headA == null || headB == null) {
+            return null;
+        }
+        // 算 A 的长度
+        int countA = 0;
+        ListNode tailA = headA;
+        while (tailA != null) {
+            tailA = tailA.next;
+            countA++;
+        }
+        // 算 B 的长度
+        int countB = 0;
+        ListNode tailB = headB;
+        while (tailB != null) {
+            tailB = tailB.next;
+            countB++;
+        }
+        tailA = headA;
+        tailB = headB;
+        // 依据长度差，先让长的链表 tail 指针往后移
+        if (countA > countB) {
+            while (countA > countB) {
+                tailA = tailA.next;
+                countA--;
+            }
+        } else if (countA < countB) {
+            while (countA < countB) {
+                tailB = tailB.next;
+                countB--;
+            }
+        }
+        // 然后以相同速度遍历两个链表比较
+        while (tailA != null) {
+            if (tailA == tailB) {
+                return tailA;
+            } else {
+                tailA = tailA.next;
+                tailB = tailB.next;
+            }
+        }
+        return null;
+    }

    总结

    可能缺少这种思维，做的还是比较少，所以没法一下子反应过来，需要锻炼，我的第一反应是两重遍历，不过那样复杂度就高了，这里应该是只有 O(N) 的复杂度。

    @@ -331,13 +367,13 @@
    Leetcode 104 二叉树的最大深度(Maximum Depth of Binary Tree) 题解分析
  • -
    Leetcode 124 二叉树中的最大路径和(Binary Tree Maximum Path Sum) 题解分析
    +
    Leetcode 105 从前序与中序遍历序列构造二叉树(Construct Binary Tree from Preorder and Inorder Traversal) 题解分析
  • -
    Leetcode 105 从前序与中序遍历序列构造二叉树(Construct Binary Tree from Preorder and Inorder Traversal) 题解分析
    +
    Leetcode 124 二叉树中的最大路径和(Binary Tree Maximum Path Sum) 题解分析
  • -
    Leetcode 2 Add Two Numbers 题解分析
    +
    Leetcode 155 最小栈(Min Stack) 题解分析
    • @@ -465,7 +501,7 @@
    -
    1. 1. 题目介绍
      1. 1.1. Example 1:
    2. 2. 分析题解
      1. 2.1. 代码
      2. 2.2. 总结
    +
    1. 1. 题目介绍
      1. 1.1. Example 1:
    2. 2. 分析题解
      1. 2.1. 代码
      2. 2.2. 总结
    diff --git a/2021/01/17/聊聊那些加塞狗/index.html b/2021/01/17/聊聊那些加塞狗/index.html index b8f4ea8343..d5806ccb9e 100644 --- a/2021/01/17/聊聊那些加塞狗/index.html +++ b/2021/01/17/聊聊那些加塞狗/index.html @@ -4,7 +4,7 @@ - + @@ -32,13 +32,13 @@ + - + - @@ -297,19 +297,19 @@
    Related Posts
    diff --git a/2021/01/24/Leetcode-124-二叉树中的最大路径和-Binary-Tree-Maximum-Path-Sum-题解分析/index.html b/2021/01/24/Leetcode-124-二叉树中的最大路径和-Binary-Tree-Maximum-Path-Sum-题解分析/index.html index ce99337c92..111d9b5e7e 100644 --- a/2021/01/24/Leetcode-124-二叉树中的最大路径和-Binary-Tree-Maximum-Path-Sum-题解分析/index.html +++ b/2021/01/24/Leetcode-124-二叉树中的最大路径和-Binary-Tree-Maximum-Path-Sum-题解分析/index.html @@ -4,7 +4,7 @@ - + @@ -32,17 +32,17 @@ + - + - + - - - + + @@ -307,11 +307,34 @@

    路径 被定义为一条从树中任意节点出发，沿父节点-子节点连接，达到任意节点的序列。该路径 至少包含一个 节点，且不一定经过根节点。

    路径和 是路径中各节点值的总和。

    给你一个二叉树的根节点 root ，返回其 最大路径和

    -

    简要分析

    其实这个题目会被误解成比较简单，左子树最大的，或者右子树最大的，或者两边加一下，仔细想想都不对，其实有可能是产生于左子树中，或者右子树中，这两个都是指跟左子树根还有右子树根没关系的，这么说感觉不太容易理解，画个图

    可以看到图里，其实最长路径和是左边这个子树组成的，跟根节点还有右子树完全没关系，然后再想一种情况，如果是整棵树就是图中的左子树，那么这个最长路径和就是左子树加右子树加根节点了，所以不是我一开始想得那么简单，在代码实现中也需要一些技巧

    -

    代码

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    int ansNew = Integer.MIN_VALUE;
    public int maxPathSum(TreeNode root) {
            maxSumNew(root);
            return ansNew;
        }
        
    public int maxSumNew(TreeNode root) {
        if (root == null) {
            return 0;
        }
        // 这里是个简单的递归，就是去递归左右子树，但是这里其实有个概念，当这样处理时，其实相当于把子树的内部的最大路径和已经算出来了
        int left = maxSumNew(root.left);
        int right = maxSumNew(root.right);
        // 这里前面我有点没想明白，但是看到 ansNew 的比较，其实相当于，返回的是三种情况里的最大值，一个是左子树+根，一个是右子树+根，一个是单独根节点，
        // 这样这个递归的返回才会有意义，不然像原来的方法，它可能是跳着的，但是这种情况其实是借助于 ansNew 这个全局的最大值，因为原来我觉得要比较的是
        // left, right, left + root , right + root, root, left + right + root 这些的最大值，这里是分成了两个阶段，left 跟 right 的最大值已经在上面的
        // 调用过程中赋值给 ansNew 了    
        int currentSum = Math.max(Math.max(root.val + left , root.val + right), root.val);
        // 这边返回的是 currentSum，然后再用它跟 left + right + root 进行对比，然后再去更新 ans
        // PS: 有个小点也是这边的破局点，就是这个 ansNew
        int res = Math.max(left + right + root.val, currentSum);
        ans = Math.max(res, ans);
        return currentSum;
    }
    +

    简要分析

    其实这个题目会被误解成比较简单，左子树最大的，或者右子树最大的，或者两边加一下，仔细想想都不对，其实有可能是产生于左子树中，或者右子树中，这两个都是指跟左子树根还有右子树根没关系的，这么说感觉不太容易理解，画个图

    可以看到图里，其实最长路径和是左边这个子树组成的，跟根节点还有右子树完全没关系，然后再想一种情况，如果是整棵树就是图中的左子树，那么这个最长路径和就是左子树加右子树加根节点了，所以不是我一开始想得那么简单，在代码实现中也需要一些技巧

    +

    代码

    int ansNew = Integer.MIN_VALUE;
+public int maxPathSum(TreeNode root) {
+        maxSumNew(root);
+        return ansNew;
+    }
+    
+public int maxSumNew(TreeNode root) {
+    if (root == null) {
+        return 0;
+    }
+    // 这里是个简单的递归，就是去递归左右子树，但是这里其实有个概念，当这样处理时，其实相当于把子树的内部的最大路径和已经算出来了
+    int left = maxSumNew(root.left);
+    int right = maxSumNew(root.right);
+    // 这里前面我有点没想明白，但是看到 ansNew 的比较，其实相当于，返回的是三种情况里的最大值，一个是左子树+根，一个是右子树+根，一个是单独根节点，
+    // 这样这个递归的返回才会有意义，不然像原来的方法，它可能是跳着的，但是这种情况其实是借助于 ansNew 这个全局的最大值，因为原来我觉得要比较的是
+    // left, right, left + root , right + root, root, left + right + root 这些的最大值，这里是分成了两个阶段，left 跟 right 的最大值已经在上面的
+    // 调用过程中赋值给 ansNew 了    
+    int currentSum = Math.max(Math.max(root.val + left , root.val + right), root.val);
+    // 这边返回的是 currentSum，然后再用它跟 left + right + root 进行对比，然后再去更新 ans
+    // PS: 有个小点也是这边的破局点，就是这个 ansNew
+    int res = Math.max(left + right + root.val, currentSum);
+    ans = Math.max(res, ans);
+    return currentSum;
+}

    这里非常重要的就是 ansNew 是最后的一个结果，而对于 maxSumNew 这个函数的返回值其实是需要包含了一个连续结果，因为要返回继续去算路径和，所以返回的是 currentSum，最终结果是 ansNew

    -

    结果图

    难得有个 100%，贴个图哈哈

    +

    结果图

    难得有个 100%，贴个图哈哈

    @@ -331,10 +354,10 @@
    Leetcode 160 相交链表(intersection-of-two-linked-lists) 题解分析
  • -
    Leetcode 2 Add Two Numbers 题解分析
    +
    Leetcode 155 最小栈(Min Stack) 题解分析
  • -
    Leetcode 48 旋转图像(Rotate Image) 题解分析
    +
    Leetcode 121 买卖股票的最佳时机(Best Time to Buy and Sell Stock) 题解分析
    • @@ -463,7 +486,7 @@
    -
    1. 1. 题目介绍
    2. 2. 简要分析
    3. 3. 代码
    4. 4. 结果图
    +
    1. 1. 题目介绍
    2. 2. 简要分析
    3. 3. 代码
    4. 4. 结果图
    diff --git a/2021/01/31/聊聊-redis-缓存的应用问题/index.html b/2021/01/31/聊聊-redis-缓存的应用问题/index.html index 9f89ec8a05..76888cdb20 100644 --- a/2021/01/31/聊聊-redis-缓存的应用问题/index.html +++ b/2021/01/31/聊聊-redis-缓存的应用问题/index.html @@ -4,7 +4,7 @@ - + @@ -32,8 +32,9 @@ + - + @@ -456,7 +457,7 @@
    -
    1. 1. 缓存穿透
    2. 2. 缓存击穿
    3. 3. 缓存雪崩
    4. 4. 解决缓存穿透
    5. 5. 解决缓存击穿
    6. 6. 解决缓存雪崩
    +
    1. 1. 缓存穿透
    2. 2. 缓存击穿
    3. 3. 缓存雪崩
    4. 4. 解决缓存穿透
    5. 5. 解决缓存击穿
    6. 6. 解决缓存雪崩
    diff --git a/2021/02/07/关于读书打卡与分享/index.html b/2021/02/07/关于读书打卡与分享/index.html index 78cdc2b61d..aeb34cc6d9 100644 --- a/2021/02/07/关于读书打卡与分享/index.html +++ b/2021/02/07/关于读书打卡与分享/index.html @@ -4,7 +4,7 @@ - + @@ -32,13 +32,14 @@ + - + + - diff --git a/2021/02/14/AQS篇一/index.html b/2021/02/14/AQS篇一/index.html index 8fc37866ce..88807a167b 100644 --- a/2021/02/14/AQS篇一/index.html +++ b/2021/02/14/AQS篇一/index.html @@ -4,7 +4,7 @@ - + @@ -26,19 +26,20 @@ var CONFIG = {"hostname":"nicksxs.me","root":"/","scheme":"Pisces","version":"7.8.0","exturl":false,"sidebar":{"position":"left","display":"post","padding":18,"offset":12,"onmobile":false},"copycode":{"enable":true,"show_result":false,"style":null},"back2top":{"enable":true,"sidebar":false,"scrollpercent":false},"bookmark":{"enable":false,"color":"#222","save":"auto"},"fancybox":true,"mediumzoom":false,"lazyload":true,"pangu":false,"comments":{"style":"tabs","active":null,"storage":true,"lazyload":false,"nav":null},"algolia":{"hits":{"per_page":10},"labels":{"input_placeholder":"Search for Posts","hits_empty":"We didn't find any results for the search: ${query}","hits_stats":"${hits} results found in ${time} ms"}},"localsearch":{"enable":false,"trigger":"auto","top_n_per_article":1,"unescape":false,"preload":false},"motion":{"enable":true,"async":false,"transition":{"post_block":"fadeIn","post_header":"slideDownIn","post_body":"slideDownIn","coll_header":"slideLeftIn","sidebar":"slideUpIn"}}}; - + - + + - + - + + - @@ -231,13 +232,6 @@     - - - - - Edited on - - @@ -293,20 +287,213 @@

    很多东西都是时看时新，而且时间长了也会忘，所以再来复习下，也会有一些新的角度看法这次来聊下AQS的内容，主要是这几个点，

    第一个线程

    第一个线程抢到锁了，此时state跟阻塞队列是怎么样的，其实这里是之前没理解对的地方

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    /**
             * Fair version of tryAcquire.  Don't grant access unless
             * recursive call or no waiters or is first.
             */
            protected final boolean tryAcquire(int acquires) {
                final Thread current = Thread.currentThread();
                int c = getState();
                // 这里如果state还是0说明锁还空着
                if (c == 0) {
                    // 因为是公平锁版本的，先去看下是否阻塞队列里有排着队的
                    if (!hasQueuedPredecessors() &&
                        compareAndSetState(0, acquires)) {
                        // 没有排队的，并且state使用cas设置成功的就标记当前占有锁的线程是我
                        setExclusiveOwnerThread(current);
                        // 然后其实就返回了，包括阻塞队列的head和tail节点和waitStatus都没有设置
                        return true;
                    }
                }
                else if (current == getExclusiveOwnerThread()) {
                    int nextc = c + acquires;
                    if (nextc < 0)
                        throw new Error("Maximum lock count exceeded");
                    setState(nextc);
                    return true;
                }
                // 这里就是第二个线程会返回false
                return false;
            }
        }
    +
    /**
+         * Fair version of tryAcquire.  Don't grant access unless
+         * recursive call or no waiters or is first.
+         */
+        protected final boolean tryAcquire(int acquires) {
+            final Thread current = Thread.currentThread();
+            int c = getState();
+            // 这里如果state还是0说明锁还空着
+            if (c == 0) {
+                // 因为是公平锁版本的，先去看下是否阻塞队列里有排着队的
+                if (!hasQueuedPredecessors() &&
+                    compareAndSetState(0, acquires)) {
+                    // 没有排队的，并且state使用cas设置成功的就标记当前占有锁的线程是我
+                    setExclusiveOwnerThread(current);
+                    // 然后其实就返回了，包括阻塞队列的head和tail节点和waitStatus都没有设置
+                    return true;
+                }
+            }
+            else if (current == getExclusiveOwnerThread()) {
+                int nextc = c + acquires;
+                if (nextc < 0)
+                    throw new Error("Maximum lock count exceeded");
+                setState(nextc);
+                return true;
+            }
+            // 这里就是第二个线程会返回false
+            return false;
+        }
+    }

    第二个线程

    当第二个线程进来的时候应该是怎么样，结合代码来看

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    /**
         * Acquires in exclusive mode, ignoring interrupts.  Implemented
         * by invoking at least once {@link #tryAcquire},
         * returning on success.  Otherwise the thread is queued, possibly
         * repeatedly blocking and unblocking, invoking {@link
         * #tryAcquire} until success.  This method can be used
         * to implement method {@link Lock#lock}.
         *
         * @param arg the acquire argument.  This value is conveyed to
         *        {@link #tryAcquire} but is otherwise uninterpreted and
         *        can represent anything you like.
         */
        public final void acquire(int arg) {
            // 前面第一种情况是tryAcquire直接成功了，这个if判断第一个条件就是false，就不往下执行了
            // 如果是第二个线程，第一个条件获取锁不成功，条件判断!tryAcquire(arg) == true，就会走
            // acquireQueued(addWaiter(Node.EXCLUSIVE), arg)
            if (!tryAcquire(arg) &&
                acquireQueued(addWaiter(Node.EXCLUSIVE), arg))
                selfInterrupt();
        }
    +
    /**
+     * Acquires in exclusive mode, ignoring interrupts.  Implemented
+     * by invoking at least once {@link #tryAcquire},
+     * returning on success.  Otherwise the thread is queued, possibly
+     * repeatedly blocking and unblocking, invoking {@link
+     * #tryAcquire} until success.  This method can be used
+     * to implement method {@link Lock#lock}.
+     *
+     * @param arg the acquire argument.  This value is conveyed to
+     *        {@link #tryAcquire} but is otherwise uninterpreted and
+     *        can represent anything you like.
+     */
+    public final void acquire(int arg) {
+        // 前面第一种情况是tryAcquire直接成功了，这个if判断第一个条件就是false，就不往下执行了
+        // 如果是第二个线程，第一个条件获取锁不成功，条件判断!tryAcquire(arg) == true，就会走
+        // acquireQueued(addWaiter(Node.EXCLUSIVE), arg)
+        if (!tryAcquire(arg) &&
+            acquireQueued(addWaiter(Node.EXCLUSIVE), arg))
+            selfInterrupt();
+    }

    然后来看下addWaiter的逻辑

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    /**
         * Creates and enqueues node for current thread and given mode.
         *
         * @param mode Node.EXCLUSIVE for exclusive, Node.SHARED for shared
         * @return the new node
         */
        private Node addWaiter(Node mode) {
            // 这里是包装成一个node
            Node node = new Node(Thread.currentThread(), mode);
            // Try the fast path of enq; backup to full enq on failure
            // 最快的方式就是把当前线程的节点放在阻塞队列的最后
            Node pred = tail;
            // 只有当tail，也就是pred不为空的时候可以直接接上
            if (pred != null) {
                node.prev = pred;
                // 如果这里cas成功了，就直接接上返回了
                if (compareAndSetTail(pred, node)) {
                    pred.next = node;
                    return node;
                }
            }
            // 不然就会继续走到这里
            enq(node);
            return node;
        }
    +
    /**
+     * Creates and enqueues node for current thread and given mode.
+     *
+     * @param mode Node.EXCLUSIVE for exclusive, Node.SHARED for shared
+     * @return the new node
+     */
+    private Node addWaiter(Node mode) {
+        // 这里是包装成一个node
+        Node node = new Node(Thread.currentThread(), mode);
+        // Try the fast path of enq; backup to full enq on failure
+        // 最快的方式就是把当前线程的节点放在阻塞队列的最后
+        Node pred = tail;
+        // 只有当tail，也就是pred不为空的时候可以直接接上
+        if (pred != null) {
+            node.prev = pred;
+            // 如果这里cas成功了，就直接接上返回了
+            if (compareAndSetTail(pred, node)) {
+                pred.next = node;
+                return node;
+            }
+        }
+        // 不然就会继续走到这里
+        enq(node);
+        return node;
+    }

    然后就是enq的逻辑了

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    /**
         * Inserts node into queue, initializing if necessary. See picture above.
         * @param node the node to insert
         * @return node's predecessor
         */
        private Node enq(final Node node) {
            for (;;) {
                // 如果状态没变化的话，tail这时还是null的
                Node t = tail;
                if (t == null) { // Must initialize
                    // 这里就会初始化头结点，就是个空节点
                    if (compareAndSetHead(new Node()))
                        // tail也赋值成head
                        tail = head;
                } else {
                    // 这里就设置tail了
                    node.prev = t;
                    if (compareAndSetTail(t, node)) {
                        t.next = node;
                        return t;
                    }
                }
            }
        }
    +
    /**
+     * Inserts node into queue, initializing if necessary. See picture above.
+     * @param node the node to insert
+     * @return node's predecessor
+     */
+    private Node enq(final Node node) {
+        for (;;) {
+            // 如果状态没变化的话，tail这时还是null的
+            Node t = tail;
+            if (t == null) { // Must initialize
+                // 这里就会初始化头结点，就是个空节点
+                if (compareAndSetHead(new Node()))
+                    // tail也赋值成head
+                    tail = head;
+            } else {
+                // 这里就设置tail了
+                node.prev = t;
+                if (compareAndSetTail(t, node)) {
+                    t.next = node;
+                    return t;
+                }
+            }
+        }
+    }

    所以从这里可以看出来，其实head头结点不是个真实的带有线程的节点，并且不是在第一个线程进来的时候设置的

    解锁

    通过代码来看下

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    /**
         * Attempts to release this lock.
         *
         * <p>If the current thread is the holder of this lock then the hold
         * count is decremented.  If the hold count is now zero then the lock
         * is released.  If the current thread is not the holder of this
         * lock then {@link IllegalMonitorStateException} is thrown.
         *
         * @throws IllegalMonitorStateException if the current thread does not
         *         hold this lock
         */
        public void unlock() {
            // 释放锁
            sync.release(1);
        }
    /**
         * Releases in exclusive mode.  Implemented by unblocking one or
         * more threads if {@link #tryRelease} returns true.
         * This method can be used to implement method {@link Lock#unlock}.
         *
         * @param arg the release argument.  This value is conveyed to
         *        {@link #tryRelease} but is otherwise uninterpreted and
         *        can represent anything you like.
         * @return the value returned from {@link #tryRelease}
         */
        public final boolean release(int arg) {
            // 尝试去释放
            if (tryRelease(arg)) {
                Node h = head;
                if (h != null && h.waitStatus != 0)
                    unparkSuccessor(h);
                return true;
            }
            return false;
        }
    protected final boolean tryRelease(int releases) {
                int c = getState() - releases;
                if (Thread.currentThread() != getExclusiveOwnerThread())
                    throw new IllegalMonitorStateException();
                boolean free = false;
        		// 判断是否完全释放锁，因为可重入
                if (c == 0) {
                    free = true;
                    setExclusiveOwnerThread(null);
                }
                setState(c);
                return free;
            }
    // 这段代码和上面的一致，只是为了顺序性，又拷下来看下

    public final boolean release(int arg) {
            // 尝试去释放，如果是完全释放，返回的就是true，否则是false
            if (tryRelease(arg)) {
                Node h = head;
                // 这里判断头结点是否为空以及waitStatus的状态，前面说了head节点其实是
                // 在第二个线程进来的时候初始化的，如果是空的话说明没后续节点，并且waitStatus
                // 也表示了后续的等待状态
                if (h != null && h.waitStatus != 0)
                    unparkSuccessor(h);
                return true;
            }
            return false;
        }

    /**
         * Wakes up node's successor, if one exists.
         *
         * @param node the node
         */
    // 唤醒后继节点
        private void unparkSuccessor(Node node) {
            /*
             * If status is negative (i.e., possibly needing signal) try
             * to clear in anticipation of signalling.  It is OK if this
             * fails or if status is changed by waiting thread.
             */
            int ws = node.waitStatus;
            if (ws < 0)
                compareAndSetWaitStatus(node, ws, 0);

            /*
             * Thread to unpark is held in successor, which is normally
             * just the next node.  But if cancelled or apparently null,
             * traverse backwards from tail to find the actual
             * non-cancelled successor.
             */
            Node s = node.next;
            // 如果后继节点是空或者当前节点取消等待了
            if (s == null || s.waitStatus > 0) {
                s = null;
                // 从后往前找，找到非取消的节点，注意这里不是找到就退出，而是一直找到头
                // 所以不必担心中间有取消的
                for (Node t = tail; t != null && t != node; t = t.prev)
                    if (t.waitStatus <= 0)
                        s = t;
            }
            if (s != null)
                // 将其唤醒
                LockSupport.unpark(s.thread);
        }
    +
    /**
+     * Attempts to release this lock.
+     *
+     * <p>If the current thread is the holder of this lock then the hold
+     * count is decremented.  If the hold count is now zero then the lock
+     * is released.  If the current thread is not the holder of this
+     * lock then {@link IllegalMonitorStateException} is thrown.
+     *
+     * @throws IllegalMonitorStateException if the current thread does not
+     *         hold this lock
+     */
+    public void unlock() {
+        // 释放锁
+        sync.release(1);
+    }
+/**
+     * Releases in exclusive mode.  Implemented by unblocking one or
+     * more threads if {@link #tryRelease} returns true.
+     * This method can be used to implement method {@link Lock#unlock}.
+     *
+     * @param arg the release argument.  This value is conveyed to
+     *        {@link #tryRelease} but is otherwise uninterpreted and
+     *        can represent anything you like.
+     * @return the value returned from {@link #tryRelease}
+     */
+    public final boolean release(int arg) {
+        // 尝试去释放
+        if (tryRelease(arg)) {
+            Node h = head;
+            if (h != null && h.waitStatus != 0)
+                unparkSuccessor(h);
+            return true;
+        }
+        return false;
+    }
+protected final boolean tryRelease(int releases) {
+            int c = getState() - releases;
+            if (Thread.currentThread() != getExclusiveOwnerThread())
+                throw new IllegalMonitorStateException();
+            boolean free = false;
+    		// 判断是否完全释放锁，因为可重入
+            if (c == 0) {
+                free = true;
+                setExclusiveOwnerThread(null);
+            }
+            setState(c);
+            return free;
+        }
+// 这段代码和上面的一致，只是为了顺序性，又拷下来看下
+
+public final boolean release(int arg) {
+        // 尝试去释放，如果是完全释放，返回的就是true，否则是false
+        if (tryRelease(arg)) {
+            Node h = head;
+            // 这里判断头结点是否为空以及waitStatus的状态，前面说了head节点其实是
+            // 在第二个线程进来的时候初始化的，如果是空的话说明没后续节点，并且waitStatus
+            // 也表示了后续的等待状态
+            if (h != null && h.waitStatus != 0)
+                unparkSuccessor(h);
+            return true;
+        }
+        return false;
+    }
+
+/**
+     * Wakes up node's successor, if one exists.
+     *
+     * @param node the node
+     */
+// 唤醒后继节点
+    private void unparkSuccessor(Node node) {
+        /*
+         * If status is negative (i.e., possibly needing signal) try
+         * to clear in anticipation of signalling.  It is OK if this
+         * fails or if status is changed by waiting thread.
+         */
+        int ws = node.waitStatus;
+        if (ws < 0)
+            compareAndSetWaitStatus(node, ws, 0);
+
+        /*
+         * Thread to unpark is held in successor, which is normally
+         * just the next node.  But if cancelled or apparently null,
+         * traverse backwards from tail to find the actual
+         * non-cancelled successor.
+         */
+        Node s = node.next;
+        // 如果后继节点是空或者当前节点取消等待了
+        if (s == null || s.waitStatus > 0) {
+            s = null;
+            // 从后往前找，找到非取消的节点，注意这里不是找到就退出，而是一直找到头
+            // 所以不必担心中间有取消的
+            for (Node t = tail; t != null && t != node; t = t.prev)
+                if (t.waitStatus <= 0)
+                    s = t;
+        }
+        if (s != null)
+            // 将其唤醒
+            LockSupport.unpark(s.thread);
+    }
    @@ -327,13 +514,13 @@
    AbstractQueuedSynchronizer
  • -
    Leetcode 121 买卖股票的最佳时机(Best Time to Buy and Sell Stock) 题解分析
    +
    Leetcode 3 Longest Substring Without Repeating Characters 题解分析
  • -
    Leetcode 124 二叉树中的最大路径和(Binary Tree Maximum Path Sum) 题解分析
    +
    Leetcode 105 从前序与中序遍历序列构造二叉树(Construct Binary Tree from Preorder and Inorder Traversal) 题解分析
  • -
    Leetcode 105 从前序与中序遍历序列构造二叉树(Construct Binary Tree from Preorder and Inorder Traversal) 题解分析
    +
    Leetcode 155 最小栈(Min Stack) 题解分析
    • @@ -461,7 +648,7 @@
    -
    1. 1. 第一个线程
    2. 2. 第二个线程
    3. 3. 解锁
    +
    1. 1. 第一个线程
    2. 2. 第二个线程
    3. 3. 解锁
    diff --git a/2021/02/21/AQS-之-Condition-浅析笔记/index.html b/2021/02/21/AQS-之-Condition-浅析笔记/index.html index 23b756fcbf..548c4d612a 100644 --- a/2021/02/21/AQS-之-Condition-浅析笔记/index.html +++ b/2021/02/21/AQS-之-Condition-浅析笔记/index.html @@ -4,7 +4,7 @@ - + @@ -26,20 +26,21 @@ var CONFIG = {"hostname":"nicksxs.me","root":"/","scheme":"Pisces","version":"7.8.0","exturl":false,"sidebar":{"position":"left","display":"post","padding":18,"offset":12,"onmobile":false},"copycode":{"enable":true,"show_result":false,"style":null},"back2top":{"enable":true,"sidebar":false,"scrollpercent":false},"bookmark":{"enable":false,"color":"#222","save":"auto"},"fancybox":true,"mediumzoom":false,"lazyload":true,"pangu":false,"comments":{"style":"tabs","active":null,"storage":true,"lazyload":false,"nav":null},"algolia":{"hits":{"per_page":10},"labels":{"input_placeholder":"Search for Posts","hits_empty":"We didn't find any results for the search: ${query}","hits_stats":"${hits} results found in ${time} ms"}},"localsearch":{"enable":false,"trigger":"auto","top_n_per_article":1,"unescape":false,"preload":false},"motion":{"enable":true,"async":false,"transition":{"post_block":"fadeIn","post_header":"slideDownIn","post_body":"slideDownIn","coll_header":"slideLeftIn","sidebar":"slideUpIn"}}}; - + - + + - + + - @@ -291,27 +292,483 @@
    -

    Condition也是 AQS 中很重要的一块内容，可以先看段示例代码，这段代码应该来自于Doug Lea大大，可以在 javadoc 中的 condition 部分找到，其实大大原来写过基于 synchronized 实现的，后面我也贴下代码

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    import java.util.concurrent.locks.Condition;
    import java.util.concurrent.locks.Lock;
    import java.util.concurrent.locks.ReentrantLock;

    class BoundedBuffer {
        final Lock lock = new ReentrantLock();
        // condition 依赖于 lock 来产生
        final Condition notFull = lock.newCondition();
        final Condition notEmpty = lock.newCondition();

        // 对象池子，put 跟 take 的就是这里的
        final Object[] items = new Object[100];
        int putptr, takeptr, count;

        // 生产
        public void put(Object x) throws InterruptedException {
            // 这里也说明了，需要先拥有锁
            lock.lock();
            try {
                while (count == items.length)
                    notFull.await();  // 队列已满，等待，直到 not full 才能继续生产
                items[putptr] = x;
                if (++putptr == items.length) putptr = 0;
                ++count;
                notEmpty.signal(); // 生产成功，队列已经 not empty 了，发个通知出去
            } finally {
                lock.unlock();
            }
        }

        // 消费
        public Object take() throws InterruptedException {
            lock.lock();
            try {
                while (count == 0)
                    notEmpty.await(); // 队列为空，等待，直到队列 not empty，才能继续消费
                Object x = items[takeptr];
                if (++takeptr == items.length) takeptr = 0;
                --count;
                notFull.signal(); // 被我消费掉一个，队列 not full 了，发个通知出去
                return x;
            } finally {
                lock.unlock();
            }
        }
    }
    +

    Condition也是 AQS 中很重要的一块内容，可以先看段示例代码，这段代码应该来自于Doug Lea大大，可以在 javadoc 中的 condition 部分找到，其实大大原来写过基于 synchronized 实现的，后面我也贴下代码

    +
    import java.util.concurrent.locks.Condition;
+import java.util.concurrent.locks.Lock;
+import java.util.concurrent.locks.ReentrantLock;
+
+class BoundedBuffer {
+    final Lock lock = new ReentrantLock();
+    // condition 依赖于 lock 来产生
+    final Condition notFull = lock.newCondition();
+    final Condition notEmpty = lock.newCondition();
+
+    // 对象池子，put 跟 take 的就是这里的
+    final Object[] items = new Object[100];
+    int putptr, takeptr, count;
+
+    // 生产
+    public void put(Object x) throws InterruptedException {
+        // 这里也说明了，需要先拥有锁
+        lock.lock();
+        try {
+            while (count == items.length)
+                notFull.await();  // 队列已满，等待，直到 not full 才能继续生产
+            items[putptr] = x;
+            if (++putptr == items.length) putptr = 0;
+            ++count;
+            notEmpty.signal(); // 生产成功，队列已经 not empty 了，发个通知出去
+        } finally {
+            lock.unlock();
+        }
+    }
+
+    // 消费
+    public Object take() throws InterruptedException {
+        lock.lock();
+        try {
+            while (count == 0)
+                notEmpty.await(); // 队列为空，等待，直到队列 not empty，才能继续消费
+            Object x = items[takeptr];
+            if (++takeptr == items.length) takeptr = 0;
+            --count;
+            notFull.signal(); // 被我消费掉一个，队列 not full 了，发个通知出去
+            return x;
+        } finally {
+            lock.unlock();
+        }
+    }
+}

    介绍下 Condition 的结构

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    public class ConditionObject implements Condition, java.io.Serializable {
            private static final long serialVersionUID = 1173984872572414699L;
            /** First node of condition queue. */
            private transient Node firstWaiter;
            /** Last node of condition queue. */
            private transient Node lastWaiter;
    -

    主要的就这么点，而且也复用了 AQS 阻塞队列或者大大叫 lock queue中同样的 Node 节点，只不过它没有使用其中的双向队列，也就是prev 和 next，而是在 Node 中的 nextWaiter，所以只是个单向的队列，没使用 next 其实还有个用处，后面会提到，看下结构的示意图

    然后主要是看两个方法，await 和 signal,
    先来看下 await

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    /**
     * Implements interruptible condition wait.
     * <ol>
     * <li> If current thread is interrupted, throw InterruptedException.
     * <li> Save lock state returned by {@link #getState}.
     * <li> Invoke {@link #release} with saved state as argument,
     *      throwing IllegalMonitorStateException if it fails.
     * <li> Block until signalled or interrupted.
     * <li> Reacquire by invoking specialized version of
     *      {@link #acquire} with saved state as argument.
     * <li> If interrupted while blocked in step 4, throw InterruptedException.
     * </ol>
     */
    public final void await() throws InterruptedException {
        if (Thread.interrupted())
            throw new InterruptedException();

        // 将当前节点包装成一个  condition waiter node 节点
        Node node = addConditionWaiter();

        // 完全释放占有的锁，这里需要是占有锁的线程
        int savedState = fullyRelease(node);
        int interruptMode = 0;

        // 判断下是否在阻塞队列中，因为有可能被其他节点从等待队列移动到阻塞队列
        while (!isOnSyncQueue(node)) {
            // park等待，等待被唤醒
            LockSupport.park(this);
            if ((interruptMode = checkInterruptWhileWaiting(node)) != 0)
                break;
        }

        // 被唤醒后进入阻塞队列，等待获取锁，这里继续用了fullyRelease返回的 state
        if (acquireQueued(node, savedState) && interruptMode != THROW_IE)
            interruptMode = REINTERRUPT;
        if (node.nextWaiter != null) // clean up if cancelled
            unlinkCancelledWaiters();
        if (interruptMode != 0)
            reportInterruptAfterWait(interruptMode);
    }
    +
    public class ConditionObject implements Condition, java.io.Serializable {
+        private static final long serialVersionUID = 1173984872572414699L;
+        /** First node of condition queue. */
+        private transient Node firstWaiter;
+        /** Last node of condition queue. */
+        private transient Node lastWaiter;
    +

    主要的就这么点，而且也复用了 AQS 阻塞队列或者大大叫 lock queue中同样的 Node 节点，只不过它没有使用其中的双向队列，也就是prev 和 next，而是在 Node 中的 nextWaiter，所以只是个单向的队列，没使用 next 其实还有个用处，后面会提到，看下结构的示意图

    然后主要是看两个方法，await 和 signal,
    先来看下 await

    +
    /**
+ * Implements interruptible condition wait.
+ * <ol>
+ * <li> If current thread is interrupted, throw InterruptedException.
+ * <li> Save lock state returned by {@link #getState}.
+ * <li> Invoke {@link #release} with saved state as argument,
+ *      throwing IllegalMonitorStateException if it fails.
+ * <li> Block until signalled or interrupted.
+ * <li> Reacquire by invoking specialized version of
+ *      {@link #acquire} with saved state as argument.
+ * <li> If interrupted while blocked in step 4, throw InterruptedException.
+ * </ol>
+ */
+public final void await() throws InterruptedException {
+    if (Thread.interrupted())
+        throw new InterruptedException();
+
+    // 将当前节点包装成一个  condition waiter node 节点
+    Node node = addConditionWaiter();
+
+    // 完全释放占有的锁，这里需要是占有锁的线程
+    int savedState = fullyRelease(node);
+    int interruptMode = 0;
+
+    // 判断下是否在阻塞队列中，因为有可能被其他节点从等待队列移动到阻塞队列
+    while (!isOnSyncQueue(node)) {
+        // park等待，等待被唤醒
+        LockSupport.park(this);
+        if ((interruptMode = checkInterruptWhileWaiting(node)) != 0)
+            break;
+    }
+
+    // 被唤醒后进入阻塞队列，等待获取锁，这里继续用了fullyRelease返回的 state
+    if (acquireQueued(node, savedState) && interruptMode != THROW_IE)
+        interruptMode = REINTERRUPT;
+    if (node.nextWaiter != null) // clean up if cancelled
+        unlinkCancelledWaiters();
+    if (interruptMode != 0)
+        reportInterruptAfterWait(interruptMode);
+}

    添加条件队列节点

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    /**
     * Adds a new waiter to wait queue.
     * @return its new wait node
     */
    private Node addConditionWaiter() {
        Node t = lastWaiter;
        // If lastWaiter is cancelled, clean out.
        // 如果节点已经不是 CONDITION 状态了，表示已经取消了
        if (t != null && t.waitStatus != Node.CONDITION) {
            // 把等待队列中取消的节点清理出去
            unlinkCancelledWaiters();
            t = lastWaiter;
        }
        // 把当前线程包装成waitStatus=CONDITION 的节点
        Node node = new Node(Thread.currentThread(), Node.CONDITION);
        // 没有 lastWaiter 节点，直接是 firstWaiter
        if (t == null)
            firstWaiter = node;
        else
        // 不然就接在 lastWaiter 后面
            t.nextWaiter = node;
        // 当前节点就会变成新的 lastWaiter
        lastWaiter = node;
        return node;
    }
    +
    /**
+ * Adds a new waiter to wait queue.
+ * @return its new wait node
+ */
+private Node addConditionWaiter() {
+    Node t = lastWaiter;
+    // If lastWaiter is cancelled, clean out.
+    // 如果节点已经不是 CONDITION 状态了，表示已经取消了
+    if (t != null && t.waitStatus != Node.CONDITION) {
+        // 把等待队列中取消的节点清理出去
+        unlinkCancelledWaiters();
+        t = lastWaiter;
+    }
+    // 把当前线程包装成waitStatus=CONDITION 的节点
+    Node node = new Node(Thread.currentThread(), Node.CONDITION);
+    // 没有 lastWaiter 节点，直接是 firstWaiter
+    if (t == null)
+        firstWaiter = node;
+    else
+    // 不然就接在 lastWaiter 后面
+        t.nextWaiter = node;
+    // 当前节点就会变成新的 lastWaiter
+    lastWaiter = node;
+    return node;
+}

    清理取消的节点

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    /**
     * Unlinks cancelled waiter nodes from condition queue.
     * Called only while holding lock. This is called when
     * cancellation occurred during condition wait, and upon
     * insertion of a new waiter when lastWaiter is seen to have
     * been cancelled. This method is needed to avoid garbage
     * retention in the absence of signals. So even though it may
     * require a full traversal, it comes into play only when
     * timeouts or cancellations occur in the absence of
     * signals. It traverses all nodes rather than stopping at a
     * particular target to unlink all pointers to garbage nodes
     * without requiring many re-traversals during cancellation
     * storms.
     */
    private void unlinkCancelledWaiters() {
        Node t = firstWaiter;
        Node trail = null;
        // 循环遍历单向链表的节点，如果状态不是 CONDITION 就清出去
        while (t != null) {
            Node next = t.nextWaiter;
            // 循环链表操作，清掉取消的节点
            if (t.waitStatus != Node.CONDITION) {
                t.nextWaiter = null;
                if (trail == null)
                    firstWaiter = next;
                else
                    trail.nextWaiter = next;
                if (next == null)
                    lastWaiter = trail;
            }
            else
                trail = t;
            t = next;
        }
    }
    +
    /**
+ * Unlinks cancelled waiter nodes from condition queue.
+ * Called only while holding lock. This is called when
+ * cancellation occurred during condition wait, and upon
+ * insertion of a new waiter when lastWaiter is seen to have
+ * been cancelled. This method is needed to avoid garbage
+ * retention in the absence of signals. So even though it may
+ * require a full traversal, it comes into play only when
+ * timeouts or cancellations occur in the absence of
+ * signals. It traverses all nodes rather than stopping at a
+ * particular target to unlink all pointers to garbage nodes
+ * without requiring many re-traversals during cancellation
+ * storms.
+ */
+private void unlinkCancelledWaiters() {
+    Node t = firstWaiter;
+    Node trail = null;
+    // 循环遍历单向链表的节点，如果状态不是 CONDITION 就清出去
+    while (t != null) {
+        Node next = t.nextWaiter;
+        // 循环链表操作，清掉取消的节点
+        if (t.waitStatus != Node.CONDITION) {
+            t.nextWaiter = null;
+            if (trail == null)
+                firstWaiter = next;
+            else
+                trail.nextWaiter = next;
+            if (next == null)
+                lastWaiter = trail;
+        }
+        else
+            trail = t;
+        t = next;
+    }
+}

    完全释放锁

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    /**
     * Invokes release with current state value; returns saved state.
     * Cancels node and throws exception on failure.
     * @param node the condition node for this wait
     * @return previous sync state
     */
    final int fullyRelease(Node node) {
        boolean failed = true;
        try {
            // 获取下当前的 state 值，因为是可重入的，所以这个值要保存下来
            int savedState = getState();
            // 这里还包含比较多操作，不过跟前面分析 AQS 的释放比较类似，不深入了
            if (release(savedState)) {
                failed = false;
                // 返回这个值
                return savedState;
            } else {
                throw new IllegalMonitorStateException();
            }
        } finally {
            if (failed)
                node.waitStatus = Node.CANCELLED;
        }
    }
    +
    /**
+ * Invokes release with current state value; returns saved state.
+ * Cancels node and throws exception on failure.
+ * @param node the condition node for this wait
+ * @return previous sync state
+ */
+final int fullyRelease(Node node) {
+    boolean failed = true;
+    try {
+        // 获取下当前的 state 值，因为是可重入的，所以这个值要保存下来
+        int savedState = getState();
+        // 这里还包含比较多操作，不过跟前面分析 AQS 的释放比较类似，不深入了
+        if (release(savedState)) {
+            failed = false;
+            // 返回这个值
+            return savedState;
+        } else {
+            throw new IllegalMonitorStateException();
+        }
+    } finally {
+        if (failed)
+            node.waitStatus = Node.CANCELLED;
+    }
+}

    判断是否在阻塞队列中

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    /**
     * Returns true if a node, always one that was initially placed on
     * a condition queue, is now waiting to reacquire on sync queue.
     * @param node the node
     * @return true if is reacquiring
     */
    final boolean isOnSyncQueue(Node node) {
        // 如果waitStatus 是 CONDITION 或者没有 prev 前置节点肯定就不在
        if (node.waitStatus == Node.CONDITION || node.prev == null)
            return false;
        // 这里就是我前面提到的 next 的作用
        if (node.next != null) // If has successor, it must be on queue
            return true;
        // 从 tail 开始找，是否在阻塞队列中
        /*
         * node.prev can be non-null, but not yet on queue because
         * the CAS to place it on queue can fail. So we have to
         * traverse from tail to make sure it actually made it.  It
         * will always be near the tail in calls to this method, and
         * unless the CAS failed (which is unlikely), it will be
         * there, so we hardly ever traverse much.
         */
        return findNodeFromTail(node);
    }
    /**
     * Returns true if node is on sync queue by searching backwards from tail.
     * Called only when needed by isOnSyncQueue.
     * @return true if present
     */
    private boolean findNodeFromTail(Node node) {
        Node t = tail;
        // 从 tail 开始，从后往前找
        for (;;) {
            if (t == node)
                return true;
            if (t == null)
                return false;
            t = t.prev;
        }
    }
    +
    /**
+ * Returns true if a node, always one that was initially placed on
+ * a condition queue, is now waiting to reacquire on sync queue.
+ * @param node the node
+ * @return true if is reacquiring
+ */
+final boolean isOnSyncQueue(Node node) {
+    // 如果waitStatus 是 CONDITION 或者没有 prev 前置节点肯定就不在
+    if (node.waitStatus == Node.CONDITION || node.prev == null)
+        return false;
+    // 这里就是我前面提到的 next 的作用
+    if (node.next != null) // If has successor, it must be on queue
+        return true;
+    // 从 tail 开始找，是否在阻塞队列中
+    /*
+     * node.prev can be non-null, but not yet on queue because
+     * the CAS to place it on queue can fail. So we have to
+     * traverse from tail to make sure it actually made it.  It
+     * will always be near the tail in calls to this method, and
+     * unless the CAS failed (which is unlikely), it will be
+     * there, so we hardly ever traverse much.
+     */
+    return findNodeFromTail(node);
+}
+/**
+ * Returns true if node is on sync queue by searching backwards from tail.
+ * Called only when needed by isOnSyncQueue.
+ * @return true if present
+ */
+private boolean findNodeFromTail(Node node) {
+    Node t = tail;
+    // 从 tail 开始，从后往前找
+    for (;;) {
+        if (t == node)
+            return true;
+        if (t == null)
+            return false;
+        t = t.prev;
+    }
+}

    await 的逻辑差不多就是这样子，主要的就是把自己包成一个 Node 节点，waitStatus 的状态是 CONDITION，挂在等待队列的最后，然后完全释放锁，park 等待

    -

    signal

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    /**
     * Moves the longest-waiting thread, if one exists, from the
     * wait queue for this condition to the wait queue for the
     * owning lock.
     *
     * @throws IllegalMonitorStateException if {@link #isHeldExclusively}
     *         returns {@code false}
     */
    public final void signal() {
        if (!isHeldExclusively())
            throw new IllegalMonitorStateException();
        // firstWaiter 肯定是最早开始等待的
        Node first = firstWaiter;
        // 如果不为空就唤醒
        if (first != null)
            doSignal(first);
    }
    /**
     * Removes and transfers nodes until hit non-cancelled one or
     * null. Split out from signal in part to encourage compilers
     * to inline the case of no waiters.
     * @param first (non-null) the first node on condition queue
     */
    private void doSignal(Node first) {
        do {
            // 因为要去唤醒 first 节点了，firstWaiter 需要再从后面找一个
            // 并且判断是否为空，如果是空的话就直接可以把 lastWaiter 设置成空了
            if ( (firstWaiter = first.nextWaiter) == null)
                lastWaiter = null;
            //  first 不需要继续保存后面的 waiter 了，因为 firstWaiter 已经是 first 的后置节点了
            first.nextWaiter = null;
        // 如果 first 节点转移不成功，并且 firstWaiter 节点不为空，则继续进入循环
        } while (!transferForSignal(first) &&
                 (first = firstWaiter) != null);
    }
    /**
     * Transfers a node from a condition queue onto sync queue.
     * Returns true if successful.
     * @param node the node
     * @return true if successfully transferred (else the node was
     * cancelled before signal)
     */
    final boolean transferForSignal(Node node) {
        /*
         * If cannot change waitStatus, the node has been cancelled.
         */
        // 如果状态已经不是 CONDITION 就不会设置成功，返回 false
        if (!compareAndSetWaitStatus(node, Node.CONDITION, 0))
            return false;
        /*
         * Splice onto queue and try to set waitStatus of predecessor to
         * indicate that thread is (probably) waiting. If cancelled or
         * attempt to set waitStatus fails, wake up to resync (in which
         * case the waitStatus can be transiently and harmlessly wrong).
         */
        // 调用跟aqs 第一篇中一样的 enq 方法进入阻塞队列，返回入队后的前一节点
        Node p = enq(node);
        int ws = p.waitStatus;
        // 将前置节点状态设置成SIGNAL，表示后面有节点在等了
        if (ws > 0 || !compareAndSetWaitStatus(p, ws, Node.SIGNAL))
            LockSupport.unpark(node.thread);
        // 返回 true，上一个方法的循环就退出了
        return true;
    }
    +

    signal

    /**
+ * Moves the longest-waiting thread, if one exists, from the
+ * wait queue for this condition to the wait queue for the
+ * owning lock.
+ *
+ * @throws IllegalMonitorStateException if {@link #isHeldExclusively}
+ *         returns {@code false}
+ */
+public final void signal() {
+    if (!isHeldExclusively())
+        throw new IllegalMonitorStateException();
+    // firstWaiter 肯定是最早开始等待的
+    Node first = firstWaiter;
+    // 如果不为空就唤醒
+    if (first != null)
+        doSignal(first);
+}
+/**
+ * Removes and transfers nodes until hit non-cancelled one or
+ * null. Split out from signal in part to encourage compilers
+ * to inline the case of no waiters.
+ * @param first (non-null) the first node on condition queue
+ */
+private void doSignal(Node first) {
+    do {
+        // 因为要去唤醒 first 节点了，firstWaiter 需要再从后面找一个
+        // 并且判断是否为空，如果是空的话就直接可以把 lastWaiter 设置成空了
+        if ( (firstWaiter = first.nextWaiter) == null)
+            lastWaiter = null;
+        //  first 不需要继续保存后面的 waiter 了，因为 firstWaiter 已经是 first 的后置节点了
+        first.nextWaiter = null;
+    // 如果 first 节点转移不成功，并且 firstWaiter 节点不为空，则继续进入循环
+    } while (!transferForSignal(first) &&
+             (first = firstWaiter) != null);
+}
+/**
+ * Transfers a node from a condition queue onto sync queue.
+ * Returns true if successful.
+ * @param node the node
+ * @return true if successfully transferred (else the node was
+ * cancelled before signal)
+ */
+final boolean transferForSignal(Node node) {
+    /*
+     * If cannot change waitStatus, the node has been cancelled.
+     */
+    // 如果状态已经不是 CONDITION 就不会设置成功，返回 false
+    if (!compareAndSetWaitStatus(node, Node.CONDITION, 0))
+        return false;
+    /*
+     * Splice onto queue and try to set waitStatus of predecessor to
+     * indicate that thread is (probably) waiting. If cancelled or
+     * attempt to set waitStatus fails, wake up to resync (in which
+     * case the waitStatus can be transiently and harmlessly wrong).
+     */
+    // 调用跟aqs 第一篇中一样的 enq 方法进入阻塞队列，返回入队后的前一节点
+    Node p = enq(node);
+    int ws = p.waitStatus;
+    // 将前置节点状态设置成SIGNAL，表示后面有节点在等了
+    if (ws > 0 || !compareAndSetWaitStatus(p, ws, Node.SIGNAL))
+        LockSupport.unpark(node.thread);
+    // 返回 true，上一个方法的循环就退出了
+    return true;
+}

    这里其实就是把 condition 等待队列的第一个未取消的节点入队到阻塞队列去争锁

    附录

    synchronized 版的 BoundedBuffer

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    /*
      File: BoundedBuffer.java

      Originally written by Doug Lea and released into the public domain.
      This may be used for any purposes whatsoever without acknowledgment.
      Thanks for the assistance and support of Sun Microsystems Labs,
      and everyone contributing, testing, and using this code.

      History:
      Date       Who                What
      11Jun1998  dl               Create public version
      17Jul1998  dl               Simplified by eliminating wait counts
      25aug1998  dl               added peek
       5May1999  dl               replace % with conditional (slightly faster)
    */

    package EDU.oswego.cs.dl.util.concurrent;

    /**
     * Efficient array-based bounded buffer class.
     * Adapted from CPJ, chapter 8, which describes design.
     * <p>[<a href="http://gee.cs.oswego.edu/dl/classes/EDU/oswego/cs/dl/util/concurrent/intro.html"> Introduction to this package. </a>] <p>
     **/

    public class BoundedBuffer implements BoundedChannel {

      protected final Object[]  array_;      // the elements

      protected int takePtr_ = 0;            // circular indices
      protected int putPtr_ = 0;       

      protected int usedSlots_ = 0;          // length
      protected int emptySlots_;             // capacity - length

      /**
       * Helper monitor to handle puts. 
       **/
      protected final Object putMonitor_ = new Object();

      /**
       * Create a BoundedBuffer with the given capacity.
       * @exception IllegalArgumentException if capacity less or equal to zero
       **/
      public BoundedBuffer(int capacity) throws IllegalArgumentException {
        if (capacity <= 0) throw new IllegalArgumentException();
        array_ = new Object[capacity];
        emptySlots_ = capacity;
      }

      /**
       * Create a buffer with the current default capacity
       **/

      public BoundedBuffer() { 
        this(DefaultChannelCapacity.get()); 
      }

      /** 
       * Return the number of elements in the buffer.
       * This is only a snapshot value, that may change
       * immediately after returning.
       **/
      public synchronized int size() { return usedSlots_; }

      public int capacity() { return array_.length; }

      protected void incEmptySlots() {
        synchronized(putMonitor_) {
          ++emptySlots_;
          putMonitor_.notify();
        }
      }

      protected synchronized void incUsedSlots() {
        ++usedSlots_;
        notify();
      }

      protected final void insert(Object x) { // mechanics of put
        --emptySlots_;
        array_[putPtr_] = x;
        if (++putPtr_ >= array_.length) putPtr_ = 0;
      }

      protected final Object extract() { // mechanics of take
        --usedSlots_;
        Object old = array_[takePtr_];
        array_[takePtr_] = null;
        if (++takePtr_ >= array_.length) takePtr_ = 0;
        return old;
      }

      public Object peek() {
        synchronized(this) {
          if (usedSlots_ > 0)
            return array_[takePtr_];
          else
            return null;
        }
      }


      public void put(Object x) throws InterruptedException {
        if (x == null) throw new IllegalArgumentException();
        if (Thread.interrupted()) throw new InterruptedException();

        synchronized(putMonitor_) {
          while (emptySlots_ <= 0) {
    	try { putMonitor_.wait(); }
            catch (InterruptedException ex) {
              putMonitor_.notify();
              throw ex;
            }
          }
          insert(x);
        }
        incUsedSlots();
      }

      public boolean offer(Object x, long msecs) throws InterruptedException {
        if (x == null) throw new IllegalArgumentException();
        if (Thread.interrupted()) throw new InterruptedException();

        synchronized(putMonitor_) {
          long start = (msecs <= 0)? 0 : System.currentTimeMillis();
          long waitTime = msecs;
          while (emptySlots_ <= 0) {
            if (waitTime <= 0) return false;
    	try { putMonitor_.wait(waitTime); }
            catch (InterruptedException ex) {
              putMonitor_.notify();
              throw ex;
            }
            waitTime = msecs - (System.currentTimeMillis() - start);
          }
          insert(x);
        }
        incUsedSlots();
        return true;
      }



      public  Object take() throws InterruptedException { 
        if (Thread.interrupted()) throw new InterruptedException();
        Object old = null; 
        synchronized(this) { 
          while (usedSlots_ <= 0) {
            try { wait(); }
            catch (InterruptedException ex) {
              notify();
              throw ex; 
            }
          }
          old = extract();
        }
        incEmptySlots();
        return old;
      }

      public  Object poll(long msecs) throws InterruptedException { 
        if (Thread.interrupted()) throw new InterruptedException();
        Object old = null; 
        synchronized(this) { 
          long start = (msecs <= 0)? 0 : System.currentTimeMillis();
          long waitTime = msecs;
          
          while (usedSlots_ <= 0) {
            if (waitTime <= 0) return null;
            try { wait(waitTime); }
            catch (InterruptedException ex) {
              notify();
              throw ex; 
            }
            waitTime = msecs - (System.currentTimeMillis() - start);

          }
          old = extract();
        }
        incEmptySlots();
        return old;
      }

    }
    +
    /*
+  File: BoundedBuffer.java
+
+  Originally written by Doug Lea and released into the public domain.
+  This may be used for any purposes whatsoever without acknowledgment.
+  Thanks for the assistance and support of Sun Microsystems Labs,
+  and everyone contributing, testing, and using this code.
+
+  History:
+  Date       Who                What
+  11Jun1998  dl               Create public version
+  17Jul1998  dl               Simplified by eliminating wait counts
+  25aug1998  dl               added peek
+   5May1999  dl               replace % with conditional (slightly faster)
+*/
+
+package EDU.oswego.cs.dl.util.concurrent;
+
+/**
+ * Efficient array-based bounded buffer class.
+ * Adapted from CPJ, chapter 8, which describes design.
+ * <p>[<a href="http://gee.cs.oswego.edu/dl/classes/EDU/oswego/cs/dl/util/concurrent/intro.html"> Introduction to this package. </a>] <p>
+ **/
+
+public class BoundedBuffer implements BoundedChannel {
+
+  protected final Object[]  array_;      // the elements
+
+  protected int takePtr_ = 0;            // circular indices
+  protected int putPtr_ = 0;       
+
+  protected int usedSlots_ = 0;          // length
+  protected int emptySlots_;             // capacity - length
+
+  /**
+   * Helper monitor to handle puts. 
+   **/
+  protected final Object putMonitor_ = new Object();
+
+  /**
+   * Create a BoundedBuffer with the given capacity.
+   * @exception IllegalArgumentException if capacity less or equal to zero
+   **/
+  public BoundedBuffer(int capacity) throws IllegalArgumentException {
+    if (capacity <= 0) throw new IllegalArgumentException();
+    array_ = new Object[capacity];
+    emptySlots_ = capacity;
+  }
+
+  /**
+   * Create a buffer with the current default capacity
+   **/
+
+  public BoundedBuffer() { 
+    this(DefaultChannelCapacity.get()); 
+  }
+
+  /** 
+   * Return the number of elements in the buffer.
+   * This is only a snapshot value, that may change
+   * immediately after returning.
+   **/
+  public synchronized int size() { return usedSlots_; }
+
+  public int capacity() { return array_.length; }
+
+  protected void incEmptySlots() {
+    synchronized(putMonitor_) {
+      ++emptySlots_;
+      putMonitor_.notify();
+    }
+  }
+
+  protected synchronized void incUsedSlots() {
+    ++usedSlots_;
+    notify();
+  }
+
+  protected final void insert(Object x) { // mechanics of put
+    --emptySlots_;
+    array_[putPtr_] = x;
+    if (++putPtr_ >= array_.length) putPtr_ = 0;
+  }
+
+  protected final Object extract() { // mechanics of take
+    --usedSlots_;
+    Object old = array_[takePtr_];
+    array_[takePtr_] = null;
+    if (++takePtr_ >= array_.length) takePtr_ = 0;
+    return old;
+  }
+
+  public Object peek() {
+    synchronized(this) {
+      if (usedSlots_ > 0)
+        return array_[takePtr_];
+      else
+        return null;
+    }
+  }
+
+
+  public void put(Object x) throws InterruptedException {
+    if (x == null) throw new IllegalArgumentException();
+    if (Thread.interrupted()) throw new InterruptedException();
+
+    synchronized(putMonitor_) {
+      while (emptySlots_ <= 0) {
+	try { putMonitor_.wait(); }
+        catch (InterruptedException ex) {
+          putMonitor_.notify();
+          throw ex;
+        }
+      }
+      insert(x);
+    }
+    incUsedSlots();
+  }
+
+  public boolean offer(Object x, long msecs) throws InterruptedException {
+    if (x == null) throw new IllegalArgumentException();
+    if (Thread.interrupted()) throw new InterruptedException();
+
+    synchronized(putMonitor_) {
+      long start = (msecs <= 0)? 0 : System.currentTimeMillis();
+      long waitTime = msecs;
+      while (emptySlots_ <= 0) {
+        if (waitTime <= 0) return false;
+	try { putMonitor_.wait(waitTime); }
+        catch (InterruptedException ex) {
+          putMonitor_.notify();
+          throw ex;
+        }
+        waitTime = msecs - (System.currentTimeMillis() - start);
+      }
+      insert(x);
+    }
+    incUsedSlots();
+    return true;
+  }
+
+
+
+  public  Object take() throws InterruptedException { 
+    if (Thread.interrupted()) throw new InterruptedException();
+    Object old = null; 
+    synchronized(this) { 
+      while (usedSlots_ <= 0) {
+        try { wait(); }
+        catch (InterruptedException ex) {
+          notify();
+          throw ex; 
+        }
+      }
+      old = extract();
+    }
+    incEmptySlots();
+    return old;
+  }
+
+  public  Object poll(long msecs) throws InterruptedException { 
+    if (Thread.interrupted()) throw new InterruptedException();
+    Object old = null; 
+    synchronized(this) { 
+      long start = (msecs <= 0)? 0 : System.currentTimeMillis();
+      long waitTime = msecs;
+      
+      while (usedSlots_ <= 0) {
+        if (waitTime <= 0) return null;
+        try { wait(waitTime); }
+        catch (InterruptedException ex) {
+          notify();
+          throw ex; 
+        }
+        waitTime = msecs - (System.currentTimeMillis() - start);
+
+      }
+      old = extract();
+    }
+    incEmptySlots();
+    return old;
+  }
+
+}
+
    @@ -328,13 +785,13 @@
    AbstractQueuedSynchronizer
  • -
    Leetcode 121 买卖股票的最佳时机(Best Time to Buy and Sell Stock) 题解分析
    +
    Leetcode 104 二叉树的最大深度(Maximum Depth of Binary Tree) 题解分析
  • -
    Leetcode 124 二叉树中的最大路径和(Binary Tree Maximum Path Sum) 题解分析
    +
    Leetcode 105 从前序与中序遍历序列构造二叉树(Construct Binary Tree from Preorder and Inorder Traversal) 题解分析
  • -
    Leetcode 105 从前序与中序遍历序列构造二叉树(Construct Binary Tree from Preorder and Inorder Traversal) 题解分析
    +
    Leetcode 124 二叉树中的最大路径和(Binary Tree Maximum Path Sum) 题解分析
    • @@ -467,7 +924,7 @@
    -
    1. 1. signal
    2. 2. 附录
    +
    1. 1. signal
    2. 2. 附录
    diff --git a/2021/02/28/闲聊下乘公交的用户体验/index.html b/2021/02/28/闲聊下乘公交的用户体验/index.html index 668e0fa7c0..f5745c92f1 100644 --- a/2021/02/28/闲聊下乘公交的用户体验/index.html +++ b/2021/02/28/闲聊下乘公交的用户体验/index.html @@ -4,7 +4,7 @@ - + @@ -32,20 +32,20 @@ + - + - - + @@ -311,10 +311,10 @@
    聊聊厦门旅游的好与不好
  • -
    周末我在老丈人家打了天小工
    +
    在老丈人家的小工记五
  • -
    从清华美院学姐聊聊我们身边的恶人
    +
    2020年中总结
    • diff --git a/2021/03/07/《垃圾回收算法手册读书》笔记之整理算法/index.html b/2021/03/07/《垃圾回收算法手册读书》笔记之整理算法/index.html index 50cbbd5638..2c6d83f33f 100644 --- a/2021/03/07/《垃圾回收算法手册读书》笔记之整理算法/index.html +++ b/2021/03/07/《垃圾回收算法手册读书》笔记之整理算法/index.html @@ -4,7 +4,7 @@ - + @@ -32,11 +32,12 @@ + - + @@ -294,10 +295,10 @@

    最近看了下这本垃圾回收算法手册，看到了第三章的标记-整理回收算法，做个简单的读书笔记

    -

    双指针整理算法

    对于一块待整理区域，通过两个指针，free 在区域的起始端，scan 指针在区域的末端，free 指针从前往后知道找到空闲区域，scan 从后往前一直找到存活对象，当 free 指针未与 scan 指针交叉时，会给 scan 位置的对象特定位置标记上 free 的地址，即将要转移的地址，不过这里有个限制，这种整理算法一般会用于对象大小统一的情况，否则 free 指针扫描时还需要匹配scan 指针扫描到的存活对象的大小。

    +

    双指针整理算法

    对于一块待整理区域，通过两个指针，free 在区域的起始端，scan 指针在区域的末端，free 指针从前往后知道找到空闲区域，scan 从后往前一直找到存活对象，当 free 指针未与 scan 指针交叉时，会给 scan 位置的对象特定位置标记上 free 的地址，即将要转移的地址，不过这里有个限制，这种整理算法一般会用于对象大小统一的情况，否则 free 指针扫描时还需要匹配scan 指针扫描到的存活对象的大小。

    Lisp 2 整理算法

    需要三次完整遍历堆区域
    第一遍是遍历后将计算出所有对象的最终地址（转发地址）
    第二遍是使用转发地址更新赋值器线程根以及被标记对象中的引用，该操作将确保它们指向对象的新位置
    第三次遍历是relocate最终将存活对象移动到其新的目标位置

    -

    引线整理算法

    这个真的长见识了，

    可以看到，原来是 A，B，C 对象引用了 N，这里会在第一次遍历的时候把这种引用反过来，让 N 的对象头部保存下 A 的地址，表示这类引用，然后在遍历到 B 的时候在链起来，到最后就会把所有引用了 N 对象的所有对象通过引线链起来，在第二次遍历的时候就把更新A，B，C 对象引用的 N 地址，并且移动 N 对象

    -

    单次遍历算法

    这个一直提到过位图的实现方式，

    可以看到在第一步会先通过位图标记，标记的方式是位图的每一位对应的堆内存的一个字（这里可能指的是 byte 吧），然后将一个存活对象的内存区域的第一个字跟最后一个字标记，这里如果在通过普通的方式就还需要一个地方在存转发地址，但是因为具体的位置可以通过位图算出来，也就不需要额外记录了

    +

    引线整理算法

    这个真的长见识了，

    可以看到，原来是 A，B，C 对象引用了 N，这里会在第一次遍历的时候把这种引用反过来，让 N 的对象头部保存下 A 的地址，表示这类引用，然后在遍历到 B 的时候在链起来，到最后就会把所有引用了 N 对象的所有对象通过引线链起来，在第二次遍历的时候就把更新A，B，C 对象引用的 N 地址，并且移动 N 对象

    +

    单次遍历算法

    这个一直提到过位图的实现方式，

    可以看到在第一步会先通过位图标记，标记的方式是位图的每一位对应的堆内存的一个字（这里可能指的是 byte 吧），然后将一个存活对象的内存区域的第一个字跟最后一个字标记，这里如果在通过普通的方式就还需要一个地方在存转发地址，但是因为具体的位置可以通过位图算出来，也就不需要额外记录了

    @@ -308,19 +309,19 @@
    Related Posts
    @@ -449,7 +450,7 @@
    -
    1. 1. 双指针整理算法
    2. 2. Lisp 2 整理算法
    3. 3. 引线整理算法
    4. 4. 单次遍历算法
    +
    1. 1. 双指针整理算法
    2. 2. Lisp 2 整理算法
    3. 3. 引线整理算法
    4. 4. 单次遍历算法
    diff --git a/2021/03/14/Leetcode-121-买卖股票的最佳时机-Best-Time-to-Buy-and-Sell-Stock-题解分析/index.html b/2021/03/14/Leetcode-121-买卖股票的最佳时机-Best-Time-to-Buy-and-Sell-Stock-题解分析/index.html index 83e2a794be..1bca9682e9 100644 --- a/2021/03/14/Leetcode-121-买卖股票的最佳时机-Best-Time-to-Buy-and-Sell-Stock-题解分析/index.html +++ b/2021/03/14/Leetcode-121-买卖股票的最佳时机-Best-Time-to-Buy-and-Sell-Stock-题解分析/index.html @@ -4,7 +4,7 @@ - + @@ -32,14 +32,14 @@ + - + - - + @@ -246,11 +246,11 @@     , - + , - + , @@ -300,11 +300,32 @@

    题目介绍

    You are given an array prices where prices[i] is the price of a given stock on the ith day.

    You want to maximize your profit by choosing a single day to buy one stock and choosing a different day in the future to sell that stock.

    Return the maximum profit you can achieve from this transaction. If you cannot achieve any profit, return 0.

    -

    给定一个数组 prices ，它的第 i 个元素 prices[i] 表示一支给定股票第 i 天的价格。

    +

    给定一个数组 prices ，它的第 i 个元素 prices[i] 表示一支给定股票第 i 天的价格。

    你只能选择 某一天 买入这只股票，并选择在 未来的某一个不同的日子 卖出该股票。设计一个算法来计算你所能获取的最大利润。

    返回你可以从这笔交易中获取的最大利润。如果你不能获取任何利润，返回 0 。

    简单分析

    其实这个跟二叉树的最长路径和有点类似，需要找到整体的最大收益，但是在迭代过程中需要一个当前的值

    -
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    int maxSofar = 0;
    public int maxProfit(int[] prices) {
        if (prices.length <= 1) {
            return 0;
        }
        int maxIn = prices[0];
        int maxOut = prices[0];
        for (int i = 1; i < prices.length; i++) {
            if (maxIn > prices[i]) {
                // 当循环当前值小于之前的买入值时就当成买入值，同时卖出也要更新
                maxIn = prices[i];
                maxOut = prices[i];
            }
            if (prices[i] > maxOut) {
                // 表示一个可卖出点，即比买入值高时
                maxOut = prices[i];
                // 需要设置一个历史值
                maxSofar = Math.max(maxSofar, maxOut - maxIn);
            }
        }
        return maxSofar;
    }
    +
    int maxSofar = 0;
+public int maxProfit(int[] prices) {
+    if (prices.length <= 1) {
+        return 0;
+    }
+    int maxIn = prices[0];
+    int maxOut = prices[0];
+    for (int i = 1; i < prices.length; i++) {
+        if (maxIn > prices[i]) {
+            // 当循环当前值小于之前的买入值时就当成买入值，同时卖出也要更新
+            maxIn = prices[i];
+            maxOut = prices[i];
+        }
+        if (prices[i] > maxOut) {
+            // 表示一个可卖出点，即比买入值高时
+            maxOut = prices[i];
+            // 需要设置一个历史值
+            maxSofar = Math.max(maxSofar, maxOut - maxIn);
+        }
+    }
+    return maxSofar;
+}

    总结下

    一开始看到 easy 就觉得是很简单，就没有 maxSofar ，但是一提交就出现问题了
    对于[2, 4, 1]这种就会变成 0，所以还是需要一个历史值来存放历史最大值，这题有点动态规划的意思

    @@ -317,19 +338,19 @@
    Related Posts
    @@ -457,7 +478,7 @@
    -
    1. 1. 题目介绍
    2. 2. 简单分析
    3. 3. 总结下
    +
    1. 1. 题目介绍
    2. 2. 简单分析
    3. 3. 总结下
    diff --git a/2021/03/21/关于公共交通再吐个槽/index.html b/2021/03/21/关于公共交通再吐个槽/index.html index 1fc8d0108a..a53e092b8c 100644 --- a/2021/03/21/关于公共交通再吐个槽/index.html +++ b/2021/03/21/关于公共交通再吐个槽/index.html @@ -4,7 +4,7 @@ - + @@ -32,13 +32,13 @@ + - + - @@ -311,10 +311,10 @@
    聊聊厦门旅游的好与不好
  • -
    周末我在老丈人家打了天小工
    +
    从丁仲礼被美国制裁聊点啥
  • -
    从清华美院学姐聊聊我们身边的恶人
    +
    周末我在老丈人家打了天小工
    • diff --git a/2021/03/28/聊聊-Linux-下的-top-命令/index.html b/2021/03/28/聊聊-Linux-下的-top-命令/index.html index 76ccd7d517..954d5a54ba 100644 --- a/2021/03/28/聊聊-Linux-下的-top-命令/index.html +++ b/2021/03/28/聊聊-Linux-下的-top-命令/index.html @@ -4,7 +4,7 @@ - + @@ -26,23 +26,22 @@ var CONFIG = {"hostname":"nicksxs.me","root":"/","scheme":"Pisces","version":"7.8.0","exturl":false,"sidebar":{"position":"left","display":"post","padding":18,"offset":12,"onmobile":false},"copycode":{"enable":true,"show_result":false,"style":null},"back2top":{"enable":true,"sidebar":false,"scrollpercent":false},"bookmark":{"enable":false,"color":"#222","save":"auto"},"fancybox":true,"mediumzoom":false,"lazyload":true,"pangu":false,"comments":{"style":"tabs","active":null,"storage":true,"lazyload":false,"nav":null},"algolia":{"hits":{"per_page":10},"labels":{"input_placeholder":"Search for Posts","hits_empty":"We didn't find any results for the search: ${query}","hits_stats":"${hits} results found in ${time} ms"}},"localsearch":{"enable":false,"trigger":"auto","top_n_per_article":1,"unescape":false,"preload":false},"motion":{"enable":true,"async":false,"transition":{"post_block":"fadeIn","post_header":"slideDownIn","post_body":"slideDownIn","coll_header":"slideLeftIn","sidebar":"slideUpIn"}}}; - + - + + - + - - + - - + @@ -306,9 +305,33 @@

    top 命令在日常的 Linux 使用中，特别是做一些服务器的简单状态查看，排查故障都起了比较大的作用，但是由于这个命令看到的东西比较多，一般只会看部分，或者说像我这样就会比较片面地看一些信息，比如默认是进程维度的，可以在启动命令的时候加-H进入线程模式

    -
    1
    2
    3
    -H  :Threads-mode operation
                Instructs top to display individual threads.  Without this command-line option a summation of all threads in each process  is  shown.   Later
                this can be changed with the `H' interactive command.
    -

    这样就能用在 Java 中去 jstack 中找到对应的线程
    其实还有比较重要的两个操作，
    一个是在 top 启动状态下，按c键，这样能把比如说是一个 Java 进程，具体的进程命令显示出来
    像这样
    执行前是这样

    执行后是这样

    第二个就是排序了

    -
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    SORTING of task window

              For  compatibility,  this top supports most of the former top sort keys.  Since this is primarily a service to former top users, these commands
              do not appear on any help screen.
                    command   sorted-field                  supported
                    A         start time (non-display)      No
                    M         %MEM                          Yes
                    N         PID                           Yes
                    P         %CPU                          Yes
                    T         TIME+                         Yes

              Before using any of the following sort provisions, top suggests that you temporarily turn on column highlighting using the `x' interactive com‐
              mand.  That will help ensure that the actual sort environment matches your intent.

              The following interactive commands will only be honored when the current sort field is visible.  The sort field might not be visible because:
                    1) there is insufficient Screen Width
                    2) the `f' interactive command turned it Off

                 <  :Move-Sort-Field-Left
                     Moves the sort column to the left unless the current sort field is the first field being displayed.

                 >  :Move-Sort-Field-Right
                     Moves the sort column to the right unless the current sort field is the last field being displayed.
    +
    -H  :Threads-mode operation
+            Instructs top to display individual threads.  Without this command-line option a summation of all threads in each process  is  shown.   Later
+            this can be changed with the `H' interactive command.
    +

    这样就能用在 Java 中去 jstack 中找到对应的线程
    其实还有比较重要的两个操作，
    一个是在 top 启动状态下，按c键，这样能把比如说是一个 Java 进程，具体的进程命令显示出来
    像这样
    执行前是这样

    执行后是这样

    第二个就是排序了

    +
    SORTING of task window
+
+          For  compatibility,  this top supports most of the former top sort keys.  Since this is primarily a service to former top users, these commands
+          do not appear on any help screen.
+                command   sorted-field                  supported
+                A         start time (non-display)      No
+                M         %MEM                          Yes
+                N         PID                           Yes
+                P         %CPU                          Yes
+                T         TIME+                         Yes
+
+          Before using any of the following sort provisions, top suggests that you temporarily turn on column highlighting using the `x' interactive com‐
+          mand.  That will help ensure that the actual sort environment matches your intent.
+
+          The following interactive commands will only be honored when the current sort field is visible.  The sort field might not be visible because:
+                1) there is insufficient Screen Width
+                2) the `f' interactive command turned it Off
+
+             <  :Move-Sort-Field-Left
+                 Moves the sort column to the left unless the current sort field is the first field being displayed.
+
+             >  :Move-Sort-Field-Right
+                 Moves the sort column to the right unless the current sort field is the last field being displayed.

    查看 man page 可以找到这一段，其实一般 man page 都是最细致的，只不过因为太多了，有时候懒得看，这里可以通过大写 M 和大写 P 分别按内存和 CPU 排序，下面还有两个小技巧，通过按 x 可以将当前活跃的排序列用不同颜色标出来，然后可以通过<和>直接左右移动排序列

    diff --git a/2021/03/31/2020-年终总结/index.html b/2021/03/31/2020-年终总结/index.html index 61f039e026..bcffd15877 100644 --- a/2021/03/31/2020-年终总结/index.html +++ b/2021/03/31/2020-年终总结/index.html @@ -4,7 +4,7 @@ - + @@ -32,15 +32,13 @@ + - + - - - - + @@ -237,13 +235,6 @@     - - - - - Edited on - - @@ -311,7 +302,7 @@

    拖更原因

    这篇年终总结本来应该在农历过完年就出来的，结果是对没有受疫情影响的春节放假时间空闲情况预估太良好，虽然公司调了几天假，但是因为春节期间疫情状况比较好，本来酒店都不让接待聚餐什么的，后来统统放开，结果就是从初一到初六每天要不就是去亲戚家，要不就是去酒店饭店吃饭，计划很丰满，现实很骨感，时间感觉一下就没了，然后年后感觉有点犯懒了，所以才拖到现在。

    生活-健身跑步

    去年（19 年）的时候跑步突破了 300 公里，然后20 年给自己定了个 400 公里的目标，结果意料之中的没成功，原因可能疫情算一点吧，后面买了跑步机之后，基本周末回家都能跑一下，但是最后还是只跑了300 多公里，总的keep 记录跑量也没超过 1000 公里，所以跑步这个目标还是没成功的，不过还算是比去年多跑一点，这样也算后面好突破点，后面的目标就不定的太高了，每年能比前一年多一点就好，其实跑步已经从一种减肥方式变成一种习惯了，一周一次的跑步已经比较难有效减重了，但是对于保持精力和身体状态还是很有效和重要的，只是对于目前的体重还是要多减下去一些跑步才好，太重了对膝盖负担太大了，可惜还是时间呐，游泳骑车什么的都需要更苛刻的条件和时间，饮食呢控制起来比较难（贪吃
    终于在 3 月底之前跑到了 1000 公里，迟了三个月，不过也总算达到了，只是体重控制还是不行，有试着走走楼梯，但是感觉对膝盖负担比较大，得再想想用什么方式

    -

    +

    技术成长

    一直提不起笔来写这篇年终总结还有个比较大的原因是觉得20 年的成长不如预期，大小目标都没怎么完成，比如深入了解 jvm，是想能有些深入的见解，而不再是某些点的比较片面的理解，系统性的归纳总结也比较少，每个方向或多或少有些看法和理解，但是不全面，一些东西看过了也会忘记，需要温故而知新，比如 AQS 的内容，第一次读其实理解比较浅，后面就强迫自己去读，去写，才有了一些比之前更深入的理解，因为很多文章都是带有作者思路的引导，适不适合自己都要看是否能从他的思路把它看懂，有些就差别很大，这个跟看书也一样，有些书大众一致推荐，一般情况下大多是经典的好的，但是也有可能是不太适合自己的，可能有时候机缘巧合看到的反而让人茅塞顿开，在 todo 里已经积攒了好多的点和面需要去学习实践，一方面是自己懒，一方面是时间也相对偏少，看看 21 年能不能有所提升，加强“时间管理”，哈哈

    技术上主要是看了 mysql 的 mvcc 相关内容，rocketmq 的，redis 的代码，还有 mybatis 等，其实每一个都能写很多，也有很多值得学习的，需要全面系统学习，之前想好好画一个思维导图，将整个技术体系都梳理下，还只做了一点点，方式也有点问题，应该从大到小，而不是深度优先，细节有很多，每一个方面都有自己比较熟悉擅长的，也有不太了解的，可以做一个评分，这个也是亟待改善的，希望今年能完成。

    博客

    博客方面 20 年一年整是写了 53 篇，差不多是一周一篇的节奏，这个还是不错的，虽然博客质量参差不齐，但是这个更新频率还是比较好的，并且也定了个潜规则，可以一周技术一周生活，这样能缓解水文的频率，提高些技术文章的质量，虽然结果并没有好多少，不过感觉还是可以这么坚持的，能提高一些技术文章的质量那就更好了

    @@ -325,19 +316,19 @@
    Related Posts
    @@ -466,7 +457,7 @@
    -
    1. 1. 拖更原因
    2. 2. 生活-健身跑步
    3. 3. 技术成长
    4. 4. 博客
    +
    1. 1. 拖更原因
    2. 2. 生活-健身跑步
    3. 3. 技术成长
    4. 4. 博客
    diff --git a/2021/04/04/聊聊-dubbo-的线程池/index.html b/2021/04/04/聊聊-dubbo-的线程池/index.html index 47a69ea16d..d5bd2b45ac 100644 --- a/2021/04/04/聊聊-dubbo-的线程池/index.html +++ b/2021/04/04/聊聊-dubbo-的线程池/index.html @@ -4,7 +4,7 @@ - + @@ -26,19 +26,20 @@ var CONFIG = {"hostname":"nicksxs.me","root":"/","scheme":"Pisces","version":"7.8.0","exturl":false,"sidebar":{"position":"left","display":"post","padding":18,"offset":12,"onmobile":false},"copycode":{"enable":true,"show_result":false,"style":null},"back2top":{"enable":true,"sidebar":false,"scrollpercent":false},"bookmark":{"enable":false,"color":"#222","save":"auto"},"fancybox":true,"mediumzoom":false,"lazyload":true,"pangu":false,"comments":{"style":"tabs","active":null,"storage":true,"lazyload":false,"nav":null},"algolia":{"hits":{"per_page":10},"labels":{"input_placeholder":"Search for Posts","hits_empty":"We didn't find any results for the search: ${query}","hits_stats":"${hits} results found in ${time} ms"}},"localsearch":{"enable":false,"trigger":"auto","top_n_per_article":1,"unescape":false,"preload":false},"motion":{"enable":true,"async":false,"transition":{"post_block":"fadeIn","post_header":"slideDownIn","post_body":"slideDownIn","coll_header":"slideLeftIn","sidebar":"slideUpIn"}}}; - + - + + - + + - @@ -302,15 +303,43 @@
    -

    之前没注意到这一块，只是比较模糊的印象 dubbo 自己基于 ThreadPoolExecutor 定义了几个线程池，但是没具体看过，主要是觉得就是为了避免使用 jdk 自带的那几个(java.util.concurrent.Executors)，防止出现那些问题
    看下代码目录主要是这几个

    +

    之前没注意到这一块，只是比较模糊的印象 dubbo 自己基于 ThreadPoolExecutor 定义了几个线程池，但是没具体看过，主要是觉得就是为了避免使用 jdk 自带的那几个(java.util.concurrent.Executors)，防止出现那些问题
    看下代码目录主要是这几个

      -
    • FixedThreadPool：创建一个复用固定个数线程的线程池。
      简单看下代码
      1
      2
      3
      4
      5
      6
      public Executor getExecutor(URL url) {
              String name = url.getParameter("threadname", "Dubbo");
              int threads = url.getParameter("threads", 200);
              int queues = url.getParameter("queues", 0);
              return new ThreadPoolExecutor(threads, threads, 0L, TimeUnit.MILLISECONDS, (BlockingQueue)(queues == 0 ? new SynchronousQueue() : (queues < 0 ? new LinkedBlockingQueue() : new LinkedBlockingQueue(queues))), new NamedThreadFactory(name, true), new AbortPolicyWithReport(name, url));
          }
      +
    • FixedThreadPool：创建一个复用固定个数线程的线程池。
      简单看下代码
      public Executor getExecutor(URL url) {
+        String name = url.getParameter("threadname", "Dubbo");
+        int threads = url.getParameter("threads", 200);
+        int queues = url.getParameter("queues", 0);
+        return new ThreadPoolExecutor(threads, threads, 0L, TimeUnit.MILLISECONDS, (BlockingQueue)(queues == 0 ? new SynchronousQueue() : (queues < 0 ? new LinkedBlockingQueue() : new LinkedBlockingQueue(queues))), new NamedThreadFactory(name, true), new AbortPolicyWithReport(name, url));
+    }
      可以看到核心线程数跟最大线程数一致，也就是说就不会在核心线程数和最大线程数之间动态变化了
      • -
    • LimitedThreadPool：创建一个线程池，这个线程池中线程个数随着需要量动态增加，但是数量不超过配置的阈值的个数，另外空闲线程不会被回收，会一直存在。
      1
      2
      3
      4
      5
      6
      7
      public Executor getExecutor(URL url) {
              String name = url.getParameter("threadname", "Dubbo");
              int cores = url.getParameter("corethreads", 0);
              int threads = url.getParameter("threads", 200);
              int queues = url.getParameter("queues", 0);
              return new ThreadPoolExecutor(cores, threads, 9223372036854775807L, TimeUnit.MILLISECONDS, (BlockingQueue)(queues == 0 ? new SynchronousQueue() : (queues < 0 ? new LinkedBlockingQueue() : new LinkedBlockingQueue(queues))), new NamedThreadFactory(name, true), new AbortPolicyWithReport(name, url));
          }
      +
    • LimitedThreadPool：创建一个线程池，这个线程池中线程个数随着需要量动态增加，但是数量不超过配置的阈值的个数，另外空闲线程不会被回收，会一直存在。
      public Executor getExecutor(URL url) {
+        String name = url.getParameter("threadname", "Dubbo");
+        int cores = url.getParameter("corethreads", 0);
+        int threads = url.getParameter("threads", 200);
+        int queues = url.getParameter("queues", 0);
+        return new ThreadPoolExecutor(cores, threads, 9223372036854775807L, TimeUnit.MILLISECONDS, (BlockingQueue)(queues == 0 ? new SynchronousQueue() : (queues < 0 ? new LinkedBlockingQueue() : new LinkedBlockingQueue(queues))), new NamedThreadFactory(name, true), new AbortPolicyWithReport(name, url));
+    }
      这个特点主要是创建了保活时间特别长，即可以认为不会被回收了
      • -
    • EagerThreadPool ：创建一个线程池，这个线程池当所有核心线程都处于忙碌状态时候，创建新的线程来执行新任务，而不是把任务放入线程池阻塞队列。
      1
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      9
      10
      11
      public Executor getExecutor(URL url) {
              String name = url.getParameter("threadname", "Dubbo");
              int cores = url.getParameter("corethreads", 0);
              int threads = url.getParameter("threads", 2147483647);
              int queues = url.getParameter("queues", 0);
              int alive = url.getParameter("alive", 60000);
              TaskQueue<Runnable> taskQueue = new TaskQueue(queues <= 0 ? 1 : queues);
              EagerThreadPoolExecutor executor = new EagerThreadPoolExecutor(cores, threads, (long)alive, TimeUnit.MILLISECONDS, taskQueue, new NamedThreadFactory(name, true), new AbortPolicyWithReport(name, url));
              taskQueue.setExecutor(executor);
              return executor;
          }
      +
    • EagerThreadPool ：创建一个线程池，这个线程池当所有核心线程都处于忙碌状态时候，创建新的线程来执行新任务，而不是把任务放入线程池阻塞队列。
      public Executor getExecutor(URL url) {
+        String name = url.getParameter("threadname", "Dubbo");
+        int cores = url.getParameter("corethreads", 0);
+        int threads = url.getParameter("threads", 2147483647);
+        int queues = url.getParameter("queues", 0);
+        int alive = url.getParameter("alive", 60000);
+        TaskQueue<Runnable> taskQueue = new TaskQueue(queues <= 0 ? 1 : queues);
+        EagerThreadPoolExecutor executor = new EagerThreadPoolExecutor(cores, threads, (long)alive, TimeUnit.MILLISECONDS, taskQueue, new NamedThreadFactory(name, true), new AbortPolicyWithReport(name, url));
+        taskQueue.setExecutor(executor);
+        return executor;
+    }
      这个是改动最多的一个了，因为需要实现这个机制，有兴趣的可以详细看下
      • -
    • CachedThreadPool： 创建一个自适应线程池，当线程处于空闲1分钟时候，线程会被回收，当有新请求到来时候会创建新线程
      1
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      8
      public Executor getExecutor(URL url) {
              String name = url.getParameter("threadname", "Dubbo");
              int cores = url.getParameter("corethreads", 0);
              int threads = url.getParameter("threads", 2147483647);
              int queues = url.getParameter("queues", 0);
              int alive = url.getParameter("alive", 60000);
              return new ThreadPoolExecutor(cores, threads, (long)alive, TimeUnit.MILLISECONDS, (BlockingQueue)(queues == 0 ? new SynchronousQueue() : (queues < 0 ? new LinkedBlockingQueue() : new LinkedBlockingQueue(queues))), new NamedThreadFactory(name, true), new AbortPolicyWithReport(name, url));
          }
      +
    • CachedThreadPool： 创建一个自适应线程池，当线程处于空闲1分钟时候，线程会被回收，当有新请求到来时候会创建新线程
      public Executor getExecutor(URL url) {
+        String name = url.getParameter("threadname", "Dubbo");
+        int cores = url.getParameter("corethreads", 0);
+        int threads = url.getParameter("threads", 2147483647);
+        int queues = url.getParameter("queues", 0);
+        int alive = url.getParameter("alive", 60000);
+        return new ThreadPoolExecutor(cores, threads, (long)alive, TimeUnit.MILLISECONDS, (BlockingQueue)(queues == 0 ? new SynchronousQueue() : (queues < 0 ? new LinkedBlockingQueue() : new LinkedBlockingQueue(queues))), new NamedThreadFactory(name, true), new AbortPolicyWithReport(name, url));
+    }
      这里可以看到线程池的配置，核心是 0，最大线程数是 2147483647，保活时间是一分钟
      只是非常简略的介绍下，有兴趣可以自行阅读代码。
    diff --git a/2021/04/11/聊聊厦门旅游的好与不好/index.html b/2021/04/11/聊聊厦门旅游的好与不好/index.html index db84639055..311b3b4b3a 100644 --- a/2021/04/11/聊聊厦门旅游的好与不好/index.html +++ b/2021/04/11/聊聊厦门旅游的好与不好/index.html @@ -4,7 +4,7 @@ - + @@ -32,10 +32,12 @@ + - + + @@ -44,7 +46,6 @@ - @@ -318,10 +319,10 @@
    2020 年终总结
  • -
    周末我在老丈人家打了天小工
    +
    从丁仲礼被美国制裁聊点啥
  • -
    从清华美院学姐聊聊我们身边的恶人
    +
    2020年中总结
    • @@ -457,7 +458,7 @@
    -
    1. 1. 中山路
    2. 2. 鼓浪屿
    3. 3. 曾厝垵
    4. 4. 植物园
    5. 5. 灵玲马戏团
    6. 6. 总结
    +
    1. 1. 中山路
    2. 2. 鼓浪屿
    3. 3. 曾厝垵
    4. 4. 植物园
    5. 5. 灵玲马戏团
    6. 6. 总结
    diff --git a/2021/04/18/rust学习笔记-所有权二/index.html b/2021/04/18/rust学习笔记-所有权二/index.html index a921a48b9a..5a34f4a6fd 100644 --- a/2021/04/18/rust学习笔记-所有权二/index.html +++ b/2021/04/18/rust学习笔记-所有权二/index.html @@ -4,7 +4,7 @@ - + @@ -26,12 +26,13 @@ var CONFIG = {"hostname":"nicksxs.me","root":"/","scheme":"Pisces","version":"7.8.0","exturl":false,"sidebar":{"position":"left","display":"post","padding":18,"offset":12,"onmobile":false},"copycode":{"enable":true,"show_result":false,"style":null},"back2top":{"enable":true,"sidebar":false,"scrollpercent":false},"bookmark":{"enable":false,"color":"#222","save":"auto"},"fancybox":true,"mediumzoom":false,"lazyload":true,"pangu":false,"comments":{"style":"tabs","active":null,"storage":true,"lazyload":false,"nav":null},"algolia":{"hits":{"per_page":10},"labels":{"input_placeholder":"Search for Posts","hits_empty":"We didn't find any results for the search: ${query}","hits_stats":"${hits} results found in ${time} ms"}},"localsearch":{"enable":false,"trigger":"auto","top_n_per_article":1,"unescape":false,"preload":false},"motion":{"enable":true,"async":false,"transition":{"post_block":"fadeIn","post_header":"slideDownIn","post_body":"slideDownIn","coll_header":"slideLeftIn","sidebar":"slideUpIn"}}}; - + - + + @@ -39,13 +40,12 @@ - + - @@ -241,13 +241,6 @@ - - - - - Edited on - - @@ -301,24 +294,68 @@
    -

    这里需要说道函数和返回值了
    可以看书上的这个例子

    对于这种情况，当进入函数内部时，会把传入的变量的所有权转移进函数内部，如果最后还是要返回该变量，但是如果此时还要返回别的计算结果，就可能需要笨拙地使用元组

    +

    这里需要说道函数和返回值了
    可以看书上的这个例子

    对于这种情况，当进入函数内部时，会把传入的变量的所有权转移进函数内部，如果最后还是要返回该变量，但是如果此时还要返回别的计算结果，就可能需要笨拙地使用元组

    引用

    此时我们就可以用引用来解决这个问题

    -
    1
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    9
    fn main() {
        let s1 = String::from("hello");
        let len = calculate_length(&s1);

        println!("The length of '{}' is {}", s1, len);
    }
    fn calculate_length(s: &String) -> usize {
        s.len()
    }
    -

    这里的&符号就是引用的语义，它们允许你在不获得所有权的前提下使用值

    由于引用不持有值的所有权，所以当引用离开当前作用域时，它指向的值也不会被丢弃

    +
    fn main() {
+    let s1 = String::from("hello");
+    let len = calculate_length(&s1);
+
+    println!("The length of '{}' is {}", s1, len);
+}
+fn calculate_length(s: &String) -> usize {
+    s.len()
+}
    +

    这里的&符号就是引用的语义，它们允许你在不获得所有权的前提下使用值

    由于引用不持有值的所有权，所以当引用离开当前作用域时，它指向的值也不会被丢弃

    可变引用

    而当我们尝试对引用的字符串进行修改时

    -
    1
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    fn main() {
        let s1 = String::from("hello");
        change(&s1);
    }
    fn change(s: &String) {
        s.push_str(", world");
    }
    -

    就会有以下报错，

    其实也很容易发现，毕竟没有 mut 指出这是可变引用，同时需要将 s1 改成 mut 可变的

    -
    1
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    6
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    8
    9
    fn main() {
        let mut s1 = String::from("hello");
        change(&mut s1);
    }


    fn change(s: &mut String) {
        s.push_str(", world");
    }
    +
    fn main() {
+    let s1 = String::from("hello");
+    change(&s1);
+}
+fn change(s: &String) {
+    s.push_str(", world");
+}
    +

    就会有以下报错，

    其实也很容易发现，毕竟没有 mut 指出这是可变引用，同时需要将 s1 改成 mut 可变的

    +
    fn main() {
+    let mut s1 = String::from("hello");
+    change(&mut s1);
+}
+
+
+fn change(s: &mut String) {
+    s.push_str(", world");
+}

    再看一个例子

    -
    1
    2
    3
    4
    5
    fn main() {
        let mut s1 = String::from("hello");
        let r1 = &mut s1;
        let r2 = &mut s1;
    }
    +
    fn main() {
+    let mut s1 = String::from("hello");
+    let r1 = &mut s1;
+    let r2 = &mut s1;
+}

    这个例子在书里是会报错的，因为同时存在一个以上的可变引用，但是在我运行的版本里前面这段没有报错，只有当我真的要去更改的时候

    -
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    fn main() {
        let mut s1 = String::from("hello");
        let mut r1 = &mut s1;
        let mut r2 = &mut s1;
        change(&mut r1);
        change(&mut r2);
    }


    fn change(s: &mut String) {
        s.push_str(", world");
    }
    -


    这里可能就是具体版本在实现上的一个差异，我用的 rustc 是 1.44.0 版本
    其实上面的主要是由 rust 想要避免这类多重可变更导致的异常问题，总结下就是三个点

    +
    fn main() {
+    let mut s1 = String::from("hello");
+    let mut r1 = &mut s1;
+    let mut r2 = &mut s1;
+    change(&mut r1);
+    change(&mut r2);
+}
+
+
+fn change(s: &mut String) {
+    s.push_str(", world");
+}
    +


    这里可能就是具体版本在实现上的一个差异，我用的 rustc 是 1.44.0 版本
    其实上面的主要是由 rust 想要避免这类多重可变更导致的异常问题，总结下就是三个点

    • 两个或两个以上的指针同时同时访问同一空间
    • 其中至少有一个指针会想空间中写入数据
      • -
    • 没有同步数据访问的机制
      并且我们不能在拥有不可变引用的情况下创建可变引用

      悬垂引用

      还有一点需要注意的就是悬垂引用
      1
      2
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      6
      7
      8
      fn main() {
          let reference_to_nothing = dangle();
      }

      fn dangle() -> &String {
          let s = String::from("hello");
          &s
      }
      -这里可以看到其实在 dangle函数返回后，这里的 s 理论上就离开了作用域，但是由于返回了 s 的引用，在 main 函数中就会拿着这个引用，就会出现如下错误

      总结

      最后总结下
      • +
    • 没有同步数据访问的机制
      并且我们不能在拥有不可变引用的情况下创建可变引用

      悬垂引用

      还有一点需要注意的就是悬垂引用
      fn main() {
+    let reference_to_nothing = dangle();
+}
+
+fn dangle() -> &String {
+    let s = String::from("hello");
+    &s
+}
      +这里可以看到其实在 dangle函数返回后，这里的 s 理论上就离开了作用域，但是由于返回了 s 的引用，在 main 函数中就会拿着这个引用，就会出现如下错误

      总结

      最后总结下
    • 在任何一个段给定的时间里，你要么只能拥有一个可变引用，要么只能拥有任意数量的不可变引用。
    • 引用总是有效的。
    @@ -462,7 +499,7 @@
    -
    1. 1. 引用
    2. 2. 可变引用
    3. 3. 悬垂引用
    4. 4. 总结
    +
    1. 1. 引用
    2. 2. 可变引用
    3. 3. 悬垂引用
    4. 4. 总结
    diff --git a/2021/04/18/rust学习笔记/index.html b/2021/04/18/rust学习笔记/index.html index 1cb1c5e84e..e8d70138dd 100644 --- a/2021/04/18/rust学习笔记/index.html +++ b/2021/04/18/rust学习笔记/index.html @@ -4,7 +4,7 @@ - + @@ -32,6 +32,7 @@ + @@ -39,7 +40,7 @@ - + @@ -235,9 +236,8 @@ Posted on - - + @@ -296,16 +296,23 @@
    • Rust中的每一个值都有一个对应的变量作为它的所有者。
    • 在同一时间内，值有且只有一个所有者。
      • -
    • 当所有者离开自己的作用域时，它持有的值就会被释放掉。

      这里有两个重点：
      • +
    • 当所有者离开自己的作用域时，它持有的值就会被释放掉。

      这里有两个重点：
    • s 在进入作用域后才变得有效
    • 它会保持自己的有效性直到自己离开作用域为止

    然后看个案例

    -
    1
    2
    let x = 5;
    let y = x;
    +
    let x = 5;
+let y = x;

    这个其实有两种，一般可以认为比较多实现的会使用 copy on write 之类的，先让两个都指向同一个快 5 的存储，在发生变更后开始正式拷贝，但是涉及到内存处理的便利性，对于这类简单类型，可以直接拷贝
    但是对于非基础类型

    -
    1
    2
    3
    4
    let s1 = String::from("hello");
    let s2 = s1;

    println!("{}, world!", s1);
    -

    有可能认为有两种内存分布可能
    先看下 string 的内存结构

    第一种可能是

    第二种是

    我们来尝试编译下

    发现有这个错误，其实在 rust 中let y = x这个行为的实质是移动，在赋值给 y 之后 x 就无效了

    这样子就不会造成脱离作用域时，对同一块内存区域的二次释放，如果需要复制，可以使用 clone 方法

    -
    1
    2
    3
    4
    let s1 = String::from("hello");
    let s2 = s1.clone();

    println!("s1 = {}, s2 = {}", s1, s2);
    +
    let s1 = String::from("hello");
+let s2 = s1;
+
+println!("{}, world!", s1);
    +

    有可能认为有两种内存分布可能
    先看下 string 的内存结构

    第一种可能是

    第二种是

    我们来尝试编译下

    发现有这个错误，其实在 rust 中let y = x这个行为的实质是移动，在赋值给 y 之后 x 就无效了

    这样子就不会造成脱离作用域时，对同一块内存区域的二次释放，如果需要复制，可以使用 clone 方法

    +
    let s1 = String::from("hello");
+let s2 = s1.clone();
+
+println!("s1 = {}, s2 = {}", s1, s2);

    这里其实会有点疑惑，为什么前面的x, y 的行为跟 s1, s2 的不一样，其实主要是基本类型和 string 这类的不定大小的类型的内存分配方式不同，x, y这类整型可以直接确定大小，可以直接在栈上分配，而像 string 和其他的变体结构体，其大小都是不能在编译时确定，所以需要在堆上进行分配

    diff --git a/2021/05/01/Leetcode-48-旋转图像-Rotate-Image-题解分析/index.html b/2021/05/01/Leetcode-48-旋转图像-Rotate-Image-题解分析/index.html index 356c410fda..ed33fc6f29 100644 --- a/2021/05/01/Leetcode-48-旋转图像-Rotate-Image-题解分析/index.html +++ b/2021/05/01/Leetcode-48-旋转图像-Rotate-Image-题解分析/index.html @@ -4,7 +4,7 @@ - + @@ -32,15 +32,16 @@ + - + - - + + - + @@ -292,9 +293,45 @@

    题目介绍

    You are given an n x n 2D matrix representing an image, rotate the image by 90 degrees (clockwise).

    -

    You have to rotate the image in-place, which means you have to modify the input 2D matrix directly. DO NOT allocate another 2D matrix and do the rotation.

    如图，这道题以前做过，其实一看有点蒙，好像规则很容易描述，但是代码很难写，因为要类似于贪吃蛇那样，后来想着应该会有一些特殊的技巧，比如翻转等

    +

    You have to rotate the image in-place, which means you have to modify the input 2D matrix directly. DO NOT allocate another 2D matrix and do the rotation.

    如图，这道题以前做过，其实一看有点蒙，好像规则很容易描述，但是代码很难写，因为要类似于贪吃蛇那样，后来想着应该会有一些特殊的技巧，比如翻转等

    代码

    直接上码

    -
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    public void rotate(int[][] matrix) {
            // 这里真的傻了，长宽应该是一致的，所以取一次就够了
            int lengthX = matrix[0].length;
            int lengthY = matrix.length;
            int temp;
            System.out.println(lengthY - (lengthY % 2) / 2);
            // 这里除错了，应该是减掉余数再除 2
    //        for (int i = 0; i < lengthY - (lengthY % 2) / 2; i++) {
            /**
             * 1 2 3             7 8 9
             * 4 5 6     =>      4 5 6     先沿着 4 5 6 上下交换
             * 7 8 9             1 2 3
             */
            for (int i = 0; i < (lengthY - (lengthY % 2)) / 2; i++) {
                for (int j = 0; j < lengthX; j++) {
                    temp = matrix[i][j];
                    matrix[i][j] = matrix[lengthY-i-1][j];
                    matrix[lengthY-i-1][j] = temp;
                }
            }

            /**
             * 7 8 9               7 4 1
             * 4 5 6     =>        8 5 2   这里再沿着 7 5 3 这条对角线交换
             * 1 2 3               9 6 3
             */
            for (int i = 0; i < lengthX; i++) {
                for (int j = 0; j <= i; j++) {
                    if (i == j) {
                        continue;
                    }
                    temp = matrix[i][j];
                    matrix[i][j] = matrix[j][i];
                    matrix[j][i] = temp;
                }
            }
        }
    +
    public void rotate(int[][] matrix) {
+        // 这里真的傻了，长宽应该是一致的，所以取一次就够了
+        int lengthX = matrix[0].length;
+        int lengthY = matrix.length;
+        int temp;
+        System.out.println(lengthY - (lengthY % 2) / 2);
+        // 这里除错了，应该是减掉余数再除 2
+//        for (int i = 0; i < lengthY - (lengthY % 2) / 2; i++) {
+        /**
+         * 1 2 3             7 8 9
+         * 4 5 6     =>      4 5 6     先沿着 4 5 6 上下交换
+         * 7 8 9             1 2 3
+         */
+        for (int i = 0; i < (lengthY - (lengthY % 2)) / 2; i++) {
+            for (int j = 0; j < lengthX; j++) {
+                temp = matrix[i][j];
+                matrix[i][j] = matrix[lengthY-i-1][j];
+                matrix[lengthY-i-1][j] = temp;
+            }
+        }
+
+        /**
+         * 7 8 9               7 4 1
+         * 4 5 6     =>        8 5 2   这里再沿着 7 5 3 这条对角线交换
+         * 1 2 3               9 6 3
+         */
+        for (int i = 0; i < lengthX; i++) {
+            for (int j = 0; j <= i; j++) {
+                if (i == j) {
+                    continue;
+                }
+                temp = matrix[i][j];
+                matrix[i][j] = matrix[j][i];
+                matrix[j][i] = temp;
+            }
+        }
+    }

    还没到可以直接归纳题目类型的水平，主要是几年前做过，可能有那么点模糊的记忆，当然应该也有直接转的方法

    @@ -306,19 +343,19 @@
    Related Posts
    @@ -444,7 +481,7 @@
    -
    1. 1. 题目介绍
    2. 2. 代码
    +
    1. 1. 题目介绍
    2. 2. 代码
    diff --git a/404.html b/404.html index 76ac658779..5bc4a55bd1 100644 --- a/404.html +++ b/404.html @@ -4,7 +4,7 @@ - + @@ -30,14 +30,11 @@ + - + - - - - - + @@ -103,6 +100,7 @@ + @@ -230,7 +228,6 @@ - diff --git a/404/index.html b/404/index.html index 780cb6dbc5..79ac21ef1a 100644 --- a/404/index.html +++ b/404/index.html @@ -4,7 +4,7 @@ - + @@ -30,14 +30,11 @@ + - + - - - - - + diff --git a/archives/2014/12/index.html b/archives/2014/12/index.html index f310154d38..5b34331184 100644 --- a/archives/2014/12/index.html +++ b/archives/2014/12/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/2014/index.html b/archives/2014/index.html index 3ac5abddcb..f18d545e77 100644 --- a/archives/2014/index.html +++ b/archives/2014/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/2015/01/index.html b/archives/2015/01/index.html index 7ebd06d385..c84b5e0e05 100644 --- a/archives/2015/01/index.html +++ b/archives/2015/01/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/2015/03/index.html b/archives/2015/03/index.html index 9cc3c692e7..13401f2d3f 100644 --- a/archives/2015/03/index.html +++ b/archives/2015/03/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/2015/04/index.html b/archives/2015/04/index.html index 08e6c80cf3..3428051b39 100644 --- a/archives/2015/04/index.html +++ b/archives/2015/04/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/2015/06/index.html b/archives/2015/06/index.html index 7d1be28ca0..df68af4bf4 100644 --- a/archives/2015/06/index.html +++ b/archives/2015/06/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/2015/index.html b/archives/2015/index.html index dd5afe47c3..68fcedf991 100644 --- a/archives/2015/index.html +++ b/archives/2015/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/2016/07/index.html b/archives/2016/07/index.html index 1ab8c940b8..60a08899c3 100644 --- a/archives/2016/07/index.html +++ b/archives/2016/07/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/2016/08/index.html b/archives/2016/08/index.html index 93c8a765ae..2669eebff7 100644 --- a/archives/2016/08/index.html +++ b/archives/2016/08/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/2016/09/index.html b/archives/2016/09/index.html index 5c1e8c32f7..bf669cf5b3 100644 --- a/archives/2016/09/index.html +++ b/archives/2016/09/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/2016/10/index.html b/archives/2016/10/index.html index c0df1563ad..6018c921c3 100644 --- a/archives/2016/10/index.html +++ b/archives/2016/10/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/2016/11/index.html b/archives/2016/11/index.html index d322fb5d6b..f857e4db05 100644 --- a/archives/2016/11/index.html +++ b/archives/2016/11/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/2016/index.html b/archives/2016/index.html index ceff7fe076..6eeca43782 100644 --- a/archives/2016/index.html +++ b/archives/2016/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/2017/03/index.html b/archives/2017/03/index.html index 793689530c..12d0352801 100644 --- a/archives/2017/03/index.html +++ b/archives/2017/03/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/2017/04/index.html b/archives/2017/04/index.html index 372c77bba4..f33351c71a 100644 --- a/archives/2017/04/index.html +++ b/archives/2017/04/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/2017/05/index.html b/archives/2017/05/index.html index c40ece5c66..71b89049d9 100644 --- a/archives/2017/05/index.html +++ b/archives/2017/05/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/2017/index.html b/archives/2017/index.html index a1c00be9f3..1244e8c832 100644 --- a/archives/2017/index.html +++ b/archives/2017/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/2019/06/index.html b/archives/2019/06/index.html index 0e2afcc496..13edbd6eba 100644 --- a/archives/2019/06/index.html +++ b/archives/2019/06/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/2019/09/index.html b/archives/2019/09/index.html index dbc4e2390c..9fcbe2cc93 100644 --- a/archives/2019/09/index.html +++ b/archives/2019/09/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/2019/12/index.html b/archives/2019/12/index.html index ed63b6c3ec..b9d63fdea6 100644 --- a/archives/2019/12/index.html +++ b/archives/2019/12/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/2019/index.html b/archives/2019/index.html index 3adc7519b4..eb1f5f3a45 100644 --- a/archives/2019/index.html +++ b/archives/2019/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/2020/01/index.html b/archives/2020/01/index.html index 33f839226c..52b3a51a99 100644 --- a/archives/2020/01/index.html +++ b/archives/2020/01/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/2020/02/index.html b/archives/2020/02/index.html index 45ddc7d80e..b2548a152b 100644 --- a/archives/2020/02/index.html +++ b/archives/2020/02/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/2020/03/index.html b/archives/2020/03/index.html index f96f0382c9..99642c5982 100644 --- a/archives/2020/03/index.html +++ b/archives/2020/03/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/2020/04/index.html b/archives/2020/04/index.html index 2fa2775378..fc99becb79 100644 --- a/archives/2020/04/index.html +++ b/archives/2020/04/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/2020/05/index.html b/archives/2020/05/index.html index c4087a4ee1..bf4d8c7dda 100644 --- a/archives/2020/05/index.html +++ b/archives/2020/05/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/2020/06/index.html b/archives/2020/06/index.html index 7fedd5c12c..4f6ca95b5e 100644 --- a/archives/2020/06/index.html +++ b/archives/2020/06/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/2020/07/index.html b/archives/2020/07/index.html index 47f4565d6c..dcdf7617ff 100644 --- a/archives/2020/07/index.html +++ b/archives/2020/07/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/2020/08/index.html b/archives/2020/08/index.html index 94d6628386..66a9fe73f7 100644 --- a/archives/2020/08/index.html +++ b/archives/2020/08/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/2020/09/index.html b/archives/2020/09/index.html index 2bc9ac776c..bf8bcecce3 100644 --- a/archives/2020/09/index.html +++ b/archives/2020/09/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/2020/10/index.html b/archives/2020/10/index.html index cdc10b7460..d49d914490 100644 --- a/archives/2020/10/index.html +++ b/archives/2020/10/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/2020/11/index.html b/archives/2020/11/index.html index fbff8167ae..e13d37b258 100644 --- a/archives/2020/11/index.html +++ b/archives/2020/11/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/2020/12/index.html b/archives/2020/12/index.html index bd959774e6..3114bcd557 100644 --- a/archives/2020/12/index.html +++ b/archives/2020/12/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/2020/index.html b/archives/2020/index.html index a714662230..fc658c2d20 100644 --- a/archives/2020/index.html +++ b/archives/2020/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/2020/page/2/index.html b/archives/2020/page/2/index.html index 45d23d34e8..b279e1453a 100644 --- a/archives/2020/page/2/index.html +++ b/archives/2020/page/2/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/2020/page/3/index.html b/archives/2020/page/3/index.html index c6e3cf0106..472e29de44 100644 --- a/archives/2020/page/3/index.html +++ b/archives/2020/page/3/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/2020/page/4/index.html b/archives/2020/page/4/index.html index 0e8382fffa..d3b12de47d 100644 --- a/archives/2020/page/4/index.html +++ b/archives/2020/page/4/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/2020/page/5/index.html b/archives/2020/page/5/index.html index 1e465ce3f8..20b6e25b83 100644 --- a/archives/2020/page/5/index.html +++ b/archives/2020/page/5/index.html @@ -4,7 +4,7 @@ - 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+ @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/2021/05/index.html b/archives/2021/05/index.html index 9b527b83ef..fcbf74e117 100644 --- a/archives/2021/05/index.html +++ b/archives/2021/05/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/2021/index.html b/archives/2021/index.html index fc1880be1f..ab90261fd4 100644 --- a/archives/2021/index.html +++ b/archives/2021/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/2021/page/2/index.html b/archives/2021/page/2/index.html index 3c7bf1ee4a..d0289b24d3 100644 --- a/archives/2021/page/2/index.html +++ b/archives/2021/page/2/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/index.html b/archives/index.html index cca9de4d04..8ff0f2a086 100644 --- a/archives/index.html +++ b/archives/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/page/10/index.html b/archives/page/10/index.html index b9a1c95842..4ab65865d9 100644 --- a/archives/page/10/index.html +++ b/archives/page/10/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/page/11/index.html b/archives/page/11/index.html index baa80b3b6a..611ff8686d 100644 --- a/archives/page/11/index.html +++ b/archives/page/11/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/page/2/index.html b/archives/page/2/index.html index 85b750b7c6..b02313e7aa 100644 --- a/archives/page/2/index.html +++ b/archives/page/2/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/page/3/index.html b/archives/page/3/index.html index 4b02aca175..8f9e5f8b4e 100644 --- a/archives/page/3/index.html +++ b/archives/page/3/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/page/4/index.html b/archives/page/4/index.html index d55574a6f2..d2e0097299 100644 --- a/archives/page/4/index.html +++ b/archives/page/4/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/page/5/index.html b/archives/page/5/index.html index 0b69bbbe86..e876fb5595 100644 --- a/archives/page/5/index.html +++ b/archives/page/5/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/page/6/index.html b/archives/page/6/index.html index e755d3d1b3..7c5be7b04c 100644 --- a/archives/page/6/index.html +++ b/archives/page/6/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/page/7/index.html b/archives/page/7/index.html index 519e841479..4e096d98f0 100644 --- a/archives/page/7/index.html +++ b/archives/page/7/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/page/8/index.html b/archives/page/8/index.html index c849d6cb50..505f86f551 100644 --- a/archives/page/8/index.html +++ b/archives/page/8/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/archives/page/9/index.html b/archives/page/9/index.html index 9d099c330b..d1d85fd992 100644 --- a/archives/page/9/index.html +++ b/archives/page/9/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/atom.xml b/atom.xml index bd5df97840..a63dcfebaa 100644 --- a/atom.xml +++ b/atom.xml @@ -3,10 +3,10 @@ Nicksxs's Blog https://nicksxs.me/icon.png What hurts more, the pain of hard work or the pain of regret? - + - 2021-05-01T15:28:26.727Z + 2021-05-01T15:28:26.000Z https://nicksxs.me/ @@ -21,37 +21,35 @@ https://nicksxs.me/2021/05/01/Leetcode-48-%E6%97%8B%E8%BD%AC%E5%9B%BE%E5%83%8F-Rotate-Image-%E9%A2%98%E8%A7%A3%E5%88%86%E6%9E%90/ 2021-05-01T15:28:26.000Z - 2021-05-01T15:28:26.727Z + 2021-05-01T15:28:26.000Z - - <h3 id="题目介绍"><a href="#题目介绍" class="headerlink" title="题目介绍"></a>题目介绍</h3><p>You are given an n x n 2D <code>matrix</code> representing an + <h3 id="题目介绍"><a href="#题目介绍" class="headerlink" title="题目介绍"></a>题目介绍</h3><p>You are given an n x n 2D <code>matrix</code> representing an - - + - + - + - + - + - + - + - + @@ -60,33 +58,31 @@ https://nicksxs.me/2021/04/18/rust%E5%AD%A6%E4%B9%A0%E7%AC%94%E8%AE%B0/ 2021-04-18T14:04:01.000Z - 2021-04-18T14:06:53.609Z + 2021-04-18T14:04:01.000Z - - <p>最近在看 《rust 权威指南》，还是难度比较大的，它里面的一些概念跟之前的用过的都有比较大的差别<br>比起有 gc 的虚拟机语言，跟像 C 和 C++这种主动释放内存的，rust + <p>最近在看 《rust 权威指南》，还是难度比较大的，它里面的一些概念跟之前的用过的都有比较大的差别<br>比起有 gc 的虚拟机语言，跟像 C 和 C++这种主动释放内存的，rust - - + - + - + - + - + - + @@ -95,37 +91,35 @@ https://nicksxs.me/2021/04/18/rust%E5%AD%A6%E4%B9%A0%E7%AC%94%E8%AE%B0-%E6%89%80%E6%9C%89%E6%9D%83%E4%BA%8C/ 2021-04-18T14:03:10.000Z - 2021-04-25T12:22:00.083Z + 2021-04-18T14:03:10.000Z - - <p>这里需要说道函数和返回值了<br>可以看书上的这个例子<br><img data-src="https://gitee.com/nicksxs/images/raw/master/uPic/fnlsui.png" + <p>这里需要说道函数和返回值了<br>可以看书上的这个例子<br><img - - + - + - + - + - + - + - + - + @@ -134,49 +128,47 @@ https://nicksxs.me/2021/04/11/%E8%81%8A%E8%81%8A%E5%8E%A6%E9%97%A8%E6%97%85%E6%B8%B8%E7%9A%84%E5%A5%BD%E4%B8%8E%E4%B8%8D%E5%A5%BD/ 2021-04-11T15:38:07.000Z - 2021-04-11T15:38:07.755Z + 2021-04-11T15:38:07.000Z - - <p>这几天去了趟厦门，原来几年前就想去了，本来都请好假了，后面因为一些事情没去成，这次刚好公司组织，就跟 LD + <p>这几天去了趟厦门，原来几年前就想去了，本来都请好假了，后面因为一些事情没去成，这次刚好公司组织，就跟 LD - - + - + - + - + - + - + - + - + - + - + - + - + - + - + @@ -185,47 +177,45 @@ https://nicksxs.me/2021/04/04/%E8%81%8A%E8%81%8A-dubbo-%E7%9A%84%E7%BA%BF%E7%A8%8B%E6%B1%A0/ 2021-04-04T14:14:57.000Z - 2021-04-04T14:14:57.278Z + 2021-04-04T14:14:57.000Z - - <p>之前没注意到这一块，只是比较模糊的印象 dubbo 自己基于 ThreadPoolExecutor 定义了几个线程池，但是没具体看过，主要是觉得就是为了避免使用 jdk + <p>之前没注意到这一块，只是比较模糊的印象 dubbo 自己基于 ThreadPoolExecutor 定义了几个线程池，但是没具体看过，主要是觉得就是为了避免使用 jdk - - + - + - + - + - + - + - + - + - + - + - + - + - + @@ -234,41 +224,39 @@ https://nicksxs.me/2021/03/31/2020-%E5%B9%B4%E7%BB%88%E6%80%BB%E7%BB%93/ 2021-03-31T15:37:28.000Z - 2021-04-01T12:13:24.747Z + 2021-03-31T15:37:28.000Z - - <h2 id="拖更原因"><a href="#拖更原因" class="headerlink" + <h2 id="拖更原因"><a href="#拖更原因" class="headerlink" - - + - + - + - + - + - + - + - + - + - + @@ -277,41 +265,39 @@ https://nicksxs.me/2021/03/28/%E8%81%8A%E8%81%8A-Linux-%E4%B8%8B%E7%9A%84-top-%E5%91%BD%E4%BB%A4/ 2021-03-28T15:06:21.000Z - 2021-03-28T15:06:21.180Z + 2021-03-28T15:06:21.000Z - - <p>top 命令在日常的 Linux + <p>top 命令在日常的 Linux - - + - + - + - + - + - + - + - + - + - + @@ -320,45 +306,43 @@ https://nicksxs.me/2021/03/21/%E5%85%B3%E4%BA%8E%E5%85%AC%E5%85%B1%E4%BA%A4%E9%80%9A%E5%86%8D%E5%90%90%E4%B8%AA%E6%A7%BD/ 2021-03-21T15:23:40.000Z - 2021-03-21T15:23:40.505Z + 2021-03-21T15:23:40.000Z - - <p>事情源于周末来回家发生的两件事情，先是回去的时候从高铁下车要坐公交，现在算是有个比较好的临时候车点了，但是可能由于疫情好转，晚上都不用检查健康码就可以进候车点，但是上公交的时候还是需要看健康码，一般情况下从高铁下来的，各个地方的人都有，而且也不太清楚这边上公交车需要查验健康 + <p>事情源于周末来回家发生的两件事情，先是回去的时候从高铁下车要坐公交，现在算是有个比较好的临时候车点了，但是可能由于疫情好转，晚上都不用检查健康码就可以进候车点，但是上公交的时候还是需要看健康码，一般情况下从高铁下来的，各个地方的人都有，而且也不太清楚这边上公交车需要查验健康 - - + - + - + - + - + - + - + - + - + - + - + - + @@ -367,39 +351,37 @@ https://nicksxs.me/2021/03/14/Leetcode-121-%E4%B9%B0%E5%8D%96%E8%82%A1%E7%A5%A8%E7%9A%84%E6%9C%80%E4%BD%B3%E6%97%B6%E6%9C%BA-Best-Time-to-Buy-and-Sell-Stock-%E9%A2%98%E8%A7%A3%E5%88%86%E6%9E%90/ 2021-03-14T14:34:30.000Z - 2021-03-14T14:34:30.343Z + 2021-03-14T14:34:30.000Z - - <h3 id="题目介绍"><a href="#题目介绍" class="headerlink" title="题目介绍"></a>题目介绍</h3><p>You are given an array <code>prices</code> where + <h3 id="题目介绍"><a href="#题目介绍" class="headerlink" title="题目介绍"></a>题目介绍</h3><p>You are given an array <code>prices</code> where - - + - + - + - + - + - + - + - + - + @@ -408,38 +390,36 @@ https://nicksxs.me/2021/03/07/%E3%80%8A%E5%9E%83%E5%9C%BE%E5%9B%9E%E6%94%B6%E7%AE%97%E6%B3%95%E6%89%8B%E5%86%8C%E8%AF%BB%E4%B9%A6%E3%80%8B%E7%AC%94%E8%AE%B0%E4%B9%8B%E6%95%B4%E7%90%86%E7%AE%97%E6%B3%95/ 2021-03-07T12:37:06.000Z - 2021-03-07T12:37:06.387Z + 2021-03-07T12:37:06.000Z - - <p>最近看了下这本垃圾回收算法手册，看到了第三章的标记-整理回收算法，做个简单的读书笔记</p> -<h3 id="双指针整理算法"><a href="#双指针整理算法" class="headerlink" + <p>最近看了下这本垃圾回收算法手册，看到了第三章的标记-整理回收算法，做个简单的读书笔记</p> +<h3 id="双指针整理算法"><a href="#双指针整理算法" class="headerlink" - - + - + - + - + - + - + - + - + @@ -448,45 +428,43 @@ https://nicksxs.me/2021/02/28/%E9%97%B2%E8%81%8A%E4%B8%8B%E4%B9%98%E5%85%AC%E4%BA%A4%E7%9A%84%E7%94%A8%E6%88%B7%E4%BD%93%E9%AA%8C/ 2021-02-28T13:56:42.000Z - 2021-02-28T13:56:42.363Z + 2021-02-28T13:56:42.000Z - - <p>新年开工开车来杭州，因为没有车位加限行今天来就没开车来了，从东站做公交回住的地方，这班神奇的车我之前也吐槽过了，有神奇的乘客和神奇的司机，因为基本上这班车是从我毕业就开始乘了，所以也算是比较熟悉了，以前总体感觉不太好的是乘坐时间太长了，不过这个也不能怪车，是我自己住得远（离 + <p>新年开工开车来杭州，因为没有车位加限行今天来就没开车来了，从东站做公交回住的地方，这班神奇的车我之前也吐槽过了，有神奇的乘客和神奇的司机，因为基本上这班车是从我毕业就开始乘了，所以也算是比较熟悉了，以前总体感觉不太好的是乘坐时间太长了，不过这个也不能怪车，是我自己住得远（离 - - + - + - + - + - + - + - + - + - + - + - + - + @@ -495,43 +473,41 @@ https://nicksxs.me/2021/02/21/AQS-%E4%B9%8B-Condition-%E6%B5%85%E6%9E%90%E7%AC%94%E8%AE%B0/ 2021-02-21T13:27:06.000Z - 2021-02-21T13:27:06.183Z + 2021-02-21T13:27:06.000Z - - <p>Condition也是 AQS 中很重要的一块内容，可以先看段示例代码，这段代码应该来自于Doug Lea大大，可以在 javadoc 中的 <a + <p>Condition也是 AQS 中很重要的一块内容，可以先看段示例代码，这段代码应该来自于Doug Lea大大，可以在 javadoc 中的 <a - - + - + - + - + - + - + - + - + - + - + - + @@ -540,34 +516,32 @@ https://nicksxs.me/2021/02/14/AQS%E7%AF%87%E4%B8%80/ 2021-02-14T14:51:54.000Z - 2021-02-28T12:02:18.297Z + 2021-02-14T14:51:54.000Z - - <p>很多东西都是时看时新，而且时间长了也会忘，所以再来复习下，也会有一些新的角度看法这次来聊下AQS的内容，主要是这几个点，</p> -<h2 id="第一个线程"><a href="#第一个线程" class="headerlink" + <p>很多东西都是时看时新，而且时间长了也会忘，所以再来复习下，也会有一些新的角度看法这次来聊下AQS的内容，主要是这几个点，</p> +<h2 id="第一个线程"><a href="#第一个线程" class="headerlink" - - + - + - + - + - + - + @@ -576,39 +550,37 @@ https://nicksxs.me/2021/02/07/%E5%85%B3%E4%BA%8E%E8%AF%BB%E4%B9%A6%E6%89%93%E5%8D%A1%E4%B8%8E%E5%88%86%E4%BA%AB/ 2021-02-07T15:13:39.000Z - 2021-02-07T15:13:39.017Z + 2021-02-07T15:13:39.000Z - - <p>最近群里大佬发起了一个读书打卡活动，需要每天读一会书，在群里打卡分享感悟，争取一个月能读完一本书，说实话一天十分钟的读书时间倒是问题不大，不过每天都要打卡，而且一个月要读完一本书，其实难度还是有点大的，不过也想试试看。<br>之前某某老大给自己立了个 + <p>最近群里大佬发起了一个读书打卡活动，需要每天读一会书，在群里打卡分享感悟，争取一个月能读完一本书，说实话一天十分钟的读书时间倒是问题不大，不过每天都要打卡，而且一个月要读完一本书，其实难度还是有点大的，不过也想试试看。<br>之前某某老大给自己立了个 - - + - + - + - + - + - + - + - + - + @@ -617,50 +589,48 @@ https://nicksxs.me/2021/01/31/%E8%81%8A%E8%81%8A-redis-%E7%BC%93%E5%AD%98%E7%9A%84%E5%BA%94%E7%94%A8%E9%97%AE%E9%A2%98/ 2021-01-31T15:02:44.000Z - 2021-01-31T15:02:44.242Z + 2021-01-31T15:02:44.000Z - - <p>前面写过一系列的 redis 源码分析的，但是实际上很多的问题还是需要结合实际的使用，然后其实就避不开缓存使用的三个著名问题，穿透，击穿和雪崩，这三个概念也是有着千丝万缕的关系，</p> -<h3 id="缓存穿透"><a href="#缓存穿透" + <p>前面写过一系列的 redis 源码分析的，但是实际上很多的问题还是需要结合实际的使用，然后其实就避不开缓存使用的三个著名问题，穿透，击穿和雪崩，这三个概念也是有着千丝万缕的关系，</p> +<h3 id="缓存穿透"><a href="#缓存穿透" - - + - + - + - + - + - + - + - + - + - + - + - + - + - + @@ -669,41 +639,39 @@ https://nicksxs.me/2021/01/24/Leetcode-124-%E4%BA%8C%E5%8F%89%E6%A0%91%E4%B8%AD%E7%9A%84%E6%9C%80%E5%A4%A7%E8%B7%AF%E5%BE%84%E5%92%8C-Binary-Tree-Maximum-Path-Sum-%E9%A2%98%E8%A7%A3%E5%88%86%E6%9E%90/ 2021-01-24T14:45:03.000Z - 2021-01-24T14:45:03.748Z + 2021-01-24T14:45:03.000Z - - <h3 id="题目介绍"><a href="#题目介绍" class="headerlink" title="题目介绍"></a>题目介绍</h3><p>A <strong>path</strong> in a binary tree is a sequence of + <h3 id="题目介绍"><a href="#题目介绍" class="headerlink" title="题目介绍"></a>题目介绍</h3><p>A <strong>path</strong> in a binary tree is a sequence of - - + - + - + - + - + - + - + - + - + - + @@ -712,35 +680,33 @@ https://nicksxs.me/2021/01/17/%E8%81%8A%E8%81%8A%E9%82%A3%E4%BA%9B%E5%8A%A0%E5%A1%9E%E7%8B%97/ 2021-01-17T15:29:09.000Z - 2021-01-17T15:29:09.250Z + 2021-01-17T15:29:09.000Z - - <p>今天真的是被气得不轻，情况是碰到一个有 70 + <p>今天真的是被气得不轻，情况是碰到一个有 70 - - + - + - + - + - + - + - + @@ -749,39 +715,37 @@ https://nicksxs.me/2021/01/10/Leetcode-160-%E7%9B%B8%E4%BA%A4%E9%93%BE%E8%A1%A8-intersection-of-two-linked-lists-%E9%A2%98%E8%A7%A3%E5%88%86%E6%9E%90/ 2021-01-10T13:09:28.000Z - 2021-01-22T12:22:13.202Z + 2021-01-10T13:09:28.000Z - - <h2 id="题目介绍"><a href="#题目介绍" class="headerlink" + <h2 id="题目介绍"><a href="#题目介绍" class="headerlink" - - + - + - + - + - + - + - + - + - + @@ -790,20 +754,18 @@ https://nicksxs.me/2021/01/03/%E8%81%8A%E8%81%8A-Java-%E7%9A%84-equals-%E5%92%8C-hashCode-%E6%96%B9%E6%B3%95/ 2021-01-03T14:26:35.000Z - 2021-01-03T14:26:35.828Z + 2021-01-03T14:26:35.000Z - - <p>Java 中的这个话题也是比较常遇到的，关于这块原先也是比较忽略的，但是仔细想想又有点遗忘了就在这里记一下<br>简单看下代码<br><code>java.lang.Object#equals</code></p> -<figure class="highlight + <p>Java 中的这个话题也是比较常遇到的，关于这块原先也是比较忽略的，但是仔细想想又有点遗忘了就在这里记一下<br>简单看下代码<br><code>java.lang.Object#equals</code></p> +<pre class="line-numbers - @@ -814,40 +776,38 @@ https://nicksxs.me/2020/12/27/%E8%81%8A%E8%81%8A-mysql-%E7%B4%A2%E5%BC%95%E7%9A%84%E4%B8%80%E4%BA%9B%E7%BB%86%E8%8A%82/ 2020-12-27T15:49:05.000Z - 2020-12-27T16:16:08.313Z + 2020-12-27T15:49:05.000Z - - <p>前几天同事问了我个 mysql 索引的问题，虽然大概知道，但是还是想来实践下，就是 is null，is not null 这类查询是否能用索引，可能之前有些网上的文章说都是不能用索引，但是其实不是，我们来看个小试验</p> -<figure + <p>前几天同事问了我个 mysql 索引的问题，虽然大概知道，但是还是想来实践下，就是 is null，is not null 这类查询是否能用索引，可能之前有些网上的文章说都是不能用索引，但是其实不是，我们来看个小试验</p> +<pre - - + - + - + - + - + - + - + - + - + diff --git a/baidu_verify_Gl8jtoDV4z.html b/baidu_verify_Gl8jtoDV4z.html index ea11a6e311..5c586d112a 100644 --- a/baidu_verify_Gl8jtoDV4z.html +++ b/baidu_verify_Gl8jtoDV4z.html @@ -4,7 +4,7 @@ - + @@ -32,14 +32,11 @@ + - + - - - - - + diff --git a/baidusitemap.xml b/baidusitemap.xml index e6abfaac05..56840539c0 100644 --- a/baidusitemap.xml +++ b/baidusitemap.xml @@ -3,305 +3,405 @@ https://nicksxs.me/2021/05/01/Leetcode-48-%E6%97%8B%E8%BD%AC%E5%9B%BE%E5%83%8F-Rotate-Image-%E9%A2%98%E8%A7%A3%E5%88%86%E6%9E%90/ 2021-05-01 - - https://nicksxs.me/2021/04/18/rust%E5%AD%A6%E4%B9%A0%E7%AC%94%E8%AE%B0-%E6%89%80%E6%9C%89%E6%9D%83%E4%BA%8C/ - 2021-04-25 - + + https://nicksxs.me/2021/04/18/rust%E5%AD%A6%E4%B9%A0%E7%AC%94%E8%AE%B0/ 2021-04-18 - + + + https://nicksxs.me/2021/04/18/rust%E5%AD%A6%E4%B9%A0%E7%AC%94%E8%AE%B0-%E6%89%80%E6%9C%89%E6%9D%83%E4%BA%8C/ + 2021-04-18 + + https://nicksxs.me/2021/04/11/%E8%81%8A%E8%81%8A%E5%8E%A6%E9%97%A8%E6%97%85%E6%B8%B8%E7%9A%84%E5%A5%BD%E4%B8%8E%E4%B8%8D%E5%A5%BD/ 2021-04-11 - + + https://nicksxs.me/2021/04/04/%E8%81%8A%E8%81%8A-dubbo-%E7%9A%84%E7%BA%BF%E7%A8%8B%E6%B1%A0/ 2021-04-04 - + + https://nicksxs.me/2021/03/31/2020-%E5%B9%B4%E7%BB%88%E6%80%BB%E7%BB%93/ - 2021-04-01 - + 2021-03-31 + + https://nicksxs.me/2021/03/28/%E8%81%8A%E8%81%8A-Linux-%E4%B8%8B%E7%9A%84-top-%E5%91%BD%E4%BB%A4/ 2021-03-28 - + + https://nicksxs.me/2021/03/21/%E5%85%B3%E4%BA%8E%E5%85%AC%E5%85%B1%E4%BA%A4%E9%80%9A%E5%86%8D%E5%90%90%E4%B8%AA%E6%A7%BD/ 2021-03-21 - + + https://nicksxs.me/2021/03/14/Leetcode-121-%E4%B9%B0%E5%8D%96%E8%82%A1%E7%A5%A8%E7%9A%84%E6%9C%80%E4%BD%B3%E6%97%B6%E6%9C%BA-Best-Time-to-Buy-and-Sell-Stock-%E9%A2%98%E8%A7%A3%E5%88%86%E6%9E%90/ 2021-03-14 - 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+ @@ -32,12 +32,9 @@ + - - - - - + diff --git a/categories/Mysql/index.html b/categories/Mysql/index.html index e31a54005e..23e2b66678 100644 --- a/categories/Mysql/index.html +++ b/categories/Mysql/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/categories/Mysql/数据结构/index.html b/categories/Mysql/数据结构/index.html index e5f1392fb9..d4fc2b353b 100644 --- a/categories/Mysql/数据结构/index.html +++ b/categories/Mysql/数据结构/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/categories/Mysql/源码/index.html b/categories/Mysql/源码/index.html index 6db2ea9818..5a5c356d0b 100644 --- a/categories/Mysql/源码/index.html +++ b/categories/Mysql/源码/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/categories/Mysql/索引/index.html b/categories/Mysql/索引/index.html index f4c3e2ed79..9711b83925 100644 --- a/categories/Mysql/索引/index.html +++ b/categories/Mysql/索引/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/categories/Redis/Distributed-Lock/index.html b/categories/Redis/Distributed-Lock/index.html index 90ee30a392..91f0bc5e63 100644 --- a/categories/Redis/Distributed-Lock/index.html +++ b/categories/Redis/Distributed-Lock/index.html @@ -4,7 +4,7 @@ - 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+ @@ -32,12 +32,9 @@ + - - - - - + diff --git a/categories/RocketMQ/index.html b/categories/RocketMQ/index.html index 9b497acda3..8905fc0dd7 100644 --- a/categories/RocketMQ/index.html +++ b/categories/RocketMQ/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/categories/Rust/index.html b/categories/Rust/index.html index 5ce7564afc..3148d18833 100644 --- a/categories/Rust/index.html +++ b/categories/Rust/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/categories/Spring/Mybatis/index.html b/categories/Spring/Mybatis/index.html index 53722bb4b1..11d9b022c7 100644 --- a/categories/Spring/Mybatis/index.html +++ b/categories/Spring/Mybatis/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/categories/Spring/Servlet/Interceptor/AOP/index.html b/categories/Spring/Servlet/Interceptor/AOP/index.html index ef7e29b53d..4468e15d2f 100644 --- a/categories/Spring/Servlet/Interceptor/AOP/index.html +++ b/categories/Spring/Servlet/Interceptor/AOP/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/categories/Spring/Servlet/Interceptor/index.html b/categories/Spring/Servlet/Interceptor/index.html index 4d1d30a23f..1e18f34bce 100644 --- a/categories/Spring/Servlet/Interceptor/index.html +++ b/categories/Spring/Servlet/Interceptor/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/categories/Spring/Servlet/index.html b/categories/Spring/Servlet/index.html index 6f98d8c6ee..e811686c01 100644 --- a/categories/Spring/Servlet/index.html +++ b/categories/Spring/Servlet/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/categories/Spring/index.html b/categories/Spring/index.html index 5bc24eac88..eb32b608d7 100644 --- a/categories/Spring/index.html +++ b/categories/Spring/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/categories/Thread-dump/index.html b/categories/Thread-dump/index.html index fed39b48e4..4b14b0d024 100644 --- a/categories/Thread-dump/index.html +++ b/categories/Thread-dump/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/categories/data-analysis/index.html b/categories/data-analysis/index.html index 5e63455fd0..d3dbca621e 100644 --- a/categories/data-analysis/index.html +++ b/categories/data-analysis/index.html @@ -4,7 +4,7 @@ - + @@ -32,12 +32,9 @@ + - - - - - + diff --git a/categories/docker/index.html b/categories/docker/index.html index 94ac71e5f4..2895929c0b 100644 --- a/categories/docker/index.html +++ b/categories/docker/index.html @@ -4,7 +4,7 @@ - + @@ -29,18 +29,15 @@ - + + - - - - - + - + - Category: docker | Nicksxs's Blog + Category: Docker | Nicksxs's Blog - - - - - - -ocity/velocity.min.js"> - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Tag: docker | Nicksxs's Blog + Tag: Docker | Nicksxs's Blog - - - - - - -ib/velocity/velocity.min.js"> - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Tag: Java | Nicksxs's Blog + Tag: java | Nicksxs's Blog - - - - - - -net/npm/quicklink@1/dist/quicklink.umd.js"> - 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