关于mysql:ShardingSphereProxy-50-分库分表一

48次阅读

共计 6883 个字符,预计需要花费 18 分钟才能阅读完成。

@[toc]

一、简述

  • 简述
    ShardingSphere-Proxy4.0 曾经降级到 5.0 了,然而两者的配置文件还有肯定的差异的,这篇文章讲述的就是 ShardingSphere-Proxy 5.0 的落地。概念、分表、分库、分库分表的原理的根本和 4.0 一样的,须要理解可查看 https://blog.csdn.net/Fu_Shi_…。
  • 开发者文档
    https://shardingsphere.apache…

二、ShardingSphere-Proxy5.0 落地

  • 环境

    • JAVA JDK 下载

      https://pan.baidu.com/s/1A-ksNN0YicT3hXjFscGGwA 
      提取码:r9e0
    • JDBC 数据连贯驱动下载

      https://pan.baidu.com/s/1924iUe7wxGpStAzxxv2K3g 
      提取码:jy7z
    • ShardingSphere-Proxy 5.0 下载、

      https://archive.apache.org/dist/shardingsphere/5.0.0/
    • Window 11
  • 落地

    • 条件

      1. 实在数据库
      2. 逻辑数据库
      3. ShardingSphere-Proxy5.0 配置文件
    • 步骤

      1. 新建实在数据库和表【hmms.user 表为例】

        • 数据库表构造语句

          SET NAMES utf8mb4;
          SET FOREIGN_KEY_CHECKS = 0;
          
          -- ----------------------------
          -- Table structure for user
          -- ----------------------------
          DROP TABLE IF EXISTS `user`;
          CREATE TABLE `user`  (`useid` int(11) NOT NULL,
            `usenam` varchar(50) CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL COMMENT '登录名',
            `usepwd` varchar(100) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '登录明码',
            `usestate` int(11) NULL DEFAULT 2 COMMENT '-1:删除 1:登记 2:失常 3:挂失',
            `usekey` varchar(100) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '用户秘钥',
            `usetel` varchar(11) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '用户手机',
            `createbyid` varchar(50) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '增加人',
            `createbytime` datetime(0) NULL DEFAULT NULL COMMENT '增加工夫',
            `modifybyid` varchar(50) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '批改人',
            `modifybytime` datetime(0) NULL DEFAULT NULL COMMENT '批改工夫',
            PRIMARY KEY (`useid`) USING BTREE
          ) ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci ROW_FORMAT = Dynamic;
          SET FOREIGN_KEY_CHECKS = 1;
        • 运行后果如下:

  

2. 批改 ShardingSphere-Proxy5.0  配置文件,并连贯

   config-sharding.yaml

   ```
   # 3、创立客户端连贯库
   schemaName: hmms
   
   #1、连贯 mysql
   dataSources:
     hmmsdatasources-0:
       url: jdbc:mysql://localhost:3306/hmms?serverTimezone=UTC&useSSL=false
       username: root
       password: ****
       connectionTimeoutMilliseconds: 30000
       idleTimeoutMilliseconds: 60000
       maxLifetimeMilliseconds: 1800000
       maxPoolSize: 50
       minPoolSize: 1
       
   # 2、分片规定
   rules:
   - !SHARDING
     tables:
       user: #表名
         actualDataNodes: hmmsdatasources-0.user-${0..1}  #分表规定
         tableStrategy:
           standard:
             shardingColumn: useid   #分片键
             shardingAlgorithmName: use_MOD  #分表算法
     shardingAlgorithms:  #分表算法
       use_MOD:  #取模算法
         type: MOD
         props:
           sharding-count: 2
   ```

   server.yaml

   ```
   rules:
     - !AUTHORITY
       users:
         - root@%:*****
         - sharding@:sharding
       provider:
         type: ALL_PRIVILEGES_PERMITTED
   ```

   运行命令

   ```
   #在 ShardingSphere-Proxy bin
   start.bat 端口号
   ```

   运行后果如下:![在这里插入图片形容](https://img-blog.csdnimg.cn/8d7b5ca3c7e84edb927779bcc84da367.png?x-oss-process=image/watermark,type_d3F5LXplbmhlaQ,shadow_50,text_Q1NETiBAQEDnpZ7lhpw=,size_20,color_FFFFFF,t_70,g_se,x_16#pic_center)


3. 新建逻辑数据连贯,并执行表构造和数据脚本

   逻辑库执行后果如下:![在这里插入图片形容](https://img-blog.csdnimg.cn/fcb4986d5c6142b58892c09826ea715e.png#pic_center)


    逻辑数据库增加两条数据

   SQL 语句

   ```
   INSERT INTO `user` VALUES (1, 'admin', '202CB962AC59075B964B07152D234B70', 2, '123', '123123', 'xiaogang', '2021-08-25 20:12:15', 'xiaogang', NULL);
   INSERT INTO `user` VALUES (2, 'admin', '202CB962AC59075B964B07152D234B70', 2, '123', '123123', 'xiaogang', '2021-08-25 20:12:15', 'xiaogang', NULL);
   ```

   执行后果如下:![在这里插入图片形容](https://img-blog.csdnimg.cn/2e27942bdd1b472fb4451ead2f76c133.png#pic_center)

  • 分库分表

ShardingSphere-Proxy 5.0 配置

# 3、创立客户端连贯库
schemaName: hmms

#1、连贯 mysql
dataSources:
  hmmsdatasources-0:
    url: jdbc:mysql:// 主机地址: 端口号 /hmms-0?serverTimezone=UTC&useSSL=false
    username: root
    password: 明码
    connectionTimeoutMilliseconds: 30000
    idleTimeoutMilliseconds: 60000
    maxLifetimeMilliseconds: 1800000
    maxPoolSize: 50
    minPoolSize: 1

  hmmsdatasources-1:
    url: jdbc:mysql:// 主机地址: 端口号 /hmms-1?serverTimezone=UTC&useSSL=false
    username: root
    password: 明码
    connectionTimeoutMilliseconds: 30000
    idleTimeoutMilliseconds: 60000
    maxLifetimeMilliseconds: 1800000
    maxPoolSize: 50
    minPoolSize: 1
    

# 2、分片规定
rules:
- !SHARDING
  tables:
    user:
      actualDataNodes: hmmsdatasources-${0..1}.user-${0..1}   
      tableStrategy:
        standard:
          shardingColumn: useid
          shardingAlgorithmName: use_MOD
      databaseStrategy:  #分库规定
          standard:
            shardingColumn: useid
            shardingAlgorithmName: use_MOD
      keyGenerateStrategy: 
        column: useid
        keyGeneratorName: snowflake
  shardingAlgorithms:
    use_MOD:
      type: MOD
      props:
        sharding-count: 2 
    use_HASH_MOD:
      type: HASH_MOD
      props:
        sharding-count: '2'
  keyGenerators: 
    snowflake: 
       type: SNOWFLAKE
       props: 
         worker-id: 123
  • 分片算法

    1. 取模算法
    shardingAlgorithms:  #分表算法
    use_MOD:  #取模算法
      type: MOD
      props:
        sharding-count: 2  #分表数据和分表的表达式必须是统一的 
  1. 范畴算法

      shardingAlgorithms:
        use_BOUNDARY_RANGE:
          type: BOUNDARY_RANGE
          props:
            sharding-ranges: 2,100  #多个节点是以逗号宰割  [是依据分的表联合配置节点]
     #备注
      #分片键为:useid  int 类型
      #分表的为 3 个表
      #sharding-ranges: 2,100 是以 2 为节点,小于 2 的数据存到表 0,2 到 99 存到表 1,100 以上存到表 3 
  2. 容量算法

    shardingAlgorithms:
        use_VOLUME_RANGE:
                type: VOLUME_RANGE
                props:
                  range-lower: '20000000'  #最小值
                  range-upper: '40000000'  #最大值
                  # 分片的区间的数据的距离
                  sharding-volume: '20000000'
     #备注
        最小值为 2000 万,也就是说表数据量小于等于 2000 万,最大数量为 4000 万
        表与表的距离为 2000 万
        比如说分了两张表:1-2000 万       存到表 0
        2001 万 -4000 万   存到表 1
        是依据分表的数量来定义最大值的
        分了三张表,那最大值为 6000 万 
  3. HASH-CODE 算法【如果分片键是字符串类型,须要这种算法分表】

      shardingAlgorithms:
        use_HASH_MOD:
          type: HASH_MOD
          props:
            sharding-count: '2'  #分表数量,单引号必须要加 
  4. 依据工夫分表算法

    shardingAlgorithms:
        use_AUTO_INTERVAL:
            type: AUTO_INTERVAL
            props:
              datetime-lower: '2020-01-01 23:59:59'
              datetime-upper: '2022-12-31 23:59:59'
              # 以 1 年度为单位进行划分
              sharding-seconds: '31536000'  
              # 以 1 个月为单位进行划分
              #sharding-seconds: '2678400'   
              # 以 1 天为单位进行划分
              #sharding-seconds: '86400'
     #设置的最大值必须和分多少表匹配才行,否者报错,找不到表 
  • 分布式 ID

    config-sharding.yaml

    # 3、创立客户端连贯库
    schemaName: hmms
    
    #1、连贯 mysql
    dataSources:
      hmmsdatasources-0:
        url: jdbc:mysql://localhost:3306/hmms?serverTimezone=UTC&useSSL=false
        username: root
        password: 1QAZ2WSX3EDC
        connectionTimeoutMilliseconds: 30000
        idleTimeoutMilliseconds: 60000
        maxLifetimeMilliseconds: 1800000
        maxPoolSize: 50
        minPoolSize: 1
        
    # 2、分片规定
    rules:
    - !SHARDING
      tables:
        user:
          actualDataNodes: hmmsdatasources-0.user-${0..1}
          tableStrategy:
            standard:
              shardingColumn: id
              shardingAlgorithmName: use_HASH_MOD
          keyGenerateStrategy: 
            column: id
            keyGeneratorName: snowflake
      shardingAlgorithms:
        use_MOD:
          type: MOD
          props:
            sharding-count: 2 
        use_HASH_MOD:
          type: HASH_MOD
          props:
            sharding-count: '2'
      keyGenerators: 
        snowflake: 
           type: SNOWFLAKE
           props: 
             worker-id: 123
          

    表构造 sql 语句

    SET NAMES utf8mb4;
    SET FOREIGN_KEY_CHECKS = 0;
    
    -- ----------------------------
    -- Table structure for user
    -- ----------------------------
    DROP TABLE IF EXISTS `user`;
    CREATE TABLE `user`  (`id` varchar(100),
      `useid` int(11) NOT NULL,
      `usenam` varchar(50) CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL COMMENT '登录名',
      `usepwd` varchar(100) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '登录明码',
      `usestate` int(11) NULL DEFAULT 2 COMMENT '-1:删除 1:登记 2:失常 3:挂失',
      `usekey` varchar(100) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '用户秘钥',
      `usetel` varchar(11) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '用户手机',
      `createbyid` varchar(50) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '增加人',
      `createbytime` datetime(0) NULL DEFAULT NULL COMMENT '增加工夫',
      `modifybyid` varchar(50) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '批改人',
      `modifybytime` datetime(0) NULL DEFAULT NULL COMMENT '批改工夫',
      PRIMARY KEY (`useid`) USING BTREE
    ) ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci ROW_FORMAT = Dynamic;
    SET FOREIGN_KEY_CHECKS = 1;

    数据填充语句

    INSERT INTO `user`(useid,usenam,usepwd,usestate,usekey,usetel,createbyid,createbytime,modifybyid,modifybytime) VALUES (1, 'admin', '202CB962AC59075B964B07152D234B70', 2, '123', '123123', 'xiaogang', '2021-08-25 20:12:15', 'xiaogang', NULL);

    执行构造如下:


正文完
 0