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GPL-2.0
  1. openGauss-tools-datachecker

    介绍

    DataChecker是一个用Java语言编写的检验两个数据库间数据一致性的工具,一般情况下用于数据迁移完成之后的正确性校验。在将大量数据从一个数据库迁移至另一个数据库后,往往需要确定迁移过去的数据是否正确、完整。DataChecker就是用来检验两边数据库中的数据是否一致的工具。

    校验原理

    简单地说,就是对两边数据库对应的表的checksum值做full join,得出校验结果。举个例子,假设要校验mysql端的表A以及openGauss端的表A,先用哈希函数(MD5)分别算出两端的表A里每一条记录的哈希值,再对两边的哈希值做full join,得出校验结果。

    实现架构

    整个工具的实现框架分为4个部分:

    1.Preparer:计算出openGauss端的表的checksum值,并插入一个新建的表checksumB。

    2.Extractor:计算出Oracle/Mysql/Postgresql端的表的checksum值, 并提取出来。

    3.Applier:将Extractor中提取出来的checksum值,插入openGauss端的一个新建的表checksumA。

    4.让checksumA和checksumB做full join操作,得出校验结果并反向查找出具体的不匹配记录。

    环境要求

    操作系统

    纯java开发,有bat和shell脚本,windows/linux均可支持。

    jdk建议使用1.6.25以上的版本。

    数据库

    源库支持mysql、Oracle,后续将增加对Postgresql的支持。

    目标库仅支持openGauss数据库。

    安装教程

    ① 下载源码:
    git clone git@gitee.com:opengauss/openGauss-tools-datachecker.git
    ② 进入根目录
    cd openGauss-tools-datachecker
    ③ 编译
    mvn clean install -Dmaven.test.skip -Denv=release

    使用说明

    1. 编译后根目录下会出现target文件夹,target文件夹中的DataChecker-1.0.0-RELEASE.tar.gz即为所需要的包。

    2. 解压DataChecker-1.0.0-RELEASE.tar.gz

    3. 修改配置文件/conf/ gauss.properties

      参数名字 参数说明 默认值
      gauss.database.source.username 源数据库的用户名
      gauss.database.source.password 源数据库的密码
      gauss.database.source.type 源数据库的类型 Mysql
      gauss.database.source.url 源数据库的连接url,须遵循一定的格式
      gauss.database.source.encode 源数据库的编码格式 UTF-8
      gauss.database.target.username 目标数据库的用户名
      gauss.database.target.password 目标数据库的密码
      gauss.database.target.type 目标数据库的类型 OPGS(即openGauss)
      gauss.database.target.url 目标数据库的连接url,须遵循一定的格式
      gauss.database.target.encode 目标数据库的编码 UTF-8
      gauss.table.onceCrawNum extractor/applier每个批次最多处理记录数 1000
      gauss.table.tpsLimit tps限制,0代表不限制 0
      gauss.table.white 白名单。定义需要进行校验的表: 格式为schema.tablename组成,多个表可加逗号分隔。如想要校验一个schema下面的所有表,则填schema的名字即可
      gauss.table.black 黑名单,需要忽略的表。格式同gauss.table.white
      gauss.table.concurrent.enable 多张表之前是否开启并行处理,如果false代表需要串行处理 true
      gauss.table.concurrent.size 允许并行处理的表数 5
      gauss.table.query_dop opengauss中的query_dop参数,用于控制执行的并行线程数
      gauss.extractor.concurrent.global extractor是启用全局线程池模式,如果true代表所有extractor任务都使用一组线程池,线程池大小由concurrent.size控制 false
      gauss.extractor.concurrent.size 允许并行处理的线程数,需要先开启concurrent.enable该参数才会生效 30
      gauss.applier.concurrent.enable applier是否开启并行处理 true
      gauss.applier.concurrent.global applier是启用全局线程池模式,如果true代表所有applier任务都使用一组线程池,线程池大小由concurrent.size控制 false
      gauss.applier.concurrent.size 允许并行处理的线程数,需要先开启concurrent.enable该参数才会生效 30
      gauss.stat.print.interval 统计信息打印频率. 频率为5,代表,完成5轮extract/applier后,打印一次统计信息 5
    4. 启动及停止

      #Linux下:
      sh bin/startup.sh(启动)
      sh bin/stop.sh (停止)
      
      #windows下:
      双击bin/startup.bat(启动)
      直接关掉窗口(停止)

      日志说明

      日志结构为:

      /logs
      	summary/    
      		summary.log
      	gauss/      
      		table.log 
      	${table}/           
              table.log
              extractor.log
              applier.log
              check.log   
           
      gauss目录下的table.log为整个校验过程的总日志。
      summary目录下的summary.log记录了所有校验结果为不正确的表名(即两边表的数据不一致)。
      ${table} 为各个表的表名,其下的table.log为该表的校验过程总日志,extractor.log为checksum提取过程的总日志,applier.log为插入checksum过程中的总日志。check.log记录了校验失败的具体某一行的数据。如没有出现check.log,则表示校验结果为正确。

参与贡献

  1. Fork 本仓库 2. 新建 Feat_xxx 分支 3. 提交代码 4. 新建 Pull Request
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