如何通过 Apache SeaTunnel 实现 MySQL 到 OceanBase的数据迁移同步

本文来源于 OceanBase 数据库官方博客，目前 Apache SeaTunnel 2.3.9 已支持本文提到的所有功能，故原文2.3.7已全部修改为2.3.9

准备传输工具

本方案采用 Apache SeaTunnel（简称SeaTunnel）进行MySQL 到 OceanBase 的数据迁移和同步，出于对方案轻量性的考量，我们采用其内置的 Zeta 引擎来实现，包括全量同步、离线增量同步，以及 CDC 方案。

运行环境准备

自行安装运行环境JAVA，推荐版本为8，但理论上高于8的版本也能正常工作。

安装后，请确保已正确配置JAVA_HOME

root:~# java -version
openjdk version "17.0.12" 2024-07-16
OpenJDK Runtime Environment (build 17.0.12+7-Debian-2deb11u1)
OpenJDK 64-Bit Server VM (build 17.0.12+7-Debian-2deb11u1, mixed mode, sharing)java

下载并安装SeaTunnel

进入官网下载页面，下载适合版本SeaTunnel : https://seatunnel.apache.org/

我这里选择最新版本2.3.9

下载
wget https://dlcdn.apache.org/seatunnel/2.3.9/apache-seatunnel-2.3.9-bin.tar.gz
解压
tar -zxvf apache-seatunnel-2.3.9-bin.tar.gz 

连接器插件的下载与安装

SeaTunnel 安装包只包含主体文件与 Zeta 引擎，连接不同数据源的插件需要手动下载并配置。

自动下载方案

通过配置config/plugin_config文件来指定你需要的连接器，默认文件里是全方案的，可以根据你的需要增删一些，我们这里只包含这次演示需要使用的连接库。

connector-cdc-mysql
connector-jdbc
connector-fake
connector-console

输入命令

sh bin/install-plugin.sh 2.3.9

开始自动下载连接器

手动下载方案

进入网站：https://repo.maven.apache.org/maven2/org/apache/seatunnel/

找到自己需要的插件例如：

connector-cdc-mysql-2.3.9.jar
connector-console-2.3.9.jar
connector-fake-2.3.9.jar
connector-jdbc-2.3.9.jar
seatunnel-transforms-v2-2.3.9.jar

将文件手动下载之后 放入Connectors

验证连接器安装情况

./bin/seatunnel-connector.sh -l
 
Source
FakeSource MySQL-CDC Jdbc
 
 
Sink
Jdbc Console
 
 
Transform
Copy DynamicCompile FieldMapper Filter FilterRowKind JsonPath LLM Replace Split Sql

由于我们是使用 JDBC 使用 MySQL 的连接方式去操作 OceanBase 所以还需要下载一个jdbc-mysql，请自行前往前往 MySQL 官网下载 JDBC 。

将下载的mysql-connector-j-9.0.0.jar放到{seatunnel/lib}中。

SeaTunnel验证

使用 config 官方自带的v2批操作验证 SeaTunnel 是否正常

./bin/seatunnel.sh --config ./config/v2.batch.config.template -m local
 
参数解释:
seatunnel.sh #seatunnel标准启动脚本
config #选择配置脚本
m #运行方式 这里选择本地运行

当您运行该命令时，可以在控制台中看到它的输出

2022-12-19 11:01:45,417 INFO  org.apache.seatunnel.connectors.seatunnel.console.sink.ConsoleSinkWriter - output rowType: name<STRING>, age<INT>
2022-12-19 11:01:46,489 INFO  org.apache.seatunnel.connectors.seatunnel.console.sink.ConsoleSinkWriter - subtaskIndex=0 rowIndex=1:  SeaTunnelRow#tableId=-1 SeaTunnelRow#kind=INSERT: CpiOd, 8520946
2022-12-19 11:01:46,490 INFO  org.apache.seatunnel.connectors.seatunnel.console.sink.ConsoleSinkWriter - subtaskIndex=0 rowIndex=2: SeaTunnelRow#tableId=-1 SeaTunnelRow#kind=INSERT: eQqTs, 1256802974
2022-12-19 11:01:46,490 INFO  org.apache.seatunnel.connectors.seatunnel.console.sink.ConsoleSinkWriter - subtaskIndex=0 rowIndex=3: SeaTunnelRow#tableId=-1 SeaTunnelRow#kind=INSERT: UsRgO, 2053193072
2022-12-19 11:01:46,490 INFO  org.apache.seatunnel.connectors.seatunnel.console.sink.ConsoleSinkWriter - subtaskIndex=0 rowIndex=4: SeaTunnelRow#tableId=-1 SeaTunnelRow#kind=INSERT: jDQJj, 1993016602
2022-12-19 11:01:46,490 INFO  org.apache.seatunnel.connectors.seatunnel.console.sink.ConsoleSinkWriter - subtaskIndex=0 rowIndex=5: SeaTunnelRow#tableId=-1 SeaTunnelRow#kind=INSERT: rqdKp, 1392682764
2022-12-19 11:01:46,490 INFO  org.apache.seatunnel.connectors.seatunnel.console.sink.ConsoleSinkWriter - subtaskIndex=0 rowIndex=6: SeaTunnelRow#tableId=-1 SeaTunnelRow#kind=INSERT: wCoWN, 986999925
2022-12-19 11:01:46,490 INFO  org.apache.seatunnel.connectors.seatunnel.console.sink.ConsoleSinkWriter - subtaskIndex=0 rowIndex=7: SeaTunnelRow#tableId=-1 SeaTunnelRow#kind=INSERT: qomTU, 72775247
2022-12-19 11:01:46,490 INFO  org.apache.seatunnel.connectors.seatunnel.console.sink.ConsoleSinkWriter - subtaskIndex=0 rowIndex=8: SeaTunnelRow#tableId=-1 SeaTunnelRow#kind=INSERT: jcqXR, 1074529204
2022-12-19 11:01:46,490 INFO  org.apache.seatunnel.connectors.seatunnel.console.sink.ConsoleSinkWriter - subtaskIndex=0 rowIndex=9: SeaTunnelRow#tableId=-1 SeaTunnelRow#kind=INSERT: AkWIO, 1961723427
2022-12-19 11:01:46,490 INFO  org.apache.seatunnel.connectors.seatunnel.console.sink.ConsoleSinkWriter - subtaskIndex=0 rowIndex=10: SeaTunnelRow#tableId=-1 SeaTunnelRow#kind=INSERT: hBoib, 929089763
2022-12-19 11:01:46,490 INFO  org.apache.seatunnel.connectors.seatunnel.console.sink.ConsoleSinkWriter - subtaskIndex=0 rowIndex=11: SeaTunnelRow#tableId=-1 SeaTunnelRow#kind=INSERT: GSvzm, 827085798
2022-12-19 11:01:46,491 INFO  org.apache.seatunnel.connectors.seatunnel.console.sink.ConsoleSinkWriter - subtaskIndex=0 rowIndex=12: SeaTunnelRow#tableId=-1 SeaTunnelRow#kind=INSERT: NNAYI, 94307133
2022-12-19 11:01:46,491 INFO  org.apache.seatunnel.connectors.seatunnel.console.sink.ConsoleSinkWriter - subtaskIndex=0 rowIndex=13: SeaTunnelRow#tableId=-1 SeaTunnelRow#kind=INSERT: EexFl, 1823689599
2022-12-19 11:01:46,491 INFO  org.apache.seatunnel.connectors.seatunnel.console.sink.ConsoleSinkWriter - subtaskIndex=0 rowIndex=14: SeaTunnelRow#tableId=-1 SeaTunnelRow#kind=INSERT: CBXUb, 869582787
2022-12-19 11:01:46,491 INFO  org.apache.seatunnel.connectors.seatunnel.console.sink.ConsoleSinkWriter - subtaskIndex=0 rowIndex=15: SeaTunnelRow#tableId=-1 SeaTunnelRow#kind=INSERT: Wbxtm, 1469371353
2022-12-19 11:01:46,491 INFO  org.apache.seatunnel.connectors.seatunnel.console.sink.ConsoleSinkWriter - subtaskIndex=0 rowIndex=16: SeaTunnelRow#tableId=-1 SeaTunnelRow#kind=INSERT: mIJDt, 995616438

并且结尾有一个 Job 总结日志

***********************************************
           Job Statistic Information
***********************************************
Start Time                : 2024-08-29 22:45:29
End Time                  : 2024-08-29 22:45:33
Total Time(s)             :                   4
Total Read Count          :                  32
Total Write Count         :                  32
Total Failed Count        :                   0
***********************************************

全量同步

测试表创建

创建两张一模一样的表 表结构如下：
CREATE TABLE `table1` (
    `id` INT NOT NULL AUTO_INCREMENT,
    `value1` VARCHAR(255) NOT NULL,
    `value2` VARCHAR(255) ,
    `value3` VARCHAR(255) ,
    `value4` VARCHAR(255) ,
    `value5` VARCHAR(255) ,
    `created_at` TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
    `updated_at` TIMESTAMP DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
    PRIMARY KEY (`id`),
    UNIQUE INDEX `idx_value1` (`value1`),
    INDEX `idx_value2_value3` (`value2`, `value3`),
    INDEX `idx_value3_value4_value5` (`value3`, `value4`, `value5`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;
 
CREATE TABLE `table2` (
    `id` INT NOT NULL AUTO_INCREMENT,
    `value1` VARCHAR(255) NOT NULL,
    `value2` VARCHAR(255) ,
    `value3` VARCHAR(255) ,
    `value4` VARCHAR(255) ,
    `value5` VARCHAR(255) ,
    `created_at` TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
    `updated_at` TIMESTAMP DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
    PRIMARY KEY (`id`),
    UNIQUE INDEX `idx_value1` (`value1`),
    INDEX `idx_value2_value3` (`value2`, `value3`),
    INDEX `idx_value3_value4_value5` (`value3`, `value4`, `value5`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;

我们这边使用 navicat 创建了各100000条数据

全量同步配置文件编写

表结构建议手动迁移，自动迁移的表结构会有一些问题，并且不会附加索引。

单表全量

env {
  parallelism = 5
  job.mode = "BATCH"
}
source {
    Jdbc {
        url = "jdbc:mysql://127.0.0.1:3306/mysql?&useUnicode=true&characterEncoding=UTF-8&rewriteBatchedStatements=true"
        driver = "com.mysql.cj.jdbc.Driver"
        connection_check_timeout_sec = 100
        user = "xxx"
        password = "xxx"
        query = "select * from seatunnel.table1"
    }
}
sink {
    jdbc {
        url = "jdbc:mysql://127.0.0.1:2883/mysql?&useUnicode=true&characterEncoding=UTF-8&rewriteBatchedStatements=true"
        driver = "com.mysql.cj.jdbc.Driver"
        user = "xxx@xxx"
        password = "xxx"
        # 自动判断sql语句
        generate_sink_sql = true
        database = seatunnel
        table = table1
    }
}

结果

  ***********************************************
             Job Statistic Information
  ***********************************************
  Start Time                : 2024-08-30 15:05:39
  End Time                  : 2024-08-30 15:05:47
  Total Time(s)             :                   8
  Total Read Count          :              100000
  Total Write Count         :              100000
  Total Failed Count        :                   0
  ***********************************************

多表全量抽取

env {
  parallelism = 5
  job.mode = "BATCH"
}
source {
    Jdbc {
        url = "jdbc:mysql://127.0.0.1:3306/mysql?&useUnicode=true&characterEncoding=UTF-8&rewriteBatchedStatements=true"
        driver = "com.mysql.cj.jdbc.Driver"
        connection_check_timeout_sec = 100
        user = "xxx"
        password = "xxx"
    table_list = [
      {
      table_path = "seatunnel.table1"
      },
      {
      table_path = "seatunnel.table2"
      query = "select * from seatunnel.table2 where id > 100"
      }
    ]
    }
}
sink {
    jdbc {
        url = "jdbc:mysql://127.0.0.1:2883/mysql?&useUnicode=true&characterEncoding=UTF-8&rewriteBatchedStatements=true"
        driver = "com.mysql.cj.jdbc.Driver"
        user = "xxx@xxx"
        password = "xxx"
        # 自动判断sql语句
        generate_sink_sql = true
        database = seatunnel
    table_list = ["seatunnel.table1","seatunnel.table2"]
    }
}

结果

  ***********************************************
             Job Statistic Information
  ***********************************************
  Start Time                : 2024-08-30 15:10:09
  End Time                  : 2024-08-30 15:10:20
  Total Time(s)             :                  10
  Total Read Count          :              200000
  Total Write Count         :              200000
  Total Failed Count        :                   0
  ***********************************************

增量同步配置文件编写

对于增量同步，简单的方法是在文件编写时，通过 Query 编写 id 或 updatetime 做增量。

env {
  parallelism = 1
  job.mode = "BATCH"
}
source {
    Jdbc {
        url = "jdbc:mysql://127.0.0.1:3306/mysql?&useUnicode=true&characterEncoding=UTF-8&rewriteBatchedStatements=true"
        driver = "com.mysql.cj.jdbc.Driver"
        connection_check_timeout_sec = 100
        user = "xxx"
        password = "xxx"
        query = "SELECT * FROM seatunnel.table1 WHERE updatetime > '2024-01-01' "
    }
}
sink {
    jdbc {
        url = "jdbc:mysql://127.0.0.1:2883/mysql?&useUnicode=true&characterEncoding=UTF-8&rewriteBatchedStatements=true"
        driver = "com.mysql.cj.jdbc.Driver"
        user = "xxx@xxx"
        password = "xxx"
        generate_sink_sql = true
        database = seatunnel
        table = table1 
    }
}

在输出端的时候会根据主键进行插入与更新操作，但是这种需要从每次配置配置文件的方案比较繁琐，我更加推荐使用 Apache DolphinScheduler 配合 SeaTunnel 进行操作创建一个工作流。

从输出端获取最大时间或者 id 通过 DolphinScheduler 的工作流变量进行传输。

env {
  parallelism = 1
  job.mode = "BATCH"
}
source {
    Jdbc {
        url = "jdbc:mysql://127.0.0.1:3306/mysql?&useUnicode=true&characterEncoding=UTF-8&rewriteBatchedStatements=true"
        driver = "com.mysql.cj.jdbc.Driver"
        connection_check_timeout_sec = 100
        user = "xxx"
        password = "xxx"
        query = "SELECT * FROM seatunnel.table1 WHERE updatetime > ${max_id} "
    }
}
sink {
    jdbc {
        url = "jdbc:mysql://127.0.0.1:2883/mysql?&useUnicode=true&characterEncoding=UTF-8&rewriteBatchedStatements=true"
        driver = "com.mysql.cj.jdbc.Driver"
        user = "xxx@xxx"
        password = "xxx"
        generate_sink_sql = true
        database = seatunnel
        table = table1 
    }
}

多表方案同上

CDC同步配置文件编写

手动同步表结构

由于 SeaTunnel 的 oceanbase 组件还是有所问题，表结构同步 遇到报错比较麻烦，这一步还是手动同步。

检查MySQL Binlog状态

赋予用户所需权限

mysql> GRANT SELECT, RELOAD, SHOW DATABASES, REPLICATION SLAVE, REPLICATION CLIENT ON *.* TO 'user' IDENTIFIED BY 'password';
 
mysql> FLUSH PRIVILEGES;

检查binlog日志是否开启

mysql> show variables where variable_name in ('log_bin', 'binlog_format', 'binlog_row_image', 'gtid_mode', 'enforce_gtid_consistency');
+--------------------------+----------------+
| Variable_name            | Value          |
+--------------------------+----------------+
| binlog_format            | ROW            |
| binlog_row_image         | FULL           |
| enforce_gtid_consistency | ON             |
| gtid_mode                | ON             |
| log_bin                  | ON             |
+--------------------------+----------------+
5 rows in set (0.00 sec)

如果不一致 请自行更改mysql.cnf文件。

在大型数据库创建一致性快照时，可能会存在读超时，请合理配置！

interactive_timeoutwait_timeout

在处理完准备工作之后编写配置文件。

env {
  parallelism = 1
  job.mode = "STREAMING"
  checkpoint.interval = 10000
}
 
source {
  MySQL-CDC {
    base-url = "jdbc:mysql://127.0.0.1:3306/mysql"
    username = "xxx"
    password = "xxx@xxx"
    table-names = ["seatunnel.table1", "seatunnel.table2"]
    
    startup.mode = "initial"
  }
}
 
sink {
    jdbc {
        url = "jdbc:mysql://127.0.0.1:2883/mysql?&useUnicode=true&characterEncoding=UTF-8&rewriteBatchedStatements=true"
        driver = "com.mysql.cj.jdbc.Driver"
        user = "xxx@xxx"
        password = "xxx"
        database = "seatunnel"  # 目标数据库
        table-names = ["seatunnel.table1", "seatunnel.table2"]
        generate_sink_sql = true     # 自动生成 SQL
    }
}

正常启动之后会进行历史数据迁移，再进行 CDC 变更。

注意:

启动之后会根据配置的表和startup.mode选择的模式进行不同的操作。

startup.mode操作如下: initial 启动时同步历史数据，然后同步增量数据earliest ，从最早的偏移量启动 latest 从最新偏移量启动specific，从用户提供的特定偏移量启动。

如果使用specific，需要添加startup.specific-offset.file binlog文件名startup.specific-offset.pos binlog偏转量。

本文完！