关于数据同步:数据传输-利用-DTLE-将-MySQL-数据同步到-DBLE

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作者：任仲禹

爱可生 DBA 团队成员，善于故障剖析和性能优化，文章相干技术问题，欢送大家一起探讨。

本文起源：原创投稿

* 爱可生开源社区出品，原创内容未经受权不得随便应用，转载请分割小编并注明起源。

背景

源于某客户的需要，存在线上某业务 MySQL 库因为数据量及业务读写压力较大，须要将业务数据迁徙到 DBLE 分布式数据库，但同时因为业务为 7x24h，可能停机的工夫窗口较短，所以须要思考数据实时同步的计划。

过往 DBLE 的业务上线根本为全新部署，数据实时同步的状况极少施行，去年 DTLE 公布后这一问题失去了些改善，明天咱们来实际下。

环境筹备

1. 指标端 DBLE 集群部署

  • 装置 DBLE 软件、后端分片 MySQL 库过程略

    • DBLE 版本 3.20.10.8、MySQL 版本 5.7.25
  • sharding.xml
  <?xml version="1.0"?>
  <!DOCTYPE dble:sharding SYSTEM "sharding.dtd">
  <dble:sharding xmlns:dble="http://dble.cloud/" version="4.0">
      <schema name="dtle" sqlMaxLimit="-1" shardingNode="dn_01">
          <singleTable name="gtid_executed_v4" shardingNode="dn_01" sqlMaxLimit="-1"></singleTable>
      </schema>
      <schema name="ren" sqlMaxLimit="-1" shardingNode="dn_01">
          <shardingTable name="test" shardingNode="dn_01,dn_02,dn_03,dn_04" sqlMaxLimit="-1" shardingColumn="id" function="func_jumphash"></shardingTable>
      </schema>
      <shardingNode name="dn_03" dbGroup="dh-mysql-cluster02" database="dh_dn_03"></shardingNode>
      <shardingNode name="dn_04" dbGroup="dh-mysql-cluster02" database="dh_dn_04"></shardingNode>
      <shardingNode name="dn_02" dbGroup="dh-mysql-cluster01" database="dh_dn_02"></shardingNode>
      <shardingNode name="dn_01" dbGroup="dh-mysql-cluster01" database="dh_dn_01"></shardingNode>
      <function name="func_jumphash" class="jumpStringHash">
          <property name="partitionCount">4</property>
          <property name="hashSlice">0:-1</property>
      </function>
  </dble:sharding>
  • db.xml
  <?xml version="1.0"?>
  <!DOCTYPE dble:db SYSTEM "db.dtd">
  <dble:db xmlns:dble="http://dble.cloud/" version="4.0">
      <dbGroup name="dh-mysql-cluster02" rwSplitMode="0" delayThreshold="-1">
          <heartbeat timeout="0" errorRetryCount="0">show slave status</heartbeat>
          <dbInstance name="10.186.61.13-3326-dh-1" url="10.186.61.13:3326" user="dbleuser" password="jpfmxIeMt1vxAJ6zd6Q10PGRRi+Qj023Dl+YXuOr3C4VXTdV5+GJaOIv5iVmWCwpXcucn/zi02HVlT7ADX+m6Q==" maxCon="100" minCon="10" primary="true" readWeight="0" id="mysql-i63009" usingDecrypt="true"></dbInstance>
      </dbGroup>
      <dbGroup name="dh-mysql-cluster01" rwSplitMode="0" delayThreshold="-1">
          <heartbeat timeout="0" errorRetryCount="0">show slave status</heartbeat>
          <dbInstance name="10.186.61.11-3316-dh-1" url="10.186.61.11:3316" user="dbleuser" password="QQWRF80AGNbx4jIAx/b2Ww7Myol1+ntlyzGmA1A3PXVISmRD/i5pgRnLLwYsXoLmH0jiv1qZAkqIBHv6Yg/XAg==" maxCon="100" minCon="10" primary="true" readWeight="0" id="mysql-47vn84" usingDecrypt="true"></dbInstance>
      </dbGroup>
  </dble:db>
  • user.xml
  <?xml version="1.0"?>
  <!DOCTYPE dble:user SYSTEM "user.dtd">
  <dble:user xmlns:dble="http://dble.cloud/" version="4.0">
      <managerUser name="root" password="CrjpLhvVJkHk0EPW35Y07dUeTimf52zMqClYQkIAN3/dqiG1DVUe9Zr4JLh8Kl+1KH1zd7YTKu5w04QgdyQeDw==" usingDecrypt="true"></managerUser>
      <shardingUser name="ren" schemas="ren,dtle" password="P+C2KazQiS3ZZ6uojBJ91MZIqYqGczspQ/ebyBZOC9xKAAkAFrqEDC9OPn/vObAyO4P8Zu3vHQJ+rljM040Kdg==" usingDecrypt="true" readOnly="false" maxCon="0" blacklist="default_black_list"></shardingUser>
  </dble:user>

2. 源端和指标端测试表创立

  • 源端 MySQL 数据库软件装置略
  • 源端 MySQL 与指标端 DBLE 都须要创立测试表名：test
  use ren;
  CREATE TABLE `test` (`id` int(11) NOT NULL AUTO_INCREMENT,
    `name` varchar(20) COLLATE utf8mb4_bin DEFAULT NULL,
    `city` varchar(20) COLLATE utf8mb4_bin DEFAULT NULL,
    `dt` datetime DEFAULT CURRENT_TIMESTAMP,
    PRIMARY KEY (`id`),
    KEY `idx_ctiy` (`city`)
  ) ENGINE=InnoDB;

3. 部署单节点 DTLE

  • DTLE 社区版本 GitHub 下载地址：https://github.com/actiontech…

  • 下载实现后间接 rpm 装置（本示例应用外部 QA 验证版本）

    • rpm -ivh –prefix=/data/dtle dtle-ee-9.9.9.9.x86_64.rpm
  • 装置实现确认启动失常
  # curl -XGET "127.0.0.1:4646/v1/nodes" -s | jq
  [
    {
      "Address": "127.0.0.1",
      "ID": "223c31b4-05cd-a763-b3e7-dbea6d416576",
      "Datacenter": "dc1",
      "Name": "nomad0",
      "NodeClass": "","Version":"1.1.2","Drain": false,"SchedulingEligibility":"eligible","Status":"ready","StatusDescription":"",
      "Drivers": {
        "dtle": {
          "Attributes": {
            "driver.dtle.full_version": "9.9.9.9-master-a65ee13",
            "driver.dtle": "true",
            "driver.dtle.version": "9.9.9.9"
          },
          "Detected": true,
          "Healthy": true,     
          "HealthDescription": "Healthy",
          "UpdateTime": "2022-02-28T07:45:15.650289984Z"
  ·········
  ]

创立 MySQL-To-DBLE 工作

一、全量同步

1. 筹备 job 文件
# cat job.json
{
  "Job": {
    "ID": "mysqlToDBLE",
    "Datacenters": ["dc1"],
    "TaskGroups": [{
        "Name": "src",
        "Tasks": [{
          "Name": "src",
          "Driver": "dtle",
          "Config": {"Gtid": "","ReplicateDoDb": [{"TableSchema":"ren","Tables": [{"TableName":"test"}]
            }],
            "ConnectionConfig": {
              "Host": "10.186.61.11",
              "Port": 3306,
              "User": "root",
              "Password": "root"
            }
          }
        }]
      }, {
        "Name": "dest",
        "Tasks": [{
          "Name": "dest",
          "Driver": "dtle",
          "Config": {
            "ConnectionConfig": {
              "Host": "10.186.61.10",
              "Port": 8066,
              "User": "ren",
              "Password": "ren"
            }
          }
        }]
    }]
  }
}
2. 筹备全量复制数据
  • 源端 MySQL 库执行
mysql> insert into test values(1,'ren','sh',now());
mysql> insert into test values(2,'jack','bj',now());
mysql> insert into test values(3,'tom','sz',now());
3. 启动同步工作
# curl -XPOST "http://127.0.0.1:4646/v1/jobs" -d @job.json -s| jq
{
  "EvalID": "88ab4a42-98b7-696e-0f98-08c1fe3ee4bd",
  "EvalCreateIndex": 12310,
  "JobModifyIndex": 12310,
  "Warnings": "","Index": 12310,"LastContact": 0,"KnownLeader": false
}
4. 查看同步状况
  • 确认全量数据同步实现
# 指标端 DBLE 中执行
mysql> use ren;
Database changed
mysql> show tables;
+------------------+
| Tables_in_ren    |
+------------------+
| test             |
| gtid_executed_v4 |
+------------------+
2 rows in set (0.01 sec)

mysql> select * from test;
+----+------+------+---------------------+
| id | name | city | dt                  |
+----+------+------+---------------------+
|  1 | ren  | sh   | 2022-03-07 06:53:30 |
|  2 | jack | bj   | 2022-03-07 06:53:41 |
|  3 | tom  | sz   | 2022-03-07 06:53:59 |
+----+------+------+---------------------+
3 rows in set (0.01 sec)

# 源端 MySQL 写入增量测试数据
mysql> insert into test select null,'mike','nj',now();
Query OK, 1 row affected (0.01 sec)
Records: 1  Duplicates: 0  Warnings: 0
········
mysql> insert into test select null,'mike4','nj',now();
Query OK, 1 row affected (0.01 sec)
Records: 1  Duplicates: 0  Warnings: 0

mysql> update test set city = 'sh' where name like 'mike%';
Query OK, 4 rows affected (0.01 sec)
Rows matched: 4  Changed: 4  Warnings: 0

mysql> select * from test;
+----+-------+------+---------------------+
| id | name  | city | dt                  |
+----+-------+------+---------------------+
|  1 | ren   | sh   | 2022-03-07 06:53:30 |
|  2 | jack  | bj   | 2022-03-07 06:53:41 |
|  3 | tom   | sz   | 2022-03-07 06:53:59 |
| 45 | mike  | sh   | 2022-03-07 08:03:57 |
| 46 | mike2 | sh   | 2022-03-07 08:04:02 |
| 47 | mike3 | sh   | 2022-03-07 08:04:05 |
| 48 | mike4 | sh   | 2022-03-07 08:04:09 |
+----+-------+------+---------------------+
7 rows in set (0.01 sec)

# 指标端 DBLE 查看增量同步状况
mysql> select * from test;
+----+-------+------+---------------------+
| id | name  | city | dt                  |
+----+-------+------+---------------------+
|  1 | ren   | sh   | 2022-03-07 06:53:30 |
|  2 | jack  | bj   | 2022-03-07 06:53:41 |
|  3 | tom   | sz   | 2022-03-07 06:53:59 |
| 45 | mike  | sh   | 2022-03-07 08:03:57 |
| 46 | mike2 | sh   | 2022-03-07 08:04:02 |
| 47 | mike3 | sh   | 2022-03-07 08:04:05 |
| 48 | mike4 | sh   | 2022-03-07 08:04:09 |
+----+-------+------+---------------------+
7 rows in set (0.04 sec)

mysql> explain select * from test where id  = 1;
+---------------+----------+----------------------------------+
| SHARDING_NODE | TYPE     | SQL/REF                          |
+---------------+----------+----------------------------------+
| dn_01         | BASE SQL | select * from test where id  = 1 |
+---------------+----------+----------------------------------+
1 row in set (0.03 sec)

二、基于 GTID 位点增量同步

1. 销毁全量同步工作
# cd /data/dtle/usr/bin/
# ll
total 188836
-rwxr-xr-x 1 root root 107811060 Mar 17  2020 consul
-rwxr-xr-x 1 root root  85550512 Jun 22  2021 nomad
# ./nomad job status
ID                 Type     Priority  Status   Submit Date
mysqlToDBLE        service  50        running  2022-03-07T15:47:31+08:00
mysqltoMysql-sync  service  50        running  2022-03-03T16:06:10+08:00
# ./nomad job stop -purge mysqlToDBLE
·······
  ⠙ Deployment "433ed3d4" successful
·······
# ./nomad job status
ID                 Type     Priority  Status   Submit Date
mysqltoMysql-sync  service  50        running  2022-03-03T16:06:10+08:00
2. 记录源端 GTID 位点
# 记录源端 MySQL 须要开始的 GTID 位点
mysql> show master status\G
*************************** 1. row ***************************
             File: mysql-bin.000178
········
Executed_Gtid_Set: 442dbe92-00c3-11ec-a0cf-02000aba3d0b:1-49705119,
cdc6fb62-00c2-11ec-a259-02000aba3d0a:1-3555
1 row in set (0.01 sec)
# 插入增量数据（模仿业务新增数据）mysql> insert into test select 88,'sync01','wh',now();
mysql> insert into test select 99,'sync02','wh',now();
# 源端 MySQL 确认数据已插入
mysql> select * from test;
+----+--------+------+---------------------+
| id | name   | city | dt                  |
+----+--------+------+---------------------+
|  1 | ren    | sh   | 2022-03-07 06:53:30 |
········
| 48 | mike4  | sh   | 2022-03-07 08:04:09 |
| 88 | sync01 | wh   | 2022-03-07 08:24:20 |
| 99 | sync02 | wh   | 2022-03-07 08:24:31 |
+----+--------+------+---------------------+
9 rows in set (0.00 sec)
# 指标端 DBLE 数据因同步 job 已销毁，新插入数据未同步过去
mysql> select * from test;
+----+-------+------+---------------------+
| id | name  | city | dt                  |
+----+-------+------+---------------------+
|  1 | ren   | sh   | 2022-03-07 06:53:30 |
········
| 48 | mike4 | sh   | 2022-03-07 08:04:09 |
+----+-------+------+---------------------+
7 rows in set (0.00 sec)
3. 筹备增量同步 job 文件
# cat job.json
{
  "Job": {
    "ID": "mysqlToDBLE",
    "Datacenters": ["dc1"],
    "TaskGroups": [{
        "Name": "src",
        "Tasks": [{
          "Name": "src",
          "Driver": "dtle",
          "Config": {
            "Gtid": "442dbe92-00c3-11ec-a0cf-02000aba3d0b:1-49705119,cdc6fb62-00c2-11ec-a259-02000aba3d0a:1-3555",
            "ReplicateDoDb": [{
              "TableSchema": "ren",
              "Tables": [{"TableName": "test"}]
            }],
            "ConnectionConfig": {
              "Host": "10.186.61.11",
              "Port": 3306,
              "User": "root",
              "Password": "root"
            }
          }
        }]
      }, {
        "Name": "dest",
        "Tasks": [{
          "Name": "dest",
          "Driver": "dtle",
          "Config": {
            "ConnectionConfig": {
              "Host": "10.186.61.10",
              "Port": 8066,
              "User": "ren",
              "Password": "ren"
            }
          }
        }]
    }]
  }
}
4. 开始增量同步工作
# curl -XPOST "http://127.0.0.1:4646/v1/jobs" -d @job.json -s |jq
{
  "EvalID": "cad6fb19-62d3-67aa-6f5c-fbb79f8016d2",
  "EvalCreateIndex": 12855,
  "JobModifyIndex": 12855,
  "Warnings": "","Index": 12855,"LastContact": 0,"KnownLeader": false
}
5. 查看同步状况
# 指标端 DBLE 中查看到 GTID 位点之后的数据已同步过去
mysql> select * from test;
+-----+--------+------+---------------------+
| id  | name   | city | dt                  |
+-----+--------+------+---------------------+
|   1 | ren    | sh   | 2022-03-07 06:53:30 |
|  48 | mike4  | sh   | 2022-03-07 08:04:09 |
·········
|  88 | sync01 | wh   | 2022-03-07 08:24:20 |
|  99 | sync02 | wh   | 2022-03-07 08:24:31 |
+-----+--------+------+---------------------+
11 rows in set (0.06 sec)
6. 其它 DML 及 DDL 同步
  • 验证下其它 update、delete 语句及 DDL 语句同步状况
# 源端 MySQL 执行操作
mysql> delete from test where id >= 100;
Query OK, 2 rows affected (0.01 sec)
mysql> delete from test where id > 3;
Query OK, 6 rows affected (0.01 sec)
mysql> update test set name = 'actionsky' where id = 3;
Query OK, 1 row affected (0.00 sec)
Rows matched: 1  Changed: 1  Warnings: 0

# 指标端 DBLE 查看同步状况
mysql> select * from test;
+----+-----------+------+---------------------+
| id | name      | city | dt                  |
+----+-----------+------+---------------------+
|  1 | ren       | sh   | 2022-03-07 06:53:30 |
|  2 | jack      | bj   | 2022-03-07 06:53:41 |
|  3 | actionsky | sz   | 2022-03-07 06:53:59 |
+----+-----------+------+---------------------+
3 rows in set (0.01 sec)

# 源端 MySQL 执行 DDL 操作
mysql> alter table test add column info varchar(20) default 'hello';
mysql> update test set info = 'thanks' where id = 3;
mysql> alter table test add index idx_info(`info`);

# 指标端 DBLE 能够进行 DDL 同步（篇幅所限，实际上 DBLE 兼容的 DDL 语句都能同步胜利）mysql> select * from test;
+----+-----------+------+---------------------+--------+
| id | name      | city | dt                  | info   |
+----+-----------+------+---------------------+--------+
|  1 | ren       | sh   | 2022-03-07 06:53:30 | hello  |
|  2 | jack      | bj   | 2022-03-07 06:53:41 | hello  |
|  3 | actionsky | sz   | 2022-03-07 06:53:59 | thanks |
+----+-----------+------+---------------------+--------+
3 rows in set (0.02 sec)

mysql> show create table test\G
*************************** 1. row ***************************
       Table: test
Create Table: CREATE TABLE `test` (`id` int(11) NOT NULL AUTO_INCREMENT,
  `name` varchar(20) COLLATE utf8mb4_bin DEFAULT NULL,
  `city` varchar(20) COLLATE utf8mb4_bin DEFAULT NULL,
  `dt` datetime DEFAULT CURRENT_TIMESTAMP,
  `info` varchar(20) COLLATE utf8mb4_bin DEFAULT 'hello',
  PRIMARY KEY (`id`),
  KEY `idx_ctiy` (`city`),
  KEY `idx_info` (`info`)
) ENGINE=InnoDB AUTO_INCREMENT=89 DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_bin
1 row in set (0.01 sec)

配置 MySQL-To-DBLE 注意事项

1. 检测连贯失败问题

  • 问题形容：DTLE 配置 JOB 过程中，“检测连贯”失败，nomad 日志报错 ERROR 1064 (HY000): java.sql.SQLSyntaxErrorException: illegal value[TRUE]
  • 起因：DTLE 下发的检测客户端语句 set autocommit=true，在 DBLE 某些版本中不反对
  • 解决：降级 DBLE 到 3.20.10.6 版本及之后

2. 工作启动后同步失败报 ’dtle’ 不存在

  • 问题形容：DTLE 同步工作启动后报错，nomad 日志呈现 Can’t create database ‘dtle’ that doesn’t exists.

  • 起因：

    • DTLE To MySQL，不会呈现该种报错
    • DTLE To DBLE，因为 DBLE 中间件中 schema 的创立形式与一般 MySQL 不统一，所以该 create 语法不反对

  • 解决：

    • 须要对 DBLE 进行额定的 Schema/Table 配置，参考前文 sharding.xml 和 user.xml 中相干配置

3. 工作启动后同步失败报 ’Data too long’

  • 问题形容：DTLE 同步工作启动后报错，nomad 日志呈现“applier error/restart: insert gno: Error 1406: Data too long for column ‘source_uuid’ at row 1”

  • 起因：

    • DTLE 在 DBLE 中创立的表 gtid_executed_v4 中，字段 source_uuid 的 Binary 数据类型长度不够
    • 也可通过排查 DBLE 中间件日志（core/log/dble.log），报错信息为“execute sql err : errNo:1406 Data too long for column ‘source_uuid’ at row 1”

  • 解决：

    • DBLE 中，批改字段
    • alter table gtid_executed_v4 modify column source_uuid binary(60);

论断

  • DTLE 目前性能根本能够满足 MySQL -> DBLE 间数据施行同步需要，不过须要留神的是，不倡议采纳本文所提到的 全量同步 形式

    • 生产环境施行因为 MySQL 老库数据量较大，能够先将数据全量逻辑备份进去（需记录 GTID 位点），再通过 DBLE 自带的 split 工具进行拆分后进行导入，而后再应用 DTLE 基于 GTID 位点增量同步 的形式进行数据同步
  • DTLE 创立 To-DBLE 工作前须要关注下前文所示 注意事项，尤其是提前准备好 sharding.xml、user.xml 文件并创立好 DTLE 的元数据表 gtid_executed_v4。

正文完
数据同步
发表至： 数据同步
2022-03-29
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