gravity 是摩拜单车出票的一个 异构/同构 数据复制通道软件，提供主流软件的支持，并支持k8s云原生。比较看好它的发展。 项目地址： https://github.com/moiot/gravity 官方文档：https://githu
gravity 是摩拜单车出票的一个 异构/同构 数据复制通道软件，提供主流软件的支持，并支持k8s云原生。比较看好它的发展。
项目地址： https://github.com/moiot/gravity
官方文档：https://github.com/moiot/gravity/blob/master/docs/2.0/01-quick-start.md
gravity的编译和部署不是这里的重点，我们直接跳过。
gravity的部署：
cd /root/ git clone https://github.com/moiot/gravity.git cd gravity && make mkdir /usr/local/gravity/ cd /usr/local/gravity/ cp /root/gravity/bin/gravity /usr/local/gravity/ 配置文件这里先忽略，下面是我的架构图：
业务场景：
一个老表，随着业务量增大，考虑到分表，按照 user_id 做hash取模拆分，然后业务层面去做数据CRUD操作。
数据表如下：
create database testdb; use testdb; CREATE TABLE `gravity_t1` ( `id` int(10) unsigned NOT NULL AUTO_INCREMENT COMMENT '自增id', `user_id` int(10) unsigned NOT NULL DEFAULT '0' COMMENT '用户id', `s_status` tinyint(1) unsigned NOT NULL DEFAULT '0' COMMENT '状态', PRIMARY KEY (`id`), KEY `idx_uid` (`user_id`) USING BTREE ) COMMENT = '测试表' ENGINE=InnoDB AUTO_INCREMENT=1 DEFAULT CHARSET=utf8mb4; 准备拆分后的4个分表： use testdb; create table t1_shard1 LIKE gravity_t1 ; create table t1_shard2 LIKE gravity_t1 ; create table t1_shard3 LIKE gravity_t1 ; create table t1_shard4 LIKE gravity_t1 ;测试数据库连接方式：
数据库地址：192.168.2.4 超级账号： dts 密码： dts 假设业务用的普通账号叫rd ，密码无所谓。造些测试用的数据：
for i in {1..10000} ; do mysql -hdts -pdts -h 192.168.2.4 -e "insert into testdb.gravity_t1 (user_id,s_status) values (\"$RANDOM\",'0');" done结果大致这样：
[test] > select count(*) from gravity_t1 ; +----------+ | count(*) | +----------+ | 10000 | +----------+ 1 row in set (0.007 sec) [testdb] > select (user_id%4) as hash_id,count(*) FROM gravity_t1 group by (user_id%4); +---------+----------+ | hash_id | count(*) | +---------+----------+ | 0| 2537 | | 1 | 2419 | | 2 | 2509 | | 3| 2535 | +---------+----------+ 4 rows in set (0.009 sec)shard1的配置文件，内容如下：
cat config_shard1.toml
# name 必填，这里保持每个配置文件的唯一性 name = "shard1" # 内部用于保存位点、心跳等事项的库名，默认为 _gravity ， 实测发现这里改了名字也没用，保持默认即可 internal-db-name = "_gravity" # # Input 插件的定义，此处定义使用 mysql # [input] type = "mysql" mode = "replication" [input.config.source] host = "192.168.2.4" username = "dts" password = "dts" port = 3306 # # Output 插件的定义，此处使用 mysql # [output] type = "mysql" [output.config.target] host = "192.168.2.4" username = "dts" password = "dts" port = 3306 # 路由规则的定义 [[output.config.routes]] match-schema = "testdb" match-table = "gravity_t1" target-schema = "testdb" target-table = "t1_shard1" # 这个target-table 代表的是需要写入到的分片名称，每个gravity实例的配置中都需要修改开4个窗口演示：
cd /usr/local/gravity/ ./bin/gravity -config config_shard1.toml -http-addr ":8083" ./bin/gravity -config config_shard2.toml -http-addr ":8184" ./bin/gravity -config config_shard3.toml -http-addr ":8185" ./bin/gravity -config config_shard4.toml -http-addr ":8186"TIPS：
如果我们此时开了数据库的general_log的话， 能看到gravity到dest端是使用replace into方式插入全量数据的。然后再根据启动时候监听的binlog 实现增量数据的追平操作。
然后，看下 gravity 自动生成的库，存放都是和数据复制相关的信息：
[testdb] > show tables from _gravity ; +----------------------+ | Tables_in__gravity | +----------------------+ | gravity_heartbeat_v2 | | gravity_positions | +----------------------+ 2 rows in set (0.000 sec) [testdb] > select * from _gravity.gravity_heartbeat_v2; +--------+--------+----------------------------+----------------------------+ | name | offset | update_time_at_gravity | update_time_at_source | +--------+--------+----------------------------+----------------------------+ | shard1 | 57 | 2020-03-26 16:19:08.070483 | 2020-03-26 16:19:08.070589 | | shard2 | 51 | 2020-03-26 16:19:07.469721 | 2020-03-26 16:19:07.469811 | | shard3 | 50 | 2020-03-26 16:19:09.135751 | 2020-03-26 16:19:09.135843 | | shard4 | 48 | 2020-03-26 16:19:08.448371 | 2020-03-26 16:19:08.448450 | +--------+--------+----------------------------+----------------------------+ 4 rows in set (0.001 sec) [testdb] > select * from _gravity.gravity_positions\G *************************** 1. row *************************** name: shard1 stage: stream position: {"current_position":{"binlog-name":"mysql-bin.000014","binlog-pos":28148767,"binlog-gtid":"fd2adbd9-e263-11e8-847a-141877487b3d:1-2600359"},"start_position":{"binlog-name":"mysql-bin.000014","binlog-pos":12866955,"binlog-gtid":"fd2adbd9-e263-11e8-847a-141877487b3d:1-2559919"}} created_at: 2020-03-26 16:16:14 updated_at: 2020-03-26 16:19:26 *************************** 2. row *************************** name: shard2 stage: stream position: {"current_position":{"binlog-name":"mysql-bin.000014","binlog-pos":28155813,"binlog-gtid":"fd2adbd9-e263-11e8-847a-141877487b3d:1-2600366"},"start_position":{"binlog-name":"mysql-bin.000014","binlog-pos":16601348,"binlog-gtid":"fd2adbd9-e263-11e8-847a-141877487b3d:1-2569941"}} created_at: 2020-03-26 16:16:31 updated_at: 2020-03-26 16:19:29 *************************** 3. row *************************** name: shard3 stage: stream position: {"current_position":{"binlog-name":"mysql-bin.000014","binlog-pos":28151964,"binlog-gtid":"fd2adbd9-e263-11e8-847a-141877487b3d:1-2600363"},"start_position":{"binlog-name":"mysql-bin.000014","binlog-pos":20333055,"binlog-gtid":"fd2adbd9-e263-11e8-847a-141877487b3d:1-2579960"}} created_at: 2020-03-26 16:16:35 updated_at: 2020-03-26 16:19:29 *************************** 4. row *************************** name: shard4 stage: stream position: {"current_position":{"binlog-name":"mysql-bin.000014","binlog-pos":28152473,"binlog-gtid":"fd2adbd9-e263-11e8-847a-141877487b3d:1-2600364"},"start_position":{"binlog-name":"mysql-bin.000014","binlog-pos":24076960,"binlog-gtid":"fd2adbd9-e263-11e8-847a-141877487b3d:1-2589987"}} created_at: 2020-03-26 16:16:40 updated_at: 2020-03-26 16:19:29 4 rows in set (0.000 sec)TIPS：
到这一步，我们的4个分表的数据同步都配好了，我们可以再插入几条数据测试下。
原始和拆分表的数据条数对比：
[testdb] > select (user_id%4) as hash_id,count(*) FROM gravity_t1 group by (user_id%4); +---------+----------+ | hash_id | count(*) | +---------+----------+ | 0 | 2537 | | 1 | 2419 | | 2 | 2509 | | 3 | 2535 | +---------+----------+ 4 rows in set (0.009 secselect count(*) FROM t1_shard1 where user_id%4=0; select count(*) FROM t1_shard2 where user_id%4=1; select count(*) FROM t1_shard3 where user_id%4=2; select count(*) FROM t1_shard4 where user_id%4=3;先做一次对分表中不需要的数据的删除操作，防止后期切换后删除数据量过大：
delete from t1_shard1 where user_id %4!=0; delete from t1_shard2 where user_id %4!=1; delete from t1_shard3 where user_id %4!=2; delete from t1_shard4 where user_id %4!=3; ## 注意：生产环境大表的删除操作，建议使用pt-archiver进行然后，再到原始表和分表中查询对比下数据是否一致：
select (user_id%4),count(*) as hash_id FROM gravity_t1 group by (user_id%4); select count(*) FROM t1_shard1 where user_id%4=0; select count(*) FROM t1_shard2 where user_id%4=1; select count(*) FROM t1_shard3 where user_id%4=2; select count(*) FROM t1_shard4 where user_id%4=3;然后，等低峰期进行操作。
1、dba对涉及到的业务账号 对这个大表写权限回收掉
revoke insert,update,delete on testdb.gravity_t1 from rd@'%'; flush hosts; flush tables;2、通知业务方发版，切换数据库连接到4个新表
3、切换完成后，dba再执行一次删除各个分表脏数据的操作，
delete from t1_shard1 where user_id %4!=0; delete from t1_shard2 where user_id %4!=1; delete from t1_shard3 where user_id %4!=2; delete from t1_shard4 where user_id %4!=3;4、打开4个新表的写权限
GRANT select,insert,update,delete on testdb.t1_shard1 TO rd@'%'; GRANT select,insert,update,delete on testdb.t1_shard2 TO rd@'%'; GRANT select,insert,update,delete on testdb.t1_shard3 TO rd@'%'; GRANT select,insert,update,delete on testdb.t1_shard4 TO rd@'%';5、然后，通知业务方测试。
6、业务方验证无问题后收工。至此，单表 拆分为分表的操作全部完成。
7、回退方案，待补充 （打开gravity的双向复制？？）