Sharding JDBC分库分表怎么配置

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分库分表配置

分库需要两个以上数据源，这里配置test0,test1两个数据库

spring.shardingsphere.datasource.names=test0,test1#test0spring.shardingsphere.datasource.test0.type=com.zaxxer.hikari.HikariDataSourcespring.shardingsphere.datasource.test0.driver-class-name=com.mysql.cj.jdbc.Driverspring.shardingsphere.datasource.test0.jdbcUrl=jdbc:mysql://127.0.0.1:3306/test0spring.shardingsphere.datasource.test0.username=spring.shardingsphere.datasource.test0.password=#test1spring.shardingsphere.datasource.test1.type=com.zaxxer.hikari.HikariDataSourcespring.shardingsphere.datasource.test1.driver-class-name=com.mysql.cj.jdbc.Driverspring.shardingsphere.datasource.test1.jdbcUrl=jdbc:mysql://127.0.0.1:3306/test1spring.shardingsphere.datasource.test1.username=spring.shardingsphere.datasource.test1.password=

配置分库策略 按照user_id % 2 进行分库

# 指定分片列名称的 shardingColumnspring.shardingsphere.sharding.default-database-strategy.inline.sharding-column=user_id# 指定分片算法行表达式的 algorithmExpressionspring.shardingsphere.sharding.default-database-strategy.inline.algorithm-expression=test$->{user_id % 2}

配置绑定表和广播表

# 设置绑定表spring.shardingsphere.sharding.binding-tables[0]=health_record,health_task# 设置广播表spring.shardingsphere.sharding.broadcast-tables[0]=health_level

设置分表策略，按照 record_id % 2 进行分表

# user 如果不加这个，数据会随机插入数据库中spring.shardingsphere.sharding.tables.user.actual-data-nodes=test$->{[0,1]}.user#路由到 test0 否则会随意添加到两个数据库中spring.shardingsphere.sharding.tables.other_table.actual-data-nodes=test$->{0}.other_table# health_recordspring.shardingsphere.sharding.tables.health_record.actual-data-nodes=test$->{0..1}.health_record$->{0..1}spring.shardingsphere.sharding.tables.health_record.table-strategy.inline.algorithm-expression=health_record$->{record_id % 2}spring.shardingsphere.sharding.tables.health_record.table-strategy.inline.sharding-column=record_idspring.shardingsphere.sharding.tables.health_record.key-generator.column=record_idspring.shardingsphere.sharding.tables.health_record.key-generator.type=SNOWFLAKE# health_taskspring.shardingsphere.sharding.tables.health_task.actual-data-nodes=test$->{0..1}.health_task$->{0..1}spring.shardingsphere.sharding.tables.health_task.table-strategy.inline.algorithm-expression=health_task$->{record_id % 2}spring.shardingsphere.sharding.tables.health_task.table-strategy.inline.sharding-column=record_idspring.shardingsphere.sharding.tables.health_task.key-generator.column=task_idspring.shardingsphere.sharding.tables.health_task.key-generator.type=SNOWFLAKE

完整配置

server.port=8080#打印sqlspring.shardingsphere.props.sql.show=true#配置数据源spring.shardingsphere.datasource.names=test0,test1#test0spring.shardingsphere.datasource.test0.type=com.zaxxer.hikari.HikariDataSourcespring.shardingsphere.datasource.test0.driver-class-name=com.mysql.cj.jdbc.Driverspring.shardingsphere.datasource.test0.jdbcUrl=jdbc:mysql://127.0.0.1:3306/test0spring.shardingsphere.datasource.test0.username=devadminspring.shardingsphere.datasource.test0.password=#test1spring.shardingsphere.datasource.test1.type=com.zaxxer.hikari.HikariDataSourcespring.shardingsphere.datasource.test1.driver-class-name=com.mysql.cj.jdbc.Driverspring.shardingsphere.datasource.test1.jdbcUrl=jdbc:mysql://127.0.0.1:3306/test1spring.shardingsphere.datasource.test1.username=devadminspring.shardingsphere.datasource.test1.password=# 指定分片列名称的 shardingColumnspring.shardingsphere.sharding.default-database-strategy.inline.sharding-column=user_id# 指定分片算法行表达式的 algorithmExpressionspring.shardingsphere.sharding.default-database-strategy.inline.algorithm-expression=test$->{user_id % 2}# 设置绑定表spring.shardingsphere.sharding.binding-tables[0]=health_record,health_task# 设置广播表spring.shardingsphere.sharding.broadcast-tables[0]=health_level# user 如果不加这个，数据会随机插入数据库中spring.shardingsphere.sharding.tables.user.actual-data-nodes=test$->{[0,1]}.user#路由到 test0 否则会随意添加到两个数据库中spring.shardingsphere.sharding.tables.other_table.actual-data-nodes=test$->{0}.other_table# health_recordspring.shardingsphere.sharding.tables.health_record.actual-data-nodes=test$->{0..1}.health_record$->{0..1}spring.shardingsphere.sharding.tables.health_record.table-strategy.inline.algorithm-expression=health_record$->{record_id % 2}spring.shardingsphere.sharding.tables.health_record.table-strategy.inline.sharding-column=record_idspring.shardingsphere.sharding.tables.health_record.key-generator.column=record_idspring.shardingsphere.sharding.tables.health_record.key-generator.type=SNOWFLAKE# health_taskspring.shardingsphere.sharding.tables.health_task.actual-data-nodes=test$->{0..1}.health_task$->{0..1}spring.shardingsphere.sharding.tables.health_task.table-strategy.inline.algorithm-expression=health_task$->{record_id % 2}spring.shardingsphere.sharding.tables.health_task.table-strategy.inline.sharding-column=record_idspring.shardingsphere.sharding.tables.health_task.key-generator.column=task_idspring.shardingsphere.sharding.tables.health_task.key-generator.type=SNOWFLAKE

数据库

test0 test1 两个数据库的结构如下:

执行测试方法之后，数据库的数据如下：

health_level 是广播表，所以test0、test1中的数据是一样的

user 表中的数据分布。test0中user_id 都为偶数，test1中user_id都为奇数。

testx_health_record0 、testx_health_task0 中 record_id 都为偶数，testx_health_record1、testx_health_task11中record_ir都为奇数。（我们只截取healt_record表，health_task表的数据是一样的）

test0 中 health_record0 和 health_record1

test1 中 health_record0 和 health_record1

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