分表实践(sharding-jdbc&mybatis-plus)

分表

Sharding-JDBC

此处采用自定义分表策略，如分表策略较为简单（id/时间/hashMod），可直接在配置文件中用表达式完成分表，无需配置自定义规则。
配置方式见官方文档：
/document/legacy//document/cn/manual/sharding-jdbc/configuration/config-spring-boot/

1.引入依赖

        <dependency>
            <groupId>org.apache.shardingsphere</groupId>
            <artifactId>sharding-jdbc-spring-boot-starter</artifactId>
            <version>4.1.1</version>
        </dependency>

2.数据源及分表原则配置

#启动项目报bean冲突配置
spring.main.allow-bean-definition-overriding=true
#分片sql打印
spring.shardingsphere.props.sql.show=true
#数据源名
spring.shardingsphere.datasource.names=master
#连接池
spring.shardingsphere.datasource.master.type=com.alibaba.druid.pool.DruidDataSource
#数据库驱动及连接配置
spring.shardingsphere.datasource.master.driver-class-name=com.mysql.cj.jdbc.Driver
spring.shardingsphere.datasource.master.url=jdbc:mysql://xxx.xxx.xxx.xxx:3306/xxx?serverTimezone=UTC&allowMultiQueries=true&useSSL=false
spring.shardingsphere.datasource.master.username=root
spring.shardingsphere.datasource.master.password=123456
#分表集合 此处表示共60张表 后缀为0-60
spring.shardingsphere.sharding.tables.t_material_produce_report.actual-data-nodes=master.t_material_produce_report_$->{0..60}
#分表键 包含分表键的sql会走分表原则 否则走全表
spring.shardingsphere.sharding.tables.t_material_produce_report.table-strategy.standard.sharding-column=material_production_code
#分表策略 此处为自定义分表策略
spring.shardingsphere.sharding.tables.t_material_produce_report.table-strategy.standard.precise-algorithm-class-name=com.example.plus.config.MesShardingRule

3.分表策略配置

package com.example.plus.config;

import org.apache.shardingsphere.api.sharding.standard.PreciseShardingAlgorithm;
import org.apache.shardingsphere.api.sharding.standard.PreciseShardingValue;
import org.springframework.stereotype.Component;

import java.util.Collection;

/**
 * @Author:
 * @Description: mes分表规则
 * 表前缀 t_material_produce_report_
 * 表后缀 1-27 为 一个机种
 * 表后缀 28-60 为 一个机种
 * 表后缀 0 为 不符合上述规则的数据
 * 分表键 material_production_code
 * 分表策略 对分表键判断机种后hash取模
 * @Date: create in 2022/6/30 14:18
 */
@Component
public class MesShardingRule implements PreciseShardingAlgorithm<String> {

    private static final int SHARDING_NUM_ONE = 27; // 1907 & 1908 1-27
    private static final int SHARDING_NUM_TWO = 33; // 2576 & 2577 33-60
    private static final String PREFIX = "t_material_produce_report_"; // 前缀
    private static final String DIRTY_DATA_TABLE = "t_material_produce_report_0"; // 脏数据

    @Override
    public String doSharding(Collection<String> collection, PreciseShardingValue<String> preciseShardingValue) {
        String value = preciseShardingValue.getValue();
        return getTableName(value);
    }

    private String getTableName(String value){
        String tableName = PREFIX + "error";
        if(value.contains("MNZ2")||value.contains("ZNZ2")||value.contains("PYKZN")||value.contains("PYKMN")){
            // 1908
            tableName = PREFIX+(Math.abs(value.hashCode()) % SHARDING_NUM_ONE + 1);
        }else if(value.contains("MNZ1")||value.contains("ZNZ1")){
            // 1907
            tableName = PREFIX+(Math.abs(value.hashCode()) % SHARDING_NUM_ONE + 1);
        }else if(value.contains("H1YB")||value.contains("H1YL")||value.contains("H2YB")||value.contains("H2YL")){
            tableName = PREFIX+(Math.abs(value.hashCode()) % SHARDING_NUM_TWO + SHARDING_NUM_ONE + 1);
        }else{
            tableName = DIRTY_DATA_TABLE;
        }
        return tableName;
    }
}

继承PreciseShardingAlgorithm，并重写doSharding方法即可，doSharding返回值为指定表名，参数preciseShardingValue为分表键值，可依据preciseShardingValue值来实现分表逻辑，使sql操作落到指定表中，实现分表功能。
此处为hash取模分表。

4.分表原则

分表原则一般为自增主键/时间或关键字段hash取模。
自增键易于扩容，数据分布均匀，但热点数据容易落在单表上。
时间分表，同样易于扩容，存在热点数据访问问题，新数据访问频次高于旧数据，分表数据不一定均匀，由时间段内业务决定。
hash取模，用常用查询条件hashcode除分表数取模分表，数据分表均匀，但扩容麻烦，需要将旧数据重新取模分表，适用于确定需承载数据量时使用。

5.使用

项目整合了mybatis-plus，直接使用即可。

    /**
     * 分表键检索
     * @param code
     * @return
     */
    @RequestMapping("/getListByCode")
    @ResponseBody
    public List<MaterialProduceReport> getListByCode(String code){
        QueryWrapper<MaterialProduceReport> queryWrapper = new QueryWrapper<>();
        queryWrapper.eq("material_production_code",code);
        return materialProduceReportMapper.selectList(queryWrapper);
    }

查询条件中带有分表键，会依据设定的分表策略确定去哪张子表查询。
查询条件中不带分表键，会走全表查询。

6.注意事项

1.使用mybatis/mybatis-plus的分页插件查询mysql数据库时，当分表数过多且单表数据量过大时，会出现页码越往后查询速度越慢的情况，由于分页是基于limit实现，查询结果为全字段，分页sql为 ：

SELECT * XXX WHERE ... LIMIT 80000,20;

此时*中的字段含有非索引字段，导致查询效率极低。
代码中可进行改写

    @RequestMapping("/listByPaging")
    @ResponseBody
    public IPage<MaterialProduceReport> listByPaging(int current,int size){
        Page<MaterialProduceReport> page = new Page<>(current,size);
        QueryWrapper<MaterialProduceReport> queryWrapper = new QueryWrapper<>();
        queryWrapper.orderByAsc("id");
        IPage<MaterialProduceReport> iPage = materialProduceReportMapper.selectPage(page,queryWrapper);
        return iPage;
    }

改写为

    /**
     * 分页检索全部数据
     * @param current
     * @param size
     * @return
     */
    @RequestMapping("/listByPaging")
    @ResponseBody
    public IPage<MaterialProduceReport> listByPaging(int current,int size){
        Page<MaterialProduceReport> page = new Page<>(current,size);
        QueryWrapper<MaterialProduceReport> queryWrapper = new QueryWrapper<>();
        queryWrapper.orderByAsc("id");
        queryWrapper.select("id","material_production_code");
        IPage<MaterialProduceReport> iPage = materialProduceReportMapper.selectPage(page,queryWrapper);
        List<MaterialProduceReport> list = new ArrayList<>();
        for(MaterialProduceReport materialProduceReport : iPage.getRecords()){
            QueryWrapper<MaterialProduceReport> queryWrapperItem = new QueryWrapper<>();
            queryWrapperItem.eq("material_production_code",materialProduceReport.getMaterialProductionCode());
            queryWrapperItem.eq("id",materialProduceReport.getId());
            materialProduceReport = materialProduceReportMapper.selectOne(queryWrapperItem);
            list.add(materialProduceReport);
        }
        iPage.setRecords(list);
        return iPage;
    }

先分页查询出建立索引的主键字段及分表字段，再依据主键及分表字段查询所有字段，此时sql为

SELECT id,material_production_code XXX WHERE ... LIMIT 80000,20;

查询效率可以得到提升。

2.启动时报错，但不影响项目运行，消除报错。
仅在整合到现行系统中出现，可能是版本问题，未深究。
异常内容：

org.springframework.dao.InvalidDataAccessApiUsageException: ConnectionCallback; isValid; nested exception is java.sql.SQLFeatureNotSupportedException: isValid
	at org.springframework.jdbc.support.SQLExceptionSubclassTranslator.doTranslate(SQLExceptionSubclassTranslator.java:96)
	at org.springframework.jdbc.support.AbstractFallbackSQLExceptionTranslator.translate(AbstractFallbackSQLExceptionTranslator.java:70)
	at org.springframework.jdbc.support.AbstractFallbackSQLExceptionTranslator.translate(AbstractFallbackSQLExceptionTranslator.java:79)
	at org.springframework.jdbc.core.JdbcTemplate.translateException(JdbcTemplate.java:1541)
	at org.springframework.jdbc.core.JdbcTemplate.execute(JdbcTemplate.java:342)
	at org.springframework.boot.actuate.jdbc.DataSourceHealthIndicator.isConnectionValid(DataSourceHealthIndicator.java:130)
	at org.springframework.boot.actuate.jdbc.DataSourceHealthIndicator.doDataSourceHealthCheck(DataSourceHealthIndicator.java:116)
	at org.springframework.boot.actuate.jdbc.DataSourceHealthIndicator.doHealthCheck(DataSourceHealthIndicator.java:100)
	at org.springframework.boot.actuate.health.AbstractHealthIndicator.health(AbstractHealthIndicator.java:82)
	at org.springframework.boot.actuate.health.HealthIndicator.getHealth(HealthIndicator.java:37)
	at org.springframework.boot.actuate.health.HealthEndpoint.getHealth(HealthEndpoint.java:71)
	at org.springframework.boot.actuate.health.HealthEndpoint.getHealth(HealthEndpoint.java:39)
	at org.springframework.boot.actuate.health.HealthEndpointSupport.getContribution(HealthEndpointSupport.java:99)
	at org.springframework.boot.actuate.health.HealthEndpointSupport.getAggregateHealth(HealthEndpointSupport.java:110)
	at org.springframework.boot.actuate.health.HealthEndpointSupport.getContribution(HealthEndpointSupport.java:96)
	at org.springframework.boot.actuate.health.HealthEndpointSupport.getHealth(HealthEndpointSupport.java:74)
	at org.springframework.boot.actuate.health.HealthEndpointSupport.getHealth(HealthEndpointSupport.java:61)
	at org.springframework.boot.actuate.health.HealthEndpoint.health(HealthEndpoint.java:65)
	at org.springframework.boot.actuate.health.HealthEndpoint.health(HealthEndpoint.java:55)
	at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
	at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
	at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
	at java.lang.reflect.Method.invoke(Method.java:498)
	at org.springframework.util.ReflectionUtils.invokeMethod(ReflectionUtils.java:282)
	at org.springframework.boot.actuate.endpoint.invoke.reflect.ReflectiveOperationInvoker.invoke(ReflectiveOperationInvoker.java:77)
	at org.springframework.boot.actuate.endpoint.annotation.AbstractDiscoveredOperation.invoke(AbstractDiscoveredOperation.java:60)
	at org.springframework.boot.actuate.endpoint.jmx.EndpointMBean.invoke(EndpointMBean.java:121)
	at org.springframework.boot.actuate.endpoint.jmx.EndpointMBean.invoke(EndpointMBean.java:96)
	at com.sun.jmx.interceptor.DefaultMBeanServerInterceptor.invoke(DefaultMBeanServerInterceptor.java:819)
	at com.sun.jmx.mbeanserver.JmxMBeanServer.invoke(JmxMBeanServer.java:801)
	at javax.management.remote.rmi.RMIConnectionImpl.doOperation(RMIConnectionImpl.java:1468)
	at javax.management.remote.rmi.RMIConnectionImpl.access$300(RMIConnectionImpl.java:76)
	at javax.management.remote.rmi.RMIConnectionImpl$PrivilegedOperation.run(RMIConnectionImpl.java:1309)
	at javax.management.remote.rmi.RMIConnectionImpl.doPrivilegedOperation(RMIConnectionImpl.java:1401)
	at javax.management.remote.rmi.RMIConnectionImpl.invoke(RMIConnectionImpl.java:829)
	at sun.reflect.GeneratedMethodAccessor136.invoke(Unknown Source)
	at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
	at java.lang.reflect.Method.invoke(Method.java:498)
	at sun.rmi.server.UnicastServerRef.dispatch(UnicastServerRef.java:346)
	at sun.rmi.transport.Transport$1.run(Transport.java:200)
	at sun.rmi.transport.Transport$1.run(Transport.java:197)
	at java.security.AccessController.doPrivileged(Native Method)
	at sun.rmi.transport.Transport.serviceCall(Transport.java:196)
	at sun.rmi.transport.tcp.TCPTransport.handleMessages(TCPTransport.java:568)
	at sun.rmi.transport.tcp.TCPTransport$ConnectionHandler.run0(TCPTransport.java:826)
	at sun.rmi.transport.tcp.TCPTransport$ConnectionHandler.lambda$run$0(TCPTransport.java:683)
	at java.security.AccessController.doPrivileged(Native Method)
	at sun.rmi.transport.tcp.TCPTransport$ConnectionHandler.run(TCPTransport.java:682)
	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
	at java.lang.Thread.run(Thread.java:748)
Caused by: java.sql.SQLFeatureNotSupportedException: isValid
	at org.apache.shardingsphere.shardingjdbc.jdbc.unsupported.AbstractUnsupportedOperationConnection.isValid(AbstractUnsupportedOperationConnection.java:157)
	at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
	at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
	at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
	at java.lang.reflect.Method.invoke(Method.java:498)
	at org.springframework.jdbc.core.JdbcTemplate$CloseSuppressingInvocationHandler.invoke(JdbcTemplate.java:1614)
	at com.sun.proxy.$Proxy313.isValid(Unknown Source)
	at org.springframework.boot.actuate.jdbc.DataSourceHealthIndicator.isConnectionValid(DataSourceHealthIndicator.java:134)
	at org.springframework.jdbc.core.JdbcTemplate.execute(JdbcTemplate.java:334)
	... 46 common frames omitted

解决方法，创建配置类：

import com.taobao.arthas.core.util.StringUtils;
import org.springframework.beans.factory.ObjectProvider;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.boot.actuate.autoconfigure.jdbc.DataSourceHealthContributorAutoConfiguration;
import org.springframework.boot.actuate.health.AbstractHealthIndicator;
import org.springframework.boot.actuate.jdbc.DataSourceHealthIndicator;
import org.springframework.boot.jdbc.metadata.DataSourcePoolMetadataProvider;
import org.springframework.context.annotation.Configuration;

import javax.sql.DataSource;
import java.util.Map;

/**
 * @Author:
 * @Description: 整合sharding-jdbc启动异常
 * @Date: create in 2022/7/8 8:54
 */
@Configuration
public class DataSourceHealthConfig extends DataSourceHealthContributorAutoConfiguration {
//    @Value("${:select 1}")
    @Value("${.-query:select 1}")
    private String defaultQuery;


    public DataSourceHealthConfig(Map<String, DataSource> dataSources, ObjectProvider<DataSourcePoolMetadataProvider> metadataProviders) {
        super(dataSources, metadataProviders);
    }

    @Override
    protected AbstractHealthIndicator createIndicator(DataSource source) {
        DataSourceHealthIndicator indicator = (DataSourceHealthIndicator) super.createIndicator(source);
        if (!StringUtils.hasText(indicator.getQuery())) {
            indicator.setQuery(defaultQuery);
        }
        return indicator;
    }
}

7.现行系统分表改造

现有系统为单表设计，考虑到数据量增加过多，需要进行分表改造。
方案如下
1.导出现有数据(500w左右) 30 m
2.导入到备用表 60 m
3.分备用表数据 10 h
4.正式环境建立分表 导入备份分表数据
5.正式环境建立临时表
需停机 6.停机 部署新代码(所有操作走分表)
需停机 7.导出步骤1之后新增的数据至临时表(5w左右) 5 m
需停机 8.分临时表数据至分表 10 m
9.启动项目

mybatis-plus

mybatis-plus动态表名也能实现分表功能，且较为简单。但是好像不能走全表查询（？），局限性较高，未采用。

1.设置分表原则

package com.example.plus.config;

import com.baomidou.mybatisplus.extension.plugins.handler.TableNameHandler;

/**
 * @Author:
 * @Description:
 * @Date: create in 2022/6/27 9:06
 */
public class IdModTableNameParser implements TableNameHandler {
    private Integer mod;

    private static ThreadLocal<Integer> id = new ThreadLocal<Integer>();

    public static void setId(Integer idValue) {
        id.set(idValue);
    }

    IdModTableNameParser(Integer modValue) {
        this.mod = modValue;
    }

    @Override
    public String dynamicTableName(String sql, String tableName) {
        Integer idValue = id.get();
        if (idValue == null) {
            throw new RuntimeException("请设置id值");
        } else {
            String suffix = String.valueOf(idValue % mod);
            //这里清除ThreadLocal的值，防止线程复用出现问题
            id.set(null);
            return tableName + "_" + suffix;
        }
    }
}

继承TableNameHandler ，重写dynamicTableName方法，返回值为分表名。

2.配置分表原则生效

package com.example.plus.config;

import com.baomidou.mybatisplus.annotation.DbType;
import com.baomidou.mybatisplus.extension.plugins.MybatisPlusInterceptor;
import com.baomidou.mybatisplus.extension.plugins.handler.TableNameHandler;
import com.baomidou.mybatisplus.extension.plugins.inner.BlockAttackInnerInterceptor;
import com.baomidou.mybatisplus.extension.plugins.inner.DynamicTableNameInnerInterceptor;
import com.baomidou.mybatisplus.extension.plugins.inner.PaginationInnerInterceptor;
import org.mybatis.spring.annotation.MapperScan;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;

import java.util.HashMap;

/**
 * @Author:
 * @Description:
 * @Date: create in 2022/6/27 9:15
 */
@Configuration
@MapperScan(basePackages = "")
public class MybatisConfig {
    @Bean
    public MybatisPlusInterceptor mybatisPlusInterceptor() {
        MybatisPlusInterceptor interceptor = new MybatisPlusInterceptor();
        // 分页插件
        PaginationInnerInterceptor paginationInnerInterceptor = new PaginationInnerInterceptor(DbType.MYSQL);
        paginationInnerInterceptor.setMaxLimit(500L);
        paginationInnerInterceptor.setOverflow(true);
        interceptor.addInnerInterceptor(paginationInnerInterceptor);
        // 防止全局更新删除
        interceptor.addInnerInterceptor(new BlockAttackInnerInterceptor());


        DynamicTableNameInnerInterceptor dynamicTableNameInnerInterceptor = new DynamicTableNameInnerInterceptor();
        HashMap<String, TableNameHandler> map = new HashMap<String, TableNameHandler>();
        //这里为不同的表设置对应表名处理器
//        ("user_daily_record", new DaysTableNameParser());
        map.put("t_log", new IdModTableNameParser(3));
        dynamicTableNameInnerInterceptor.setTableNameHandlerMap(map);
        interceptor.addInnerInterceptor(dynamicTableNameInnerInterceptor);


        return interceptor;
    }
}

map的key为逻辑表名，value为分表原则。

3.使用

    @RequestMapping("/insert")
    @ResponseBody
    public void insert(String id){
        IdModTableNameParser.setId(Integer.valueOf(id));
        LogEntity logEntity = new LogEntity();
        logEntity.setOid(id).setDuration("1").setEndTime("2022-06-24 16:50:30").setStartTime("2022-06-24 16:50:30").setErrorMessage("1").setEventName("1");
        testMapper.insert(logEntity);
    }