ShardingSphere5.0自定义分表策略

最新推荐文章于 2025-07-01 18:03:55 发布

thebigsilly

最新推荐文章于 2025-07-01 18:03:55 发布

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分类专栏：分库分表文章标签： java 前端服务器

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文章介绍了如何使用SPI机制来注入自定义的分片算法`UserIdSharding`，该算法实现了`StandardShardingAlgorithm`接口，根据用户ID进行数据分片。配置中包含了数据库连接信息、读写分离规则以及分片策略的详细设定，如`sharding-count`。代码示例展示了分片算法的实现，包括精确分片和范围分片的方法。

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需要根据SPI来注入

META-INF/services/org.apache.shardingsphere.sharding.spi.ShardingAlgorithm

内容：com.example.user.sharding.UserIdSharding

Java代码

@Data
public class UserIdSharding implements StandardShardingAlgorithm<String> {
    private static final String SHARDING_COUNT_KEY = "sharding-count";

    /**
     * 对应props配置
     */
    private Properties props = new Properties();

    private int shardingCount;

    /**
     * 初始化调用
     */
    @Override
    public void init() {
        shardingCount = getShardingCount();
    }

    private int getShardingCount() {
        Preconditions.checkArgument(props.containsKey(SHARDING_COUNT_KEY), "Sharding count cannot be null.");
        return Integer.parseInt(props.get(SHARDING_COUNT_KEY).toString());
    }
    /**
     * Standard Sharding
     * @param availableTargetNames real table
     * @param preciseShardingValue Single Sharding key
     * @return
     */
    @Override
    public String doSharding(Collection<String> availableTargetNames, PreciseShardingValue<String> preciseShardingValue) {
        long l = Long.parseLong(preciseShardingValue.getValue()) % shardingCount;
        for (String availableTargetName : availableTargetNames) {
            if (availableTargetName.endsWith(String.valueOf(l))) {
                return availableTargetName;
            }
        }

        return null;
    }

    /**
     * Complex Sharding
     * @param availableTargetNames real table
     * @param rangeShardingValue Multiple Sharding Key
     * @return
     */
    @Override
    public Collection<String> doSharding(Collection<String> availableTargetNames, RangeShardingValue<String> rangeShardingValue) {
        return null;
    }

    /**
     * SPI根据配置Type获取
     * @return
     */
    @Override
    public String getType() {
        return "USER_ID";
    }

配置

spring:
  config:
    activate:
      on-profile: prod
  shardingsphere:
    datasource:
      names: master,slave
      master:
        type: com.alibaba.druid.pool.DruidDataSource
        driver-class-name: com.mysql.cj.jdbc.Driver
        url: jdbc:mysql://asus:3306/auth_db?characterEncoding=UTF-8&serverTimezone=Asia/Shanghai&autoReconnect=true&failOverReadOnly=false&zeroDateTimeBehavior=convertToNull&useSSL=false
        username: auth_user
        password: zxc521cxzPass!
      slave:
        type: com.alibaba.druid.pool.DruidDataSource  # 数据库配置，配置属性名 不同连接池，连接名不一样。根据数据库连接池DataSource来配置
        driver-class-name: com.mysql.cj.jdbc.Driver
        url: jdbc:mysql://dell:3306/auth_db?characterEncoding=UTF-8&serverTimezone=Asia/Shanghai&autoReconnect=true&failOverReadOnly=false&zeroDateTimeBehavior=convertToNull&useSSL=false
        username: auth_user
        password: zxc521cxzPass!
    props:
      sql-show: true
    rules:
      readwrite-splitting:
        load-balancers:
          roundRobin:
            type: ROUND_ROBIN #从库路由算法，ROUND_ROBIN：轮询，RANDOM：随机
        data-sources:
          read-write_0:
            #自动发现数据源名称（配置动态读写分离规则显示）,库中不配置则读写分离不生效，不配置则为静态分离，可以动态扩容。
            #只支持MySQL的自动发现，可以拓展成根据配置进行动态扩容?
            #auto_aware_data_source_name
            load-balancer-name: roundRobin #轮询算法
            read-data-source-names: slave #读库
            write-data-source-name: master #写库
      sharding:
        tables:
          users:
            table-strategy:
              standard:
                sharding-algorithm-name: table-inline
                sharding-column: user_id
            actual-data-nodes: read-write_0.users_$->{0..1}  #read-write_0 为读写分离的逻辑表明
        sharding-algorithms:
          table-inline:
            type: USER_ID
            props:
              sharding-count: 2