目录
- 1.Maven 依赖
 - 2.创建表结构
 - 3.yml 配置
 - 4.TimeShardingAlgorithm.java 分片算法类
 - 5.ShardingAlgorithmTool.java 分片工具类
 - 6.ShardingTablesLoadRunner.java 初始化缓存类
 - 7.SpringUtil.java Spring工具类
 - 8.代码测试
 - 9.测试结果
 
背景: 项目用户数据库表量太大,对数据按月分表,需要满足如下需求:
- 将数据库按月分表;
 - 自动建表;
 - 数据自动跨表查询。
 
1.Maven 依赖
<!-- ShardingJDBC -->
<dependency>
    <groupId>org.apache.shardingsphere</groupId>
    <artifactId>shardingsphere-jdbc-core</artifactId>
    <version>4.0.1</version>
</dependency>
 
2.创建表结构
-- ------------------------------
-- 用户表
-- ------------------------------
CREATE TABLE `t_user` (
  `id` bigint(16) NOT NULL COMMENT '主键',
  `username` varchar(64) NOT NULL COMMENT '用户名',
  `password` varchar(64) NOT NULL COMMENT '密码',
  `age` int(8) NOT NULL COMMENT '年龄',
  `create_time` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP COMMENT '创建时间',
  `update_time` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP COMMENT '更新时间',
  PRIMARY KEY (`id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8 COMMENT='用户表';
-- ------------------------------
-- 用户表202201
-- ------------------------------
CREATE TABLE `t_user_202201` (
  `id` bigint(16) NOT NULL COMMENT '主键',
  `username` varchar(64) NOT NULL COMMENT '用户名',
  `password` varchar(64) NOT NULL COMMENT '密码',
  `age` int(8) NOT NULL COMMENT '年龄',
  `create_time` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP COMMENT '创建时间',
  `update_time` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP COMMENT '更新时间',
  PRIMARY KEY (`id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8 COMMENT='用户表202201';
 
3.yml 配置
server:
  port: 8081
spring:
  shardingsphere:
    # 打印sql
#    props:
#      sql:
#        show: true
    datasource:
      names: mydb
      mydb:
        type: com.alibaba.druid.pool.DruidDataSource
        url: jdbc:mysql://localhost:3306/mydb?useUnicode=true&characterEncoding=UTF-8&serverTimezone=Asia/Shanghai
        driver-class-name: com.mysql.cj.jdbc.Driver
        username: root
        password: root
        # 数据源其他配置
        initialSize: 5
        minIdle: 5
        maxActive: 20
        maxWait: 60000
        timeBetweenEvictionRunsMillis: 60000
        minEvictableIdleTimeMillis: 300000
        validationQuery: SELECT 1 FROM DUAL
        testWhileIdle: true
        testOnBorrow: false
        testOnReturn: false
        poolPreparedStatements: true
        # 配置监控统计拦截的filters,去掉后监控界面sql无法统计,'wall'用于防火墙
        #filters: stat,wall,log4j
        maxPoolPreparedStatementPerConnectionSize: 20
        useGlobalDataSourceStat: true
        connectionProperties: druid.stat.mergeSql=true;druid.stat.slowSqlMillis=500
    sharding:
      # 表策略配置
      tables:
        # t_user 是逻辑表
        t_user:
          # 配置数据节点,这里是按月分表
          # 示例1:时间范围设置在202201 ~ 210012
          # actualDataNodes: mydb.t_user_$->{2022..2100}0$->{1..9},mydb.t_user_$->{2022..2100}1$->{0..2}
          # 示例2:时间范围设置在202201 ~ 202203
          actualDataNodes: mydb.t_user_20220$->{1..3}
          tableStrategy:
            # 使用标准分片策略
            standard:
              # 配置分片字段
              shardingColumn: create_time
              # 配置精准分片算法
              preciseAlgorithmClassName: com.demo.module.config.sharding.TimeShardingAlgorithm
              # 配置范围分片算法
              rangeAlgorithmClassName: com.demo.module.config.sharding.TimeShardingAlgorithm
          # 配置主键及生成算法
          keyGenerator:
            column: id
            type: SNOWFLAKE
# mybatis-plus
mybatis-plus:
  mapper-locations: classpath*:/mapper/*Mapper.xml
  # 实体扫描,多个package用逗号或者分号分隔
  typeAliasesPackage: cn.agile.stats.*.entity
  # 测试环境打印sql
  configuration:
    log-impl: org.apache.ibatis.logging.stdout.StdOutImpl
 
4.TimeShardingAlgorithm.java 分片算法类
import com.google.common.collect.Range;
import lombok.extern.slf4j.Slf4j;
import org.apache.shardingsphere.api.sharding.standard.PreciseShardingAlgorithm;
import org.apache.shardingsphere.api.sharding.standard.PreciseShardingValue;
import org.apache.shardingsphere.api.sharding.standard.RangeShardingAlgorithm;
import org.apache.shardingsphere.api.sharding.standard.RangeShardingValue;
import java.sql.Timestamp;
import java.time.LocalDateTime;
import java.time.format.DateTimeFormatter;
import java.util.*;
import java.util.function.Function;
/**
 * <p> @Title TimeShardingAlgorithm
 * <p> @Description 分片算法,按月分片
 *
 * @author zhj
 * @date 2022/12/20 11:33
 */
@Slf4j
public class TimeShardingAlgorithm implements PreciseShardingAlgorithm<Timestamp>, RangeShardingAlgorithm<Timestamp> {
    /**
     * 分片时间格式
     */
    private static final DateTimeFormatter TABLE_SHARD_TIME_FORMATTER = DateTimeFormatter.ofPattern("yyyyMM");
    /**
     * 完整时间格式
     */
    private static final DateTimeFormatter DATE_TIME_FORMATTER = DateTimeFormatter.ofPattern("yyyyMMdd HH:mm:ss");
    /**
     * 表分片符号,例:t_user_202201 中,分片符号为 "_"
     */
    private final String TABLE_SPLIT_SYMBOL = "_";
    /**
     * 精准分片
     * @param tableNames 对应分片库中所有分片表的集合
     * @param preciseShardingValue 分片键值,其中 logicTableName 为逻辑表,columnName 分片键,value 为从 SQL 中解析出来的分片键的值
     * @return 表名
     */
    @Override
    public String doSharding(Collection<String> tableNames, PreciseShardingValue<Timestamp> preciseShardingValue) {
        log.info(">>>>>>>>>> 【INFO】精准分片,节点配置表名:{},数据库实时表名:{},数据库缓存表名:{}", tableNames,
                ShardingAlgorithmTool.getAllTableNameBySchema(), ShardingAlgorithmTool.getTableNameCache());
        LocalDateTime dateTime = preciseShardingValue.getValue().toLocalDateTime();
        String logicTableName = preciseShardingValue.getLogicTableName();
        String resultTableName = logicTableName + "_" + dateTime.format(TABLE_SHARD_TIME_FORMATTER);
        // 检查分表获取的表名是否存在,不存在则自动建表
        return ShardingAlgorithmTool.getShardingTableAndCreate(logicTableName, resultTableName);
    }
    /**
     * 范围分片
     * @param tableNames 对应分片库中所有分片表的集合
     * @param rangeShardingValue 分片范围
     * @return 表名集合
     */
    @Override
    public Collection<String> doSharding(Collection<String> tableNames, RangeShardingValue<Timestamp> rangeShardingValue) {
        log.info(">>>>>>>>>> 【INFO】范围分片,节点配置表名:{},数据库实时表名:{},数据库缓存表名:{}", tableNames,
                ShardingAlgorithmTool.getAllTableNameBySchema(), ShardingAlgorithmTool.getTableNameCache());
        // between and 的起始值
        Range<Timestamp> valueRange = rangeShardingValue.getValueRange();
        boolean hasLowerBound = valueRange.hasLowerBound();
        boolean hasUpperBound = valueRange.hasUpperBound();
        // 获取最大值和最小值
        Set<String> tableNameCache = ShardingAlgorithmTool.getTableNameCache();
        LocalDateTime min = hasLowerBound ? valueRange.lowerEndpoint().toLocalDateTime() :getLowerEndpoint(tableNameCache);
        LocalDateTime max = hasUpperBound ? valueRange.upperEndpoint().toLocalDateTime() :getUpperEndpoint(tableNameCache);
        // 循环计算分表范围
        Set<String> resultTableNames = new LinkedHashSet<>();
        String logicTableName = rangeShardingValue.getLogicTableName();
        while (min.isBefore(max) || min.equals(max)) {
            String tableName = logicTableName + TABLE_SPLIT_SYMBOL + min.format(TABLE_SHARD_TIME_FORMATTER);
            resultTableNames.add(tableName);
            min = min.plusMinutes(1);
        }
        return ShardingAlgorithmTool.getShardingTablesAndCreate(logicTableName, resultTableNames);
    }
    // --------------------------------------------------------------------------------------------------------------
    // 私有方法
    // --------------------------------------------------------------------------------------------------------------
    /**
     * 获取 最小分片值
     * @param tableNames 表名集合
     * @return 最小分片值
     */
    private LocalDateTime getLowerEndpoint(Collection<String> tableNames) {
        Optional<LocalDateTime> optional = tableNames.stream()
                .map(o -> LocalDateTime.parse(o.replace(TABLE_SPLIT_SYMBOL, "") + "01 00:00:00", DATE_TIME_FORMATTER))
                .min(Comparator.comparing(Function.identity()));
        if (optional.isPresent()) {
            return optional.get();
        } else {
            log.error(">>>>>>>>>> 【ERROR】获取数据最小分表失败,请稍后重试,tableName:{}", tableNames);
            throw new IllegalArgumentException("获取数据最小分表失败,请稍后重试");
        }
    }
    /**
     * 获取 最大分片值
     * @param tableNames 表名集合
     * @return 最大分片值
     */
    private LocalDateTime getUpperEndpoint(Collection<String> tableNames) {
        Optional<LocalDateTime> optional = tableNames.stream()
                .map(o -> LocalDateTime.parse(o.replace(TABLE_SPLIT_SYMBOL, "") + "01 00:00:00", DATE_TIME_FORMATTER))
                .max(Comparator.comparing(Function.identity()));
        if (optional.isPresent()) {
            return optional.get();
        } else {
            log.error(">>>>>>>>>> 【ERROR】获取数据最大分表失败,请稍后重试,tableName:{}", tableNames);
            throw new IllegalArgumentException("获取数据最大分表失败,请稍后重试");
        }
    }
}
 
5.ShardingAlgorithmTool.java 分片工具类
import com.alibaba.druid.util.StringUtils;
import com.demo.module.utils.SpringUtil;
import lombok.extern.slf4j.Slf4j;
import org.springframework.core.env.Environment;
import java.sql.*;
import java.time.YearMonth;
import java.time.format.DateTimeFormatter;
import java.util.*;
import java.util.stream.Collectors;
/**
 * <p> @Title ShardingAlgorithmTool
 * <p> @Description 按月分片算法工具
 *
 * @author zhj
 * @date 2022/12/20 14:03
 */
@Slf4j
public class ShardingAlgorithmTool {
    /** 已存在表名集合缓存 */
    private static final Set<String> tableNameCache = new HashSet<>();
    /** 用户表名 */
    private static final String userTableName = "t_user";
    /** 表分片符号,例:t_user_202201 中,分片符号为 "_" */
    private static final String tableSplitSymbol = "_";
    /** 数据库配置 */
    private static final Environment env = SpringUtil.getApplicationContext().getEnvironment();
    private static final String url = env.getProperty("spring.shardingsphere.datasource.mydb.url");
    private static final String username = env.getProperty("spring.shardingsphere.datasource.mydb.username");
    private static final String password = env.getProperty("spring.shardingsphere.datasource.mydb.password");
    /**
     * 检查分表获取的表名是否存在,不存在则自动建表
     * @param logicTableName 逻辑表名,例:t_user
     * @param resultTableNames 真实表名,例:t_user_202201
     * @return 存在于数据库中的真实表名集合
     */
    public static Set<String> getShardingTablesAndCreate(String logicTableName, Collection<String> resultTableNames) {
        return resultTableNames.stream().map(o -> getShardingTableAndCreate(logicTableName, o)).collect(Collectors.toSet());
    }
    /**
     * 检查分表获取的表名是否存在,不存在则自动建表
     * @param logicTableName 逻辑表名,例:t_user
     * @param resultTableName 真实表名,例:t_user_202201
     * @return 确认存在于数据库中的真实表名
     */
    public static String getShardingTableAndCreate(String logicTableName, String resultTableName) {
        // 缓存中有此表则返回,没有则判断创建
        if (tableNameCache.contains(resultTableName)) {
            return resultTableName;
        } else {
            // 未创建的表返回逻辑空表
            boolean isSuccess = createShardingTable(logicTableName, resultTableName);
            return isSuccess ? resultTableName : logicTableName;
        }
    }
    /**
     * 缓存重载
     */
    public static void tableNameCacheReload() {
        // 读取数据库中|所有表名
        List<String> tableNameList = getAllTableNameBySchema();
        // 删除旧的缓存(如果存在)
        tableNameCache.clear();
        // 写入新的缓存
        ShardingAlgorithmTool.tableNameCache.addAll(tableNameList);
    }
    /**
     * 获取所有表名
     * @return 表名集合
     */
    public static List<String> getAllTableNameBySchema() {
        List<String> tableNames = new ArrayList<>();
        if (StringUtils.isEmpty(url) || StringUtils.isEmpty(username) || StringUtils.isEmpty(password)) {
            log.error(">>>>>>>>>> 【ERROR】数据库连接配置有误,请稍后重试,url:{}, username:{}, password:{}", url, username, password);
            throw new IllegalArgumentException("数据库连接配置有误,请稍后重试");
        }
        try (Connection conn = DriverManager.getConnection(url, username, password);
             Statement st = conn.createStatement()) {
            try (ResultSet rs = st.executeQuery("show TABLES like 't_user_%'")) {
                while (rs.next()) {
                    tableNames.add(rs.getString(1));
                }
            }
        } catch (SQLException e) {
            log.error(">>>>>>>>>> 【ERROR】数据库连接失败,请稍后重试,原因:{}", e.getMessage(), e);
            throw new IllegalArgumentException("数据库连接失败,请稍后重试");
        }
        return tableNames;
    }
    /**
     * 获取表名缓存
     * @return 表名缓存
     */
    public static Set<String> getTableNameCache() {
        return tableNameCache;
    }
    // --------------------------------------------------------------------------------------------------------------
    // 私有方法
    // --------------------------------------------------------------------------------------------------------------
    /**
     * 创建分表
     * @param logicTableName 逻辑表名,例:t_user
     * @param resultTableName 真实表名,例:t_user_202201
     * @return 创建结果(true创建成功,false未创建)
     */
    private static boolean createShardingTable(String logicTableName, String resultTableName) {
        // 根据日期判断,当前月份之后月份分表不提前创建
        String month = resultTableName.replace(logicTableName + tableSplitSymbol,"");
        YearMonth shardingMonth = YearMonth.parse(month, DateTimeFormatter.ofPattern("yyyyMM"));
        if (shardingMonth.isAfter(YearMonth.now())) {
            return false;
        }
        synchronized (logicTableName.intern()) {
            // 缓存中有此表 返回
            if (tableNameCache.contains(resultTableName)) {
                return false;
            }
            // 缓存中无此表,则建表并添加缓存
            List<String> sqlList = getCreateTableSql(logicTableName);
            for (int i = 0; i < sqlList.size(); i++) {
                sqlList.set(i, sqlList.get(i).replace("CREATE TABLE", "CREATE TABLE IF NOT EXISTS").replace(logicTableName, resultTableName));
            }
            executeSql(sqlList);
            tableNameCache.add(resultTableName);
        }
        return true;
    }
    /**
     * 执行SQL
     * @param sqlList SQL集合
     */
    private static void executeSql(List<String> sqlList) {
        if (StringUtils.isEmpty(url) || StringUtils.isEmpty(username) || StringUtils.isEmpty(password)) {
            log.error(">>>>>>>>>> 【ERROR】数据库连接配置有误,请稍后重试,url:{}, username:{}, password:{}", url, username, password);
            throw new IllegalArgumentException("数据库连接配置有误,请稍后重试");
        }
        try (Connection conn = DriverManager.getConnection(url, username, password)) {
            try (Statement st = conn.createStatement()) {
                conn.setAutoCommit(false);
                for (String sql : sqlList) {
                    st.execute(sql);
                }
            } catch (Exception e) {
                conn.rollback();
                log.error(">>>>>>>>>> 【ERROR】数据表创建执行失败,请稍后重试,原因:{}", e.getMessage(), e);
                throw new IllegalArgumentException("数据表创建执行失败,请稍后重试");
            }
        } catch (SQLException e) {
            log.error(">>>>>>>>>> 【ERROR】数据库连接失败,请稍后重试,原因:{}", e.getMessage(), e);
            throw new IllegalArgumentException("数据库连接失败,请稍后重试");
        }
    }
    /**
     * 获取建表语句
     * @param tableName 表名,例:t_user
     * @return 建表语句集合
     */
    private static List<String> getCreateTableSql(String tableName) {
        List<String> sqlList = new ArrayList<>();
        if (tableName.equals(userTableName)) {
            // 表结构
            sqlList.add("CREATE TABLE `t_user` (\n" +
                    "  `id` bigint(16) NOT NULL COMMENT '主键',\n" +
                    "  `username` varchar(64) NOT NULL COMMENT '用户名',\n" +
                    "  `password` varchar(64) NOT NULL COMMENT '密码',\n" +
                    "  `age` int(8) NOT NULL COMMENT '年龄',\n" +
                    "  `create_time` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP COMMENT '创建时间',\n" +
                    "  `update_time` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP COMMENT '更新时间',\n" +
                    "  PRIMARY KEY (`id`)\n" +
                    ") ENGINE=InnoDB DEFAULT CHARSET=utf8 COMMENT='用户表202203';");
            // 表索引
            sqlList.add("ALTER TABLE `t_user` ADD INDEX IDX_USERNAME ( `username` ) USING BTREE");
        }
        return sqlList;
    }
}
 
6.ShardingTablesLoadRunner.java 初始化缓存类
import org.springframework.boot.CommandLineRunner;
import org.springframework.core.annotation.Order;
import org.springframework.stereotype.Component;
/**
 * <p> @Title ShardingTablesLoadRunner
 * <p> @Description 项目启动后,读取已有分表,进行缓存
 *
 * @author zhj
 * @date 2022/12/20 15:41
 */
@Order(value = 1) // 数字越小,越先执行
@Component
public class ShardingTablesLoadRunner implements CommandLineRunner {
    @Override
    public void run(String... args) {
        // 读取已有分表,进行缓存
        ShardingAlgorithmTool.tableNameCacheReload();
    }
}
 
7.SpringUtil.java Spring工具类
import org.springframework.beans.BeansException;
import org.springframework.context.ApplicationContext;
import org.springframework.context.ApplicationContextAware;
import org.springframework.core.env.Environment;
import org.springframework.stereotype.Component;
/**
 * <p> @Title SpringUtil
 * <p> @Description Spring工具类
 *
 * @author zhj
 * @date 2022/12/20 14:39
 */
@Component
public class SpringUtil implements ApplicationContextAware {
    private static ApplicationContext applicationContext = null;
    @Override
    public void setApplicationContext(ApplicationContext applicationContext) throws BeansException {
        SpringUtil.applicationContext = applicationContext;
    }
    public static ApplicationContext getApplicationContext() {
        return SpringUtil.applicationContext;
    }
    public static <T> T getBean(Class<T> cla) {
        return applicationContext.getBean(cla);
    }
    public static <T> T getBean(String name, Class<T> cal) {
        return applicationContext.getBean(name, cal);
    }
    public static String getProperty(String key) {
        return applicationContext.getBean(Environment.class).getProperty(key);
    }
}
 
8.代码测试
import com.baomidou.mybatisplus.core.conditions.query.QueryWrapper;
import com.demo.module.entity.TUser;
import com.demo.module.service.TUserService;
import org.junit.jupiter.api.Test;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.boot.test.context.SpringBootTest;
import java.time.LocalDateTime;
import java.time.format.DateTimeFormatter;
import java.util.ArrayList;
import java.util.List;
@SpringBootTest
class SpringbootDemoApplicationTests {
    private final DateTimeFormatter DATE_TIME_FORMATTER = DateTimeFormatter.ofPattern("yyyy-MM-dd HH:mm:ss");
    @Autowired
    private TUserService userService;
    @Test
    void saveTest() {
        List<TUser> users = new ArrayList<>(3);
        LocalDateTime time1 = LocalDateTime.parse("2022-01-01 00:00:00", DATE_TIME_FORMATTER);
        LocalDateTime time2 = LocalDateTime.parse("2022-02-01 00:00:00", DATE_TIME_FORMATTER);
        LocalDateTime time3 = LocalDateTime.parse("2022-03-01 00:00:00", DATE_TIME_FORMATTER);
        users.add(new TUser("ACGkaka_1", "123456", 10, time1, time1));
//        users.add(new TUser("ACGkaka_2", "123456", 11, time2, time2));
//        users.add(new TUser("ACGkaka_3", "123456", 12, time3, time3));
        userService.saveBatch(users);
    }
    @Test
    void listTest() {
        LocalDateTime timeStart1 = LocalDateTime.parse("2022-01-01 00:00:00", DATE_TIME_FORMATTER);
        LocalDateTime timeEnd1 = LocalDateTime.parse("2022-01-31 23:59:59", DATE_TIME_FORMATTER);
        List<TUser> users = userService.list(new QueryWrapper<TUser>().between("create_time", timeStart1, timeEnd1));
        System.out.println(">>>>>>>>>> 【Result】<<<<<<<<<< ");
        users.forEach(System.out::println);
    }
}
 
9.测试结果

参考地址:
1.sharding-jdbc 实现按月分表,https://blog.csdn.net/u013515384/article/details/125237140
2.SharDingJDBC-5.1.0按月水平分表+读写分离,自动创表、自动刷新节点表,https://blog.csdn.net/m0_54850467/article/details/125242908


















