Sharding-JDBC（六）5.1.0版本，实现按月分表、自动建表、自动刷新节点

2024-02-29 12:50:10 分类：后端 热度：48 评论： 0

Sharding-JDBC（六）5.1.0版本，实现按月分表、自动建表、自动刷新节点

  • 官网地址： https://shardingsphere.apache.org/
  • GitHub： https://github.***/apache/shardingsphere
  • 官方示例：https://github.***/apache/shardingsphere/tree/master/examples
  • 中文社区： https://***munity.sphere-ex.***/
  • 5.1.0 官方文档： https://shardingsphere.apache.org/document/5.1.0/***/overview/

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：

  1. 将数据库按月分表；
  2. 自动建表；
  3. 数据自动跨表查询。

ShardingJDBC 4 升到 5 过后还是解决了许多问题，4版本的分页、跨库和子查询问题都解决来了，性能也提高了。

1.Maven 依赖

<!-- Sharding-JDBC -->
<dependency>
    <groupId>org.apache.shardingsphere</groupId>
    <artifactId>shardingsphere-jdbc-core-spring-boot-starter</artifactId>
    <version>5.1.0</version>
</dependency>
<!-- ShardingJDBC 5.1.0使用druid连接池需要加dbcp依赖 -->
<dependency>
    <groupId>org.apache.tomcat</groupId>
    <artifactId>tomcat-dbcp</artifactId>
    <version>10.0.16</version>
</dependency>

<!-- MyBatis-Plus -->
<dependency>
    <groupId>***.baomidou</groupId>
    <artifactId>mybatis-plus-boot-starter</artifactId>
    <version>${mybatisplus.version}</version>
</dependency>
<!-- Mybatis的分页插件 -->
<dependency>
    <groupId>***.github.pagehelper</groupId>
    <artifactId>pagehelper-spring-boot-starter</artifactId>
    <version>1.3.0</version>
</dependency>

2.创建表结构

-- ------------------------------
-- 用户表
-- ------------------------------
CREATE TABLE `t_user` (
  `id` bigint(16) NOT NULL ***MENT '主键',
  `username` varchar(64) NOT NULL ***MENT '用户名',
  `password` varchar(64) NOT NULL ***MENT '密码',
  `age` int(8) NOT NULL ***MENT '年龄',
  `create_time` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP ***MENT '创建时间',
  `update_time` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP ***MENT '更新时间',
  PRIMARY KEY (`id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8 ***MENT='用户表';

-- ------------------------------
-- 用户表202201
-- ------------------------------
CREATE TABLE `t_user_202201` (
  `id` bigint(16) NOT NULL ***MENT '主键',
  `username` varchar(64) NOT NULL ***MENT '用户名',
  `password` varchar(64) NOT NULL ***MENT '密码',
  `age` int(8) NOT NULL ***MENT '年龄',
  `create_time` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP ***MENT '创建时间',
  `update_time` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP ***MENT '更新时间',
  PRIMARY KEY (`id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8 ***MENT='用户表202201';

3.yml 配置

server:
  port: 8081

spring:
  ### 处理连接池冲突 #####
  main:
    allow-bean-definition-overriding: true
  shardingsphere:
    # 是否启用 Sharding
    enabled: true
    # 打印sql
#    props:
#      sql-show: true
    datasource:
      names: mydb
      mydb:
        type: ***.alibaba.druid.pool.DruidDataSource
        url: jdbc:mysql://localhost:3306/mydb?useUnicode=true&characterEncoding=UTF-8&serverTimezone=Asia/Shanghai
        driver-class-name: ***.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
    rules:
      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
            tableStrategy:
              # 使用标准分片策略
              standard:
                # 配置分片字段
                shardingColumn: create_time
                # 分片算法名称，不支持大写字母和下划线，否则启动就会报错
                shardingAlgorithmName: time-sharding-algorithm
        # 分片算法配置
        shardingAlgorithms:
          # 分片算法名称，不支持大写字母和下划线，否则启动就会报错
          time-sharding-algorithm:
            # 类型：自定义策略
            type: CLASS_BASED
            props:
              # 分片策略
              strategy: standard
              # 分片算法类
              algorithmClassName: ***.demo.module.config.sharding.TimeShardingAlgorithm

# 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: ***.demo.project.*.entity
  # 测试环境打印sql
  configuration:
    log-impl: org.apache.ibatis.logging.stdout.StdOutImpl

pagehelper:
  helperDialect: postgresql

4.TimeShardingAlgorithm.java 分片算法类

import ***.demo.module.config.sharding.enums.ShardingTableCacheEnum;
import ***.google.***mon.collect.Range;
import lombok.extern.slf4j.Slf4j;
import org.apache.shardingsphere.sharding.api.sharding.standard.PreciseShardingValue;
import org.apache.shardingsphere.sharding.api.sharding.standard.RangeShardingValue;
import org.apache.shardingsphere.sharding.api.sharding.standard.StandardShardingAlgorithm;

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 ACGkaka
 * @date 2022/12/20 11:33
 */
@Slf4j
public class TimeShardingAlgorithm implements StandardShardingAlgorithm<LocalDateTime> {

    /**
     * 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_contract_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<LocalDateTime> preciseShardingValue) {
        String logicTableName = preciseShardingValue.getLogicTableName();
        ShardingTableCacheEnum logicTable = ShardingTableCacheEnum.of(logicTableName);
        if (logicTable == null) {
            log.error(">>>>>>>>>> 【ERROR】数据表类型错误，请稍后重试，logicTableNames：{}，logicTableName:{}",
                    ShardingTableCacheEnum.logicTableNames(), logicTableName);
            throw new IllegalArgumentException("数据表类型错误，请稍后重试");
        }

        /// 打印分片信息
        log.info(">>>>>>>>>> 【INFO】精确分片，节点配置表名：{}，数据库缓存表名：{}", tableNames, logicTable.resultTableNamesCache());

        LocalDateTime dateTime = preciseShardingValue.getValue();
        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
        if (!tableNames.contains(resultTableName)){
            tableNames.add(resultTableName);
        }
        return ShardingAlgorithmTool.getShardingTableAndCreate(logicTable, 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<LocalDateTime> rangeShardingValue) {
        String logicTableName = rangeShardingValue.getLogicTableName();
        ShardingTableCacheEnum logicTable = ShardingTableCacheEnum.of(logicTableName);
        if (logicTable == null) {
            log.error(">>>>>>>>>> 【ERROR】逻辑表范围异常，请稍后重试，logicTableNames：{}，logicTableName:{}",
                    ShardingTableCacheEnum.logicTableNames(), logicTableName);
            throw new IllegalArgumentException("逻辑表范围异常，请稍后重试");
        }

        /// 打印分片信息
        log.info(">>>>>>>>>> 【INFO】范围分片，节点配置表名：{}，数据库缓存表名：{}", tableNames, logicTable.resultTableNamesCache());

        // between and 的起始值
        Range<LocalDateTime> valueRange = rangeShardingValue.getValueRange();
        boolean hasLowerBound = valueRange.hasLowerBound();
        boolean hasUpperBound = valueRange.hasUpperBound();

        // 获取最大值和最小值
        Set<String> tableNameCache = logicTable.resultTableNamesCache();
        LocalDateTime min = hasLowerBound ? valueRange.lowerEndpoint() :getLowerEndpoint(tableNameCache);
        LocalDateTime max = hasUpperBound ? valueRange.upperEndpoint() :getUpperEndpoint(tableNameCache);

        // 循环计算分表范围
        Set<String> resultTableNames = new LinkedHashSet<>();
        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(logicTable, resultTableNames);
    }

    @Override
    public void init() {

    }

    @Override
    public String getType() {
        return null;
    }

    // --------------------------------------------------------------------------------------------------------------
    // 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(***parator.***paring(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(***parator.***paring(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 ***.alibaba.druid.util.StringUtils;
import ***.demo.module.config.sharding.enums.ShardingTableCacheEnum;
import ***.demo.module.utils.SpringUtil;
import lombok.extern.slf4j.Slf4j;
import org.apache.shardingsphere.driver.jdbc.core.datasource.ShardingSphereDataSource;
import org.apache.shardingsphere.infra.config.RuleConfiguration;
import org.apache.shardingsphere.mode.manager.ContextManager;
import org.apache.shardingsphere.sharding.algorithm.config.AlgorithmProvidedShardingRuleConfiguration;
import org.apache.shardingsphere.sharding.api.config.rule.ShardingTableRuleConfiguration;
import org.apache.shardingsphere.sharding.rule.TableRule;
import org.springframework.core.env.Environment;

import javax.sql.DataSource;
import java.lang.reflect.Field;
import java.lang.reflect.Modifier;
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 ACGkaka
 * @date 2022/12/20 14:03
 */
@Slf4j
public class ShardingAlgorithmTool {

    /** 表分片符号，例：t_user_202201 中，分片符号为 "_" */
    private static final String TABLE_SPLIT_SYMBOL = "_";

    /** 数据库配置 */
    private static final Environment ENV = SpringUtil.getApplicationContext().getEnvironment();
    private static final String DATASOURCE_URL = ENV.getProperty("spring.shardingsphere.datasource.mydb.url");
    private static final String DATASOURCE_USERNAME = ENV.getProperty("spring.shardingsphere.datasource.mydb.username");
    private static final String DATASOURCE_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 logicTable 逻辑表
     * @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(ShardingTableCacheEnum logicTable, Collection<String> resultTableNames) {
        return resultTableNames.stream().map(o -> getShardingTableAndCreate(logicTable, 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 logicTable 逻辑表
     * @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(ShardingTableCacheEnum logicTable, String resultTableName) {
        // 缓存中有此表则返回，没有则判断创建
        if (logicTable.resultTableNamesCache().contains(resultTableName)) {
            return resultTableName;
        } else {
            // 未创建的表返回逻辑空表
            boolean isSu***ess = createShardingTable(logicTable, resultTableName);
            return isSu***ess ? resultTableName : logicTable.logicTableName();
        }
    }

    /**
     * 重载全部缓存
     */
    public static void tableNameCacheReloadAll() {
        Arrays.stream(ShardingTableCacheEnum.values()).forEach(ShardingAlgorithmTool::tableNameCacheReload);
    }

    /**
     * 重载指定分表缓存
     * @param logicTable 逻辑表，例：t_user
     */
    public static void tableNameCacheReload(ShardingTableCacheEnum logicTable) {
        // 读取数据库中所有表名
        List<String> tableNameList = getAllTableNameBySchema(logicTable);
        // 更新缓存、配置（原子操作）
        logicTable.atomicUpdateCacheAndActualDataNodes(tableNameList);
        // 删除旧的缓存（如果存在）
        logicTable.resultTableNamesCache().clear();
        // 写入新的缓存
        logicTable.resultTableNamesCache().addAll(tableNameList);
        // 动态更新配置 actualDataNodes
        actualDataNodesRefresh(logicTable.logicTableName(), tableNameList);
    }

    /**
     * 获取所有表名
     * @return 表名集合
     * @param logicTable 逻辑表
     */
    public static List<String> getAllTableNameBySchema(ShardingTableCacheEnum logicTable) {
        List<String> tableNames = new ArrayList<>();
        if (StringUtils.isEmpty(DATASOURCE_URL) || StringUtils.isEmpty(DATASOURCE_USERNAME) || StringUtils.isEmpty(DATASOURCE_PASSWORD)) {
            log.error(">>>>>>>>>> 【ERROR】数据库连接配置有误，请稍后重试，URL:{}, username:{}, password:{}", DATASOURCE_URL, DATASOURCE_USERNAME, DATASOURCE_PASSWORD);
            throw new IllegalArgumentException("数据库连接配置有误，请稍后重试");
        }
        try (Connection conn = DriverManager.getConnection(DATASOURCE_URL, DATASOURCE_USERNAME, DATASOURCE_PASSWORD);
             Statement st = conn.createStatement()) {
            String logicTableName = logicTable.logicTableName();
            try (ResultSet rs = st.executeQuery("show TABLES like '" + logicTableName + TABLE_SPLIT_SYMBOL + "%'")) {
                while (rs.next()) {
                    String tableName = rs.getString(1);
                    // 匹配分表格式 例：^(t\_contract_\d{6})$
                    if (tableName != null && tableName.matches(String.format("^(%s\\d{6})$", logicTableName + TABLE_SPLIT_SYMBOL))) {
                        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;
    }

    /**
     * 动态更新配置 actualDataNodes
     *
     * @param logicTableName  逻辑表名
     * @param tableNamesCache 真实表名集合
     */
    public static void actualDataNodesRefresh(String logicTableName, List<String> tableNamesCache)  {
        try {
            // 获取数据分片节点
            String dbName = "mydb";
            log.info(">>>>>>>>>> 【INFO】更新分表配置，logicTableName:{}，tableNamesCache:{}", logicTableName, tableNamesCache);

            // generate actualDataNodes
            String newActualDataNodes = tableNamesCache.stream().map(o -> String.format("%s.%s", dbName, o)).collect(Collectors.joining(","));
            ShardingSphereDataSource shardingSphereDataSource = SpringUtil.getBean(ShardingSphereDataSource.class);
            updateShardRuleActualDataNodes(shardingSphereDataSource, logicTableName, newActualDataNodes);
        }catch (Exception e){
            log.error("初始化 动态表单失败，原因：{}", e.getMessage(), e);
        }
    }


    // --------------------------------------------------------------------------------------------------------------
    // 私有方法
    // --------------------------------------------------------------------------------------------------------------


    /**
     * 刷新ActualDataNodes
     */
    private static void updateShardRuleActualDataNodes(ShardingSphereDataSource dataSource, String logicTableName, String newActualDataNodes) {
        // Context manager.
        ContextManager contextManager = dataSource.getContextManager();

        // Rule configuration.
        String schemaName = "logic_db";
        Collection<RuleConfiguration> newRuleConfigList = new LinkedList<>();
        Collection<RuleConfiguration> oldRuleConfigList = dataSource.getContextManager()
                .getMetaDataContexts()
                .getMetaData(schemaName)
                .getRuleMetaData()
                .getConfigurations();

        for (RuleConfiguration oldRuleConfig : oldRuleConfigList) {
            if (oldRuleConfig instanceof AlgorithmProvidedShardingRuleConfiguration) {

                // Algorithm provided sharding rule configuration
                AlgorithmProvidedShardingRuleConfiguration oldAlgorithmConfig = (AlgorithmProvidedShardingRuleConfiguration) oldRuleConfig;
                AlgorithmProvidedShardingRuleConfiguration newAlgorithmConfig = new AlgorithmProvidedShardingRuleConfiguration();

                // Sharding table rule configuration Collection
                Collection<ShardingTableRuleConfiguration> newTableRuleConfigList = new LinkedList<>();
                Collection<ShardingTableRuleConfiguration> oldTableRuleConfigList = oldAlgorithmConfig.getTables();

                oldTableRuleConfigList.forEach(oldTableRuleConfig -> {
                    if (logicTableName.equals(oldTableRuleConfig.getLogicTable())) {
                        ShardingTableRuleConfiguration newTableRuleConfig = new ShardingTableRuleConfiguration(oldTableRuleConfig.getLogicTable(), newActualDataNodes);
                        newTableRuleConfig.setTableShardingStrategy(oldTableRuleConfig.getTableShardingStrategy());
                        newTableRuleConfig.setDatabaseShardingStrategy(oldTableRuleConfig.getDatabaseShardingStrategy());
                        newTableRuleConfig.setKeyGenerateStrategy(oldTableRuleConfig.getKeyGenerateStrategy());

                        newTableRuleConfigList.add(newTableRuleConfig);
                    } else {
                        newTableRuleConfigList.add(oldTableRuleConfig);
                    }
                });

                newAlgorithmConfig.setTables(newTableRuleConfigList);
                newAlgorithmConfig.setAutoTables(oldAlgorithmConfig.getAutoTables());
                newAlgorithmConfig.setBindingTableGroups(oldAlgorithmConfig.getBindingTableGroups());
                newAlgorithmConfig.setBroadcastTables(oldAlgorithmConfig.getBroadcastTables());
                newAlgorithmConfig.setDefaultDatabaseShardingStrategy(oldAlgorithmConfig.getDefaultDatabaseShardingStrategy());
                newAlgorithmConfig.setDefaultTableShardingStrategy(oldAlgorithmConfig.getDefaultTableShardingStrategy());
                newAlgorithmConfig.setDefaultKeyGenerateStrategy(oldAlgorithmConfig.getDefaultKeyGenerateStrategy());
                newAlgorithmConfig.setDefaultShardingColumn(oldAlgorithmConfig.getDefaultShardingColumn());
                newAlgorithmConfig.setShardingAlgorithms(oldAlgorithmConfig.getShardingAlgorithms());
                newAlgorithmConfig.setKeyGenerators(oldAlgorithmConfig.getKeyGenerators());

                newRuleConfigList.add(newAlgorithmConfig);
            }
        }

        // update context
        contextManager.alterRuleConfiguration(schemaName, newRuleConfigList);
    }

    /**
     * 创建分表
     * @param logicTable 逻辑表
     * @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(ShardingTableCacheEnum logicTable, String resultTableName) {
        // 根据日期判断，当前月份之后分表不提前创建
        String month = resultTableName.replace(logicTable.logicTableName() + TABLE_SPLIT_SYMBOL,"");
        YearMonth shardingMonth = YearMonth.parse(month, DateTimeFormatter.ofPattern("yyyyMM"));
        if (shardingMonth.isAfter(YearMonth.now())) {
            return false;
        }

        synchronized (logicTable.logicTableName().intern()) {
            // 缓存中有此表 返回
            if (logicTable.resultTableNamesCache().contains(resultTableName)) {
                return false;
            }
            // 缓存中无此表，则建表并添加缓存
            executeSql(Collections.singletonList("CREATE TABLE IF NOT EXISTS `" + resultTableName + "` LIKE `" + logicTable.logicTableName() + "`;"));
            // 缓存重载
            tableNameCacheReload(logicTable);
        }
        return true;
    }

    /**
     * 执行SQL
     * @param sqlList SQL集合
     */
    private static void executeSql(List<String> sqlList) {
        if (StringUtils.isEmpty(DATASOURCE_URL) || StringUtils.isEmpty(DATASOURCE_USERNAME) || StringUtils.isEmpty(DATASOURCE_PASSWORD)) {
            log.error(">>>>>>>>>> 【ERROR】数据库连接配置有误，请稍后重试，URL:{}, username:{}, password:{}", DATASOURCE_URL, DATASOURCE_USERNAME, DATASOURCE_PASSWORD);
            throw new IllegalArgumentException("数据库连接配置有误，请稍后重试");
        }
        try (Connection conn = DriverManager.getConnection(DATASOURCE_URL, DATASOURCE_USERNAME, DATASOURCE_PASSWORD)) {
            try (Statement st = conn.createStatement()) {
                conn.setAuto***mit(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");
        }
    }

}

6.ShardingTablesLoadRunner.java 初始化缓存类

import org.springframework.boot.***mandLineRunner;
import org.springframework.core.annotation.Order;
import org.springframework.stereotype.***ponent;

/**
 * <p> @Title ShardingTablesLoadRunner
 * <p> @Description 项目启动后，读取已有分表，进行缓存
 *
 * @author ACGkaka
 * @date 2022/12/20 15:41
 */
@Order(value = 1) // 数字越小，越先执行
@***ponent
public class ShardingTablesLoadRunner implements ***mandLineRunner {

    @Override
    public void run(String... args) {
        // 读取已有分表，进行缓存
        ShardingAlgorithmTool.tableNameCacheReloadAll();
    }
}

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.***ponent;

/**
 * <p> @Title SpringUtil
 * <p> @Description Spring工具类
 *
 * @author ACGkaka
 * @date 2022/12/20 14:39
 */
@***ponent
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.源码测试

import ***.demo.module.entity.User;
import ***.demo.module.service.UserService;
import ***.github.pagehelper.PageHelper;
import ***.github.pagehelper.PageInfo;
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 UserService userService;

    @Test
    void saveTest() {
        List<User> 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);
        users.add(new User("ACGkaka_1", "123456", 10, time1, time1));
        users.add(new User("ACGkaka_2", "123456", 11, time2, time2));
        userService.saveBatch(users);
    }

    @Test
    void listTest() {
        PageHelper.startPage(1, 1);
        List<User> users = userService.list();
        PageInfo<User> pageInfo = new PageInfo<>(users);
        System.out.println(">>>>>>>>>> 【Result】<<<<<<<<<< ");
        System.out.println(pageInfo);
    }
}

9.测试结果

新增和查询可以正常分页查询，测试成功。

10.代码地址

地址： https://gitee.***/acgkaka/SpringBootExamples/tree/master/springboot-sharding-jdbc-month-5.1.0





参考地址：

1.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.***/weixin_51216079/article/details/123873967

2.shardingjdbc 5.1 是否支持java 动态加载 数据节点，而不是在配置文件中用表达式定义好，https://***munity.sphere-ex.***/t/topic/1025

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CSS教程_站长资源网 » Sharding-JDBC（六）5.1.0版本，实现按月分表、自动建表、自动刷新节点
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