Sharding-JDBC(九)5.3.0版本,实现按月分表、自动建表、自动刷新节点

目录

    • 一、简介
    • 二、Maven依赖
    • 三、配置文件
      • application.yml
      • sharding.yaml
    • 四、代码实现
      • 1.自动建表、自动刷新节点思路
      • 2.创建表结构
      • 3.TimeShardingAlgorithm.java 分片算法类
      • 4.ShardingAlgorithmTool.java 分片工具类
      • 5.ShardingTablesLoadRunner.java 初始化缓存类
      • 6.SpringUtil.java Spring工具类
    • 五、测试
      • 1.测试代码
      • 2.测试结果
    • 六、代码地址

Sharding-JDBC(九)5.3.0版本,实现按月分表、自动建表、自动刷新节点_第1张图片

一、简介

背景: 之前使用 ShardingSphere-JDBC 的 5.1.0 版本进行数据分片,后来开源组件扫描发现 5.1.0 版本存在如下漏洞,需要升级到 5.3.0 及以上版本

  • Apache ShardingSphere远程代码执行漏洞(CVE-2020-1947): Apache ShardingSphere存在YAML解析远程代码执行漏洞,开发人员直接使用unmarshal方法对输入的YAML直接进行解析,没有做校验,攻击者在相应漏洞触发点输入payload即可完成攻击。

升级到 5.3.0 改动还是很大的,新版本移除了 Spring 全部依赖和配置支持,引入了 ShardingSphereDriver 数据库驱动,也就意味着需要使用新的配置方式

注意:由于 Druid 集成过程中遇到些问题,本文集成内容未使用 Druid 连接池,如果后续集成完毕,会再补充一篇文章说明。

二、Maven依赖


<dependency>
    <groupId>org.apache.shardingspheregroupId>
    <artifactId>shardingsphere-jdbc-coreartifactId>
    <version>5.3.0version>
dependency>

三、配置文件

application.yml

server:
  port: 8081

spring:
  ### 处理连接池冲突 #####
  main:
    allow-bean-definition-overriding: true
  datasource:
    driver-class-name: org.apache.shardingsphere.driver.ShardingSphereDriver
    url: jdbc:shardingsphere:classpath:sharding.yaml

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

pagehelper:
  helperDialect: postgresql

my:
  sharding:
    create-table:
      url: jdbc:mysql://localhost:3306/mydb?useUnicode=true&characterEncoding=UTF-8&serverTimezone=Asia/Shanghai
      username: root
      password: root

sharding.yaml

#
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements.  See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License.  You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#

dataSources:
  ds:
    dataSourceClassName: com.zaxxer.hikari.HikariDataSource
    driverClassName: com.mysql.jdbc.Driver
    jdbcUrl: jdbc:mysql://localhost:3306/mydb?useUnicode=true&characterEncoding=UTF-8&serverTimezone=Asia/Shanghai
    username: root
    password: root

rules:
- !SHARDING
  tables:
    t_user:
      actualDataNodes: ds.t_user
      tableStrategy:
        standard:
          shardingColumn: create_time
          shardingAlgorithmName: auto-custom

  shardingAlgorithms:
    auto-custom:
      type: CLASS_BASED
      props:
        strategy: standard
        algorithmClassName: com.demo.module.config.sharding.TimeShardingAlgorithm
#    auto-interval:
#      type: AUTO_INTERVAL
#      props:
#        datetime-lower: '2023-01-01 00:00:00'
#        datetime-upper: '2023-12-01 00:00:00'
#        # 60 * 60 * 24 * 30=30天
#        sharding-seconds: '2592000'
#    interval:
#      type: INTERVAL
#      props:
#        datetime-pattern: 'yyyy-MM'
#        datetime-lower: '2023-01'
#        datetime-upper: '2023-12'
#        sharding-suffix-pattern: 'yyyyMM'
#        # 间隔大小
#        datetime-interval-amount: 1
#        datetime-interval-unit: 'Months'

props:
  sql-show: false

四、代码实现

1.自动建表、自动刷新节点思路

大概思路为:

  • 配置: 编写配置的时候,我们只编写逻辑表 t_user。
  • 启动初始化: 在启动后执行脚本 LoadRunner.run() 的时候,触发精确分片来初始化数据库中表名到配置中。
  • 建表并刷新配置: 如果初始化后的配置中不存在表名,则创建表并刷新分表配置。

Sharding-JDBC(九)5.3.0版本,实现按月分表、自动建表、自动刷新节点_第2张图片

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.TimeShardingAlgorithm.java 分片算法类

/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License.  You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package com.demo.module.config.sharding;

import com.google.common.collect.Range;
import lombok.Getter;
import lombok.extern.slf4j.Slf4j;
import org.apache.shardingsphere.sharding.api.sharding.ShardingAutoTableAlgorithm;
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;
import java.util.stream.Collectors;

/**
 * 

@Title TimeShardingAlgorithm *

@Description 分片算法,按月分片 * * @author ACGkaka * @date 2022/12/20 11:33 */ @Slf4j public final class TimeShardingAlgorithm implements StandardShardingAlgorithm<LocalDateTime>, ShardingAutoTableAlgorithm { /** * 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 = "_"; @Getter private Properties props; @Getter private int autoTablesAmount; @Override public void init(final Properties props) { this.props = props; } @Override public String doSharding(final Collection<String> availableTargetNames, final PreciseShardingValue<LocalDateTime> preciseShardingValue) { String logicTableName = preciseShardingValue.getLogicTableName(); /// 打印分片信息 log.info(">>>>>>>>>> 【INFO】精确分片,节点配置表名:{}", availableTargetNames); LocalDateTime dateTime = preciseShardingValue.getValue(); String resultTableName = logicTableName + "_" + dateTime.format(TABLE_SHARD_TIME_FORMATTER); // 检查是否需要初始化 if (availableTargetNames.size() == 1) { // 如果只有一个表,说明需要获取所有表名 List<String> allTableNameBySchema = ShardingAlgorithmTool.getAllTableNameBySchema(logicTableName); availableTargetNames.clear(); availableTargetNames.addAll(allTableNameBySchema); autoTablesAmount = allTableNameBySchema.size(); return resultTableName; } return getShardingTableAndCreate(logicTableName, resultTableName, availableTargetNames); } @Override public Collection<String> doSharding(final Collection<String> availableTargetNames, final RangeShardingValue<LocalDateTime> rangeShardingValue) { String logicTableName = rangeShardingValue.getLogicTableName(); /// 打印分片信息 log.info(">>>>>>>>>> 【INFO】范围分片,节点配置表名:{}", availableTargetNames); // 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 LocalDateTime min = hasLowerBound ? valueRange.lowerEndpoint() :getLowerEndpoint(availableTargetNames); LocalDateTime max = hasUpperBound ? valueRange.upperEndpoint() :getUpperEndpoint(availableTargetNames); // 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 getShardingTablesAndCreate(logicTableName, resultTableNames, availableTargetNames); } @Override public String getType() { return "AUTO_CUSTOM"; } // -------------------------------------------------------------------------------------------------------------- // 私有方法 // -------------------------------------------------------------------------------------------------------------- /** * 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 * @param resultTableNames 真实表名,例:t_user_202201 * @param availableTargetNames 可用的数据库表名 * @return 存在于数据库中的真实表名集合 */ public Set<String> getShardingTablesAndCreate(String logicTableName, Collection<String> resultTableNames, Collection<String> availableTargetNames) { return resultTableNames.stream().map(o -> getShardingTableAndCreate(logicTableName, o, availableTargetNames)).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 * @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 */ private String getShardingTableAndCreate(String logicTableName, String resultTableName, Collection<String> availableTargetNames) { // 缓存中有此表则返回,没有则判断创建 if (availableTargetNames.contains(resultTableName)) { return resultTableName; } else { // 检查分表获取的表名不存在,需要自动建表 boolean isSuccess = ShardingAlgorithmTool.createShardingTable(logicTableName, resultTableName); if (isSuccess) { // 如果建表成功,需要更新缓存 availableTargetNames.add(resultTableName); autoTablesAmount++; return resultTableName; } else { // 如果建表失败,返回逻辑空表 return logicTableName; } } } /** * 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"); } } }

4.ShardingAlgorithmTool.java 分片工具类

package com.demo.module.config.sharding;

import com.demo.module.utils.SpringUtil;
import lombok.extern.slf4j.Slf4j;
import org.apache.commons.lang3.StringUtils;
import org.apache.shardingsphere.driver.jdbc.core.datasource.ShardingSphereDataSource;
import org.apache.shardingsphere.infra.config.rule.RuleConfiguration;
import org.apache.shardingsphere.infra.metadata.ShardingSphereMetaData;
import org.apache.shardingsphere.mode.manager.ContextManager;
import org.apache.shardingsphere.sharding.api.config.ShardingRuleConfiguration;
import org.apache.shardingsphere.sharding.api.config.rule.ShardingTableRuleConfiguration;
import org.springframework.core.env.Environment;
import org.springframework.util.ReflectionUtils;

import java.io.File;
import java.lang.reflect.Field;
import java.sql.*;
import java.time.YearMonth;
import java.time.format.DateTimeFormatter;
import java.util.*;

/**
 * 

@Title ShardingAlgorithmTool *

@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("my.sharding.create-table.url"); private static final String DATASOURCE_USERNAME = ENV.getProperty("my.sharding.create-table.username"); private static final String DATASOURCE_PASSWORD = ENV.getProperty("my.sharding.create-table.password"); /** 配置文件路径 */ private static final String CONFIG_FILE = "sharding-tables.yaml"; /** * 获取所有表名 * @return 表名集合 * @param logicTableName 逻辑表 */ public static List<String> getAllTableNameBySchema(String logicTableName) { 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()) { 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; } // -------------------------------------------------------------------------------------------------------------- // 私有方法 // -------------------------------------------------------------------------------------------------------------- /** * 获取数据源 */ // private static Map getDataSourceMap() { // return getActualDataSources().entrySet().stream().filter(entry -> ACTUAL_DATA_SOURCE_NAMES.contains(entry.getKey())).collect(Collectors.toMap(Map.Entry::getKey, Map.Entry::getValue)); // } /** * 获取数据源配置 */ private static File getShardingYAMLFile() { return new File(Objects.requireNonNull( ShardingAlgorithmTool.class.getClassLoader().getResource(CONFIG_FILE), String.format("File `%s` is not existed.", CONFIG_FILE)).getFile()); } /** * 刷新ActualDataNodes */ private static void updateShardRuleActualDataNodes(ShardingSphereDataSource dataSource, String logicTableName, String newActualDataNodes) throws NoSuchFieldException { // Context manager. Field contextManagerField = dataSource.getClass().getDeclaredField("contextManager"); ContextManager contextManager = (ContextManager) ReflectionUtils.getField(contextManagerField, dataSource); // Rule configuration. ShardingSphereMetaData shardingSphereMetaData = contextManager .getMetaDataContexts() .getMetaData(); Collection<RuleConfiguration> newRuleConfigList = new LinkedList<>(); Collection<RuleConfiguration> oldRuleConfigList = shardingSphereMetaData .getGlobalRuleMetaData() .getConfigurations(); for (RuleConfiguration oldRuleConfig : oldRuleConfigList) { if (oldRuleConfig instanceof ShardingRuleConfiguration) { // Algorithm provided sharding rule configuration ShardingRuleConfiguration oldAlgorithmConfig = (ShardingRuleConfiguration) oldRuleConfig; ShardingRuleConfiguration newAlgorithmConfig = new ShardingRuleConfiguration(); // 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 String schemaName = "logic_db"; contextManager.alterRuleConfiguration(schemaName, newRuleConfigList); } /** * 创建分表2 * @param logicTableName 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) */ public static boolean createShardingTable(String logicTableName, 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(logicTableName + TABLE_SPLIT_SYMBOL,""); YearMonth shardingMonth = YearMonth.parse(month, DateTimeFormatter.ofPattern("yyyyMM")); if (shardingMonth.isAfter(YearMonth.now())) { return false; } synchronized (logicTableName.intern()) { // 缓存中无此表,则建表并添加缓存 executeSql(Collections.singletonList("CREATE TABLE IF NOT EXISTS `" + resultTableName + "` LIKE `" + logicTableName + "`;")); } 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.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"); } } }

5.ShardingTablesLoadRunner.java 初始化缓存类

package com.demo.module.config.sharding;

import com.baomidou.mybatisplus.core.conditions.query.LambdaQueryWrapper;
import com.demo.module.entity.User;
import com.demo.module.service.UserService;
import lombok.extern.slf4j.Slf4j;
import org.springframework.boot.CommandLineRunner;
import org.springframework.core.annotation.Order;
import org.springframework.stereotype.Component;

import javax.annotation.Resource;
import java.time.LocalDateTime;

/**
 * 

@Title ShardingTablesLoadRunner *

@Description 项目启动后,读取已有分表,进行缓存 * * @author ACGkaka * @date 2022/12/20 15:41 */ @Slf4j @Order(value = 1) // 数字越小,越先执行 @Component public class ShardingTablesLoadRunner implements CommandLineRunner { @Resource private UserService userService; @Override public void run(String... args) { // 读取已有分表,进行缓存 LambdaQueryWrapper<User> queryWrapper = new LambdaQueryWrapper<>(); queryWrapper.eq(User::getCreateTime, LocalDateTime.now()).last("limit 1"); userService.list(queryWrapper); log.info(">>>>>>>>>> 【ShardingTablesLoadRunner】缓存已有分表成功 <<<<<<<<<<"); } }

6.SpringUtil.java Spring工具类

package com.demo.module.utils;

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;

/**
 * 

@Title SpringUtil *

@Description Spring工具类 * * @author ACGkaka * @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); } }

五、测试

1.测试代码

package com.demo;

import com.demo.module.entity.User;
import com.demo.module.service.UserService;
import com.github.pagehelper.PageHelper;
import com.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> user1s = 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);
        user1s.add(new User("ACGkaka_1", "123456", 10, time1, time1));
        user1s.add(new User("ACGkaka_2", "123456", 11, time2, time2));
        userService.saveBatch(user1s);
    }

    @Test
    void listTest() {
        PageHelper.startPage(1, 1);
        List<User> user1s = userService.list();
        PageInfo<User> pageInfo = new PageInfo<>(user1s);
        System.out.println(">>>>>>>>>> 【Result】<<<<<<<<<< ");
        System.out.println(pageInfo);
    }
}

2.测试结果

Sharding-JDBC(九)5.3.0版本,实现按月分表、自动建表、自动刷新节点_第3张图片

新增和查询可以正常分页查询,测试成功。

六、代码地址

地址: https://gitee.com/acgkaka/SpringBootExamples/tree/master/springboot-sharding-jdbc-month-5.3.0

整理完毕,完结撒花~





参考地址:

1.ShardingSphere 5.3 系列升级解读:Spring 配置升级指南,https://blog.csdn.net/ShardingSphere/article/details/128910559

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