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。
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。
org.apache.shardingsphere shardingsphere-jdbc-core-spring-boot-starter 5.1.0 org.apache.tomcat tomcat-dbcp 10.0.16 com.baomidou mybatis-plus-boot-starter ${mybatisplus.version} com.github.pagehelper pagehelper-spring-boot-starter 1.3.0
-- ------------------------------ -- 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';
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: 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 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: com.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: cn.demo.project.*.entity # 测试环境打印sql configuration: log-impl: org.apache.ibatis.logging.stdout.StdOutImpl pagehelper: helperDialect: postgresql
import com.demo.module.config.sharding.enums.ShardingTableCacheEnum; import com.google.common.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; /** *@Title TimeShardingAlgorithm *
@Description 分片算法,按月分片 * * @author ACGkaka * @date 2022/12/20 11:33 */ @Slf4j public class TimeShardingAlgorithm implements StandardShardingAlgorithm
{ /** * 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 tableNames, PreciseShardingValue 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 doSharding(Collection tableNames, RangeShardingValue 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 valueRange = rangeShardingValue.getValueRange(); boolean hasLowerBound = valueRange.hasLowerBound(); boolean hasUpperBound = valueRange.hasUpperBound(); // 获取最大值和最小值 Set 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 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 tableNames) { Optional 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 tableNames) { Optional 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"); } } }
import com.alibaba.druid.util.StringUtils; import com.demo.module.config.sharding.enums.ShardingTableCacheEnum; import com.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; /** *@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("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
getShardingTablesAndCreate(ShardingTableCacheEnum logicTable, Collection 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 isSuccess = createShardingTable(logicTable, resultTableName); return isSuccess ? 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 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 getAllTableNameBySchema(ShardingTableCacheEnum logicTable) { List 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 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 newRuleConfigList = new LinkedList<>(); Collection 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 newTableRuleConfigList = new LinkedList<>(); Collection 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 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"); } } }
import org.springframework.boot.CommandLineRunner; import org.springframework.core.annotation.Order; import org.springframework.stereotype.Component; /** *@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 */ @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.tableNameCacheReloadAll(); } }
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 getBean(Class cla) { return applicationContext.getBean(cla); } public static T getBean(String name, Class cal) { return applicationContext.getBean(name, cal); } public static String getProperty(String key) { return applicationContext.getBean(Environment.class).getProperty(key); } }
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() { Listusers = 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 users = userService.list(); PageInfo pageInfo = new PageInfo<>(users); System.out.println(">>>>>>>>>> 【Result】<<<<<<<<<< "); System.out.println(pageInfo); } }
新增和查询可以正常分页查询,测试成功。
地址: https://gitee.com/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.net/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://community.sphere-ex.com/t/topic/1025
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