SpringBoot 2.0 整合sharding-jdbc中間件實現(xiàn)數(shù)據(jù)分庫分表

更新時間：2019年06月04日 09:40:19 作者：知了一笑

這篇文章主要介紹了SpringBoot 2.0 整合sharding-jdbc中間件，實現(xiàn)數(shù)據(jù)分庫分表，本文圖文并茂給大家介紹的非常詳細，具有一定的參考借鑒價值 ,需要的朋友可以參考下

一、水平分割

1、水平分庫
1)、概念：
以字段為依據(jù)，按照一定策略，將一個庫中的數(shù)據(jù)拆分到多個庫中。
2)、結(jié)果
每個庫的結(jié)構(gòu)都一樣；數(shù)據(jù)都不一樣；
所有庫的并集是全量數(shù)據(jù)；
2、水平分表
1)、概念
以字段為依據(jù)，按照一定策略，將一個表中的數(shù)據(jù)拆分到多個表中。
2)、結(jié)果
每個表的結(jié)構(gòu)都一樣；數(shù)據(jù)都不一樣；
所有表的并集是全量數(shù)據(jù)；

二、Shard-jdbc 中間件

1、架構(gòu)圖

2、特點

1)、Sharding-JDBC直接封裝JDBC API，舊代碼遷移成本幾乎為零。
2)、適用于任何基于Java的ORM框架，如Hibernate、Mybatis等。
3)、可基于任何第三方的數(shù)據(jù)庫連接池，如DBCP、C3P0、 BoneCP、Druid等。
4)、以jar包形式提供服務，無proxy代理層，無需額外部署，無其他依賴。
5)、分片策略靈活，可支持等號、between、in等多維度分片，也可支持多分片鍵。
6)、SQL解析功能完善，支持聚合、分組、排序、limit、or等查詢。

三、項目演示

1、項目結(jié)構(gòu)

springboot 2.0 版本
druid 1.1.13 版本
sharding-jdbc 3.1 版本

2、數(shù)據(jù)庫配置

一臺基礎庫映射（shard_one）
兩臺庫做分庫分表（shard_two，shard_three）。
表使用：table_one，table_two

3、核心代碼塊

數(shù)據(jù)源配置文件

spring:
 datasource:
  # 數(shù)據(jù)源：shard_one
  dataOne:
   type: com.alibaba.druid.pool.DruidDataSource
   druid:
    driverClassName: com.mysql.jdbc.Driver
    url: jdbc:mysql://localhost:3306/shard_one?useUnicode=true&characterEncoding=UTF8&zeroDateTimeBehavior=convertToNull&useSSL=false
    username: root
    password: 123
    initial-size: 10
    max-active: 100
    min-idle: 10
    max-wait: 60000
    pool-prepared-statements: true
    max-pool-prepared-statement-per-connection-size: 20
    time-between-eviction-runs-millis: 60000
    min-evictable-idle-time-millis: 300000
    max-evictable-idle-time-millis: 60000
    validation-query: SELECT 1 FROM DUAL
    # validation-query-timeout: 5000
    test-on-borrow: false
    test-on-return: false
    test-while-idle: true
    connectionProperties: druid.stat.mergeSql=true;druid.stat.slowSqlMillis=5000
  # 數(shù)據(jù)源：shard_two
  dataTwo:
   type: com.alibaba.druid.pool.DruidDataSource
   druid:
    driverClassName: com.mysql.jdbc.Driver
    url: jdbc:mysql://localhost:3306/shard_two?useUnicode=true&characterEncoding=UTF8&zeroDateTimeBehavior=convertToNull&useSSL=false
    username: root
    password: 123
    initial-size: 10
    max-active: 100
    min-idle: 10
    max-wait: 60000
    pool-prepared-statements: true
    max-pool-prepared-statement-per-connection-size: 20
    time-between-eviction-runs-millis: 60000
    min-evictable-idle-time-millis: 300000
    max-evictable-idle-time-millis: 60000
    validation-query: SELECT 1 FROM DUAL
    # validation-query-timeout: 5000
    test-on-borrow: false
    test-on-return: false
    test-while-idle: true
    connectionProperties: druid.stat.mergeSql=true;druid.stat.slowSqlMillis=5000
  # 數(shù)據(jù)源：shard_three
  dataThree:
   type: com.alibaba.druid.pool.DruidDataSource
   druid:
    driverClassName: com.mysql.jdbc.Driver
    url: jdbc:mysql://localhost:3306/shard_three?useUnicode=true&characterEncoding=UTF8&zeroDateTimeBehavior=convertToNull&useSSL=false
    username: root
    password: 123
    initial-size: 10
    max-active: 100
    min-idle: 10
    max-wait: 60000
    pool-prepared-statements: true
    max-pool-prepared-statement-per-connection-size: 20
    time-between-eviction-runs-millis: 60000
    min-evictable-idle-time-millis: 300000
    max-evictable-idle-time-millis: 60000
    validation-query: SELECT 1 FROM DUAL
    # validation-query-timeout: 5000
    test-on-borrow: false
    test-on-return: false
    test-while-idle: true
    connectionProperties: druid.stat.mergeSql=true;druid.stat.slowSqlMillis=5000

數(shù)據(jù)庫分庫策略

/**
 * 數(shù)據(jù)庫映射計算
 */
public class DataSourceAlg implements PreciseShardingAlgorithm<String> {

  private static Logger LOG = LoggerFactory.getLogger(DataSourceAlg.class);
  @Override
  public String doSharding(Collection<String> names, PreciseShardingValue<String> value) {
    LOG.debug("分庫算法參數(shù) {},{}",names,value);
    int hash = HashUtil.rsHash(String.valueOf(value.getValue()));
    return "ds_" + ((hash % 2) + 2) ;
  }
}

數(shù)據(jù)表1分表策略

/**
 * 分表算法
 */
public class TableOneAlg implements PreciseShardingAlgorithm<String> {
  private static Logger LOG = LoggerFactory.getLogger(TableOneAlg.class);
  /**
   * 該表每個庫分5張表
   */
  @Override
  public String doSharding(Collection<String> names, PreciseShardingValue<String> value) {
    LOG.debug("分表算法參數(shù) {},{}",names,value);
    int hash = HashUtil.rsHash(String.valueOf(value.getValue()));
    return "table_one_" + (hash % 5+1);
  }
}

數(shù)據(jù)表2分表策略

/**
 * 分表算法
 */
public class TableTwoAlg implements PreciseShardingAlgorithm<String> {
  private static Logger LOG = LoggerFactory.getLogger(TableTwoAlg.class);
  /**
   * 該表每個庫分5張表
   */
  @Override
  public String doSharding(Collection<String> names, PreciseShardingValue<String> value) {
    LOG.debug("分表算法參數(shù) {},{}",names,value);
    int hash = HashUtil.rsHash(String.valueOf(value.getValue()));
    return "table_two_" + (hash % 5+1);
  }
}

數(shù)據(jù)源集成配置

/**
 * 數(shù)據(jù)庫分庫分表配置
 */
@Configuration
public class ShardJdbcConfig {
  // 省略了 druid 配置，源碼中有
  /**
   * Shard-JDBC 分庫配置
   */
  @Bean
  public DataSource dataSource (@Autowired DruidDataSource dataOneSource,
                 @Autowired DruidDataSource dataTwoSource,
                 @Autowired DruidDataSource dataThreeSource) throws Exception {
    ShardingRuleConfiguration shardJdbcConfig = new ShardingRuleConfiguration();
    shardJdbcConfig.getTableRuleConfigs().add(getTableRule01());
    shardJdbcConfig.getTableRuleConfigs().add(getTableRule02());
    shardJdbcConfig.setDefaultDataSourceName("ds_0");
    Map<String,DataSource> dataMap = new LinkedHashMap<>() ;
    dataMap.put("ds_0",dataOneSource) ;
    dataMap.put("ds_2",dataTwoSource) ;
    dataMap.put("ds_3",dataThreeSource) ;
    Properties prop = new Properties();
    return ShardingDataSourceFactory.createDataSource(dataMap, shardJdbcConfig, new HashMap<>(), prop);
  }

  /**
   * Shard-JDBC 分表配置
   */
  private static TableRuleConfiguration getTableRule01() {
    TableRuleConfiguration result = new TableRuleConfiguration();
    result.setLogicTable("table_one");
    result.setActualDataNodes("ds_${2..3}.table_one_${1..5}");
    result.setDatabaseShardingStrategyConfig(new StandardShardingStrategyConfiguration("phone", new DataSourceAlg()));
    result.setTableShardingStrategyConfig(new StandardShardingStrategyConfiguration("phone", new TableOneAlg()));
    return result;
  }
  private static TableRuleConfiguration getTableRule02() {
    TableRuleConfiguration result = new TableRuleConfiguration();
    result.setLogicTable("table_two");
    result.setActualDataNodes("ds_${2..3}.table_two_${1..5}");
    result.setDatabaseShardingStrategyConfig(new StandardShardingStrategyConfiguration("phone", new DataSourceAlg()));
    result.setTableShardingStrategyConfig(new StandardShardingStrategyConfiguration("phone", new TableTwoAlg()));
    return result;
  }
}

測試代碼執(zhí)行流程

@RestController
public class ShardController {
  @Resource
  private ShardService shardService ;
  /**
   * 1、建表流程
   */
  @RequestMapping("/createTable")
  public String createTable (){
    shardService.createTable();
    return "success" ;
  }
  /**
   * 2、生成表 table_one 數(shù)據(jù)
   */
  @RequestMapping("/insertOne")
  public String insertOne (){
    shardService.insertOne();
    return "SUCCESS" ;
  }
  /**
   * 3、生成表 table_two 數(shù)據(jù)
   */
  @RequestMapping("/insertTwo")
  public String insertTwo (){
    shardService.insertTwo();
    return "SUCCESS" ;
  }
  /**
   * 4、查詢表 table_one 數(shù)據(jù)
   */
  @RequestMapping("/selectOneByPhone/{phone}")
  public TableOne selectOneByPhone (@PathVariable("phone") String phone){
    return shardService.selectOneByPhone(phone);
  }
  /**
   * 5、查詢表 table_one 數(shù)據(jù)
   */
  @RequestMapping("/selectTwoByPhone/{phone}")
  public TableTwo selectTwoByPhone (@PathVariable("phone") String phone){
    return shardService.selectTwoByPhone(phone);
  }
}

四、項目源碼

GitHub：知了一笑

https://github.com/cicadasmile/middle-ware-parent

總結(jié)

以上所述是小編給大家介紹的SpringBoot 2.0 整合sharding-jdbc中間件實現(xiàn)數(shù)據(jù)分庫分表,希望對大家有所幫助，如果大家有任何疑問請給我留言，小編會及時回復大家的。在此也非常感謝大家對腳本之家網(wǎng)站的支持！
如果你覺得本文對你有幫助，歡迎轉(zhuǎn)載，煩請注明出處，謝謝！

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