ShardingJDBC

一个客户端数据库分片库

原理

简单使用

<dependency>    <groupId>io.shardingjdbc</groupId>    <artifactId>sharding-jdbc-core</artifactId>    <version>2.0.3</version></dependency>

#shardingjdbc配置sharding:  jdbc:    data-sources:      ###配置第一个从数据库      ds_slave_0:        password: 123        jdbc-url: jdbc:mysql://192.168.182.132:3306/test?useUnicode=true&characterEncoding=utf-8&useSSL=true        driver-class-name: com.mysql.jdbc.Driver        username: root      ###主数据库配置      ds_master:        password: 123        jdbc-url: jdbc:mysql://192.168.182.131:3306/test?useUnicode=true&characterEncoding=utf-8&useSSL=true        driver-class-name: com.mysql.jdbc.Driver        username: root    ###配置读写分离    master-slave-rule:      ###配置从库选择策略，提供轮询与随机，这里选择用轮询      load-balance-algorithm-type: round_robin      ####指定从数据库      slave-data-source-names: ds_slave_0      name: ds_ms      ####指定主数据库      master-data-source-name: ds_master

@Configuration@EnableConfigurationProperties(ShardingMasterSlaveConfig.class)@Log4j2// 读取ds_master主数据源和读写分离配置@ConditionalOnProperty({ "sharding.jdbc.data-sources.ds_master.jdbc-url",        "sharding.jdbc.master-slave-rule.master-data-source-name" })public class ShardingDataSourceConfig {    @Autowired    private ShardingMasterSlaveConfig shardingMasterSlaveConfig;    @Bean    public DataSource masterSlaveDataSource() throws SQLException {        final Map<String, DataSource> dataSourceMap = Maps.newHashMap();        dataSourceMap.putAll(shardingMasterSlaveConfig.getDataSources());        final Map<String, Object> newHashMap = Maps.newHashMap();        // 创建 MasterSlave数据源        DataSource dataSource = MasterSlaveDataSourceFactory.createDataSource(dataSourceMap,                shardingMasterSlaveConfig.getMasterSlaveRule(), newHashMap);        log.info("masterSlaveDataSource config complete");        return dataSource;    }}@Data@ConfigurationProperties(prefix = "sharding.jdbc")public class ShardingMasterSlaveConfig {    // 存放本地多个数据源    private Map<String, HikariDataSource> dataSources = new HashMap<>();    private MasterSlaveRuleConfiguration masterSlaveRule;}

分表

    private DataSource buildDataSource() {        // 1.设置分库映射        Map<String, DataSource> dataSourceMap = new HashMap<>(2);        dataSourceMap.put("ds_0", createDataSource("ds_0"));        // dataSourceMap.put("ds_1", createDataSource("ds_1"));        // 设置默认db为ds_0，也就是为那些没有配置分库分表策略的指定的默认库        // 如果只有一个库，也就是不需要分库的话，map里只放一个映射就行了，只有一个库时不需要指定默认库，        // 但2个及以上时必须指定默认库，否则那些没有配置策略的表将无法操作数据        DataSourceRule rule = new DataSourceRule(dataSourceMap, "ds_0");        // 2.设置分表映射，将t_order_0和t_order_1两个实际的表映射到t_order逻辑表        TableRule orderTableRule = TableRule.builder("t_order").actualTables(Arrays.asList("t_order_0", "t_order_1"))                .dataSourceRule(rule).build();        // 3.具体的分库分表策略        ShardingRule shardingRule = ShardingRule.builder().dataSourceRule(rule)                .tableRules(Arrays.asList(orderTableRule))                // 根据userid分片字段                .tableShardingStrategy(new TableShardingStrategy("user_id", new TableShardingAlgorithm())).build();        // 创建数据源        DataSource dataSource = ShardingDataSourceFactory.createDataSource(shardingRule);        return dataSource;    }    private DataSource createDataSource(String dataSourceName) {        // 使用druid连接数据库        DruidDataSource druidDataSource = new DruidDataSource();        druidDataSource.setDriverClassName(className);        druidDataSource.setUrl(String.format(url, dataSourceName));        druidDataSource.setUsername(username);        druidDataSource.setPassword(password);        return druidDataSource;    }

public class TableShardingAlgorithm implements SingleKeyTableShardingAlgorithm<Long> {    // sql 中关键字 匹配符为 =的时候，表的路由函数    @Override    public String doEqualSharding(Collection<String> availableTargetNames, ShardingValue<Long> shardingValue) {        for (String tableName : availableTargetNames) {            if (tableName.endsWith(shardingValue.getValue() % 2 + "")) {                return tableName;            }        }        throw new IllegalArgumentException();    }    ...}

spring boot快速整合

<dependency>    <groupId>io.shardingsphere</groupId>    <artifactId>sharding-jdbc-spring-boot-starter</artifactId>    <version>3.0.0.M3</version></dependency>

sharding:  jdbc:    ####ds1    datasource:      names: ds0      ds0:        password: 123        type: com.alibaba.druid.pool.DruidDataSource        driver-class-name: com.mysql.cj.jdbc.Driver        url: jdbc:mysql://192.168.182.131:3306/ds_0        username: root    config:      sharding:        tables:          t_order:            table-strategy:              inline:                #### 根据userid 进行分片                sharding-column: user_id                algorithm-expression: ds_0.t_order_$->{user_id % 2}            actual-data-nodes: ds0.t_order_$->{0..1}        props:          sql:            ### 开启分片日志            show: true