本文介紹了spring boot使用sharding jdbc的配置方式,分享給大家,具體如下:
說明
要排除DataSourceAutoConfiguration,否則多數(shù)據(jù)源無法配置
@SpringBootApplication@EnableAutoConfiguration(exclude={DataSourceAutoConfiguration.class})public class Application { public static void main(String[] args) { SpringApplication.run(Application.class, args); } }
配置的多個(gè)數(shù)據(jù)源交給sharding-jdbc管理,sharding-jdbc創(chuàng)建一個(gè)DataSource數(shù)據(jù)源提供給mybatis使用
官方文檔:http://shardingjdbc.io/index_zh.html
步驟
配置多個(gè)數(shù)據(jù)源,數(shù)據(jù)源的名稱最好要有一定的規(guī)則,方便配置分庫(kù)的計(jì)算規(guī)則
@Bean(initMethod="init", destroyMethod="close", name="dataSource0")@ConfigurationProperties(prefix = "spring.datasource")public DataSource dataSource0(){ return new DruidDataSource();}@Bean(initMethod="init", destroyMethod="close", name="dataSource1")@ConfigurationProperties(prefix = "spring.datasource2")public DataSource dataSource1(){ return new DruidDataSource();}
配置數(shù)據(jù)源規(guī)則,即將多個(gè)數(shù)據(jù)源交給sharding-jdbc管理,并且可以設(shè)置默認(rèn)的數(shù)據(jù)源,當(dāng)表沒有配置分庫(kù)規(guī)則時(shí)會(huì)使用默認(rèn)的數(shù)據(jù)源
@Beanpublic DataSourceRule dataSourceRule(@Qualifier("dataSource0") DataSource dataSource0, @Qualifier("dataSource1") DataSource dataSource1){ Map<String, DataSource> dataSourceMap = new HashMap<>(); dataSourceMap.put("dataSource0", dataSource0); dataSourceMap.put("dataSource1", dataSource1); return new DataSourceRule(dataSourceMap, "dataSource0");}
配置數(shù)據(jù)源策略和表策略,具體策略需要自己實(shí)現(xiàn)
@Beanpublic ShardingRule shardingRule(DataSourceRule dataSourceRule){ //表策略 TableRule orderTableRule = TableRule.builder("t_order") .actualTables(Arrays.asList("t_order_0", "t_order_1")) .tableShardingStrategy(new TableShardingStrategy("order_id", new ModuloTableShardingAlgorithm())) .dataSourceRule(dataSourceRule) .build(); TableRule orderItemTableRule = TableRule.builder("t_order_item") .actualTables(Arrays.asList("t_order_item_0", "t_order_item_1")) .tableShardingStrategy(new TableShardingStrategy("order_id", new ModuloTableShardingAlgorithm())) .dataSourceRule(dataSourceRule) .build(); //綁定表策略,在查詢時(shí)會(huì)使用主表策略計(jì)算路由的數(shù)據(jù)源,因此需要約定綁定表策略的表的規(guī)則需要一致,可以一定程度提高效率 List<BindingTableRule> bindingTableRules = new ArrayList<BindingTableRule>(); bindingTableRules.add(new BindingTableRule(Arrays.asList(orderTableRule, orderItemTableRule))); return ShardingRule.builder() .dataSourceRule(dataSourceRule) .tableRules(Arrays.asList(orderTableRule, orderItemTableRule)) .bindingTableRules(bindingTableRules) .databaseShardingStrategy(new DatabaseShardingStrategy("user_id", new ModuloDatabaseShardingAlgorithm())) .tableShardingStrategy(new TableShardingStrategy("order_id", new ModuloTableShardingAlgorithm())) .build();}
創(chuàng)建sharding-jdbc的數(shù)據(jù)源DataSource,MybatisAutoConfiguration會(huì)使用此數(shù)據(jù)源
@Bean("dataSource")public DataSource shardingDataSource(ShardingRule shardingRule){ return ShardingDataSourceFactory.createDataSource(shardingRule);}
需要手動(dòng)配置事務(wù)管理器(原因未知)
//需要手動(dòng)聲明配置事務(wù)@Beanpublic DataSourceTransactionManager transactitonManager(@Qualifier("dataSource") DataSource dataSource){ return new DataSourceTransactionManager(dataSource);}
分庫(kù)策略的簡(jiǎn)單實(shí)現(xiàn),接口:DatabaseShardingAlgorithm
import java.util.Collection;import java.util.LinkedHashSet;import com.dangdang.ddframe.rdb.sharding.api.ShardingValue;import com.dangdang.ddframe.rdb.sharding.api.strategy.database.SingleKeyDatabaseShardingAlgorithm;import com.google.common.collect.Range;/** * Created by fuwei.deng on 2017年5月11日. */public class ModuloDatabaseShardingAlgorithm implements SingleKeyDatabaseShardingAlgorithm<Long> { @Override public String doEqualSharding(Collection<String> databaseNames, ShardingValue<Long> shardingValue) { for (String each : databaseNames) { if (each.endsWith(shardingValue.getValue() % 2 + "")) { return each; } } throw new IllegalArgumentException(); } @Override public Collection<String> doInSharding(Collection<String> databaseNames, ShardingValue<Long> shardingValue) { Collection<String> result = new LinkedHashSet<>(databaseNames.size()); for (Long value : shardingValue.getValues()) { for (String tableName : databaseNames) { if (tableName.endsWith(value % 2 + "")) { result.add(tableName); } } } return result; } @Override public Collection<String> doBetweenSharding(Collection<String> databaseNames, ShardingValue<Long> shardingValue) { Collection<String> result = new LinkedHashSet<>(databaseNames.size()); Range<Long> range = (Range<Long>) shardingValue.getValueRange(); for (Long i = range.lowerEndpoint(); i <= range.upperEndpoint(); i++) { for (String each : databaseNames) { if (each.endsWith(i % 2 + "")) { result.add(each); } } } return result; }}
分表策略的基本實(shí)現(xiàn),接口:TableShardingAlgorithm
import java.util.Collection;import java.util.LinkedHashSet;import com.dangdang.ddframe.rdb.sharding.api.ShardingValue;import com.dangdang.ddframe.rdb.sharding.api.strategy.table.SingleKeyTableShardingAlgorithm;import com.google.common.collect.Range;/** * Created by fuwei.deng on 2017年5月11日. */public class ModuloTableShardingAlgorithm implements SingleKeyTableShardingAlgorithm<Long> { @Override public String doEqualSharding(Collection<String> tableNames, ShardingValue<Long> shardingValue) { for (String each : tableNames) { if (each.endsWith(shardingValue.getValue() % 2 + "")) { return each; } } throw new IllegalArgumentException(); } @Override public Collection<String> doInSharding(Collection<String> tableNames, ShardingValue<Long> shardingValue) { Collection<String> result = new LinkedHashSet<>(tableNames.size()); for (Long value : shardingValue.getValues()) { for (String tableName : tableNames) { if (tableName.endsWith(value % 2 + "")) { result.add(tableName); } } } return result; } @Override public Collection<String> doBetweenSharding(Collection<String> tableNames, ShardingValue<Long> shardingValue) { Collection<String> result = new LinkedHashSet<>(tableNames.size()); Range<Long> range = (Range<Long>) shardingValue.getValueRange(); for (Long i = range.lowerEndpoint(); i <= range.upperEndpoint(); i++) { for (String each : tableNames) { if (each.endsWith(i % 2 + "")) { result.add(each); } } } return result; }}
至此,分庫(kù)分表的功能已經(jīng)實(shí)現(xiàn)
讀寫分離
讀寫分離需在創(chuàng)建DataSourceRule之前加一層主從數(shù)據(jù)源的創(chuàng)建
// 構(gòu)建讀寫分離數(shù)據(jù)源, 讀寫分離數(shù)據(jù)源實(shí)現(xiàn)了DataSource接口, 可直接當(dāng)做數(shù)據(jù)源處理. // masterDataSource0, slaveDataSource00, slaveDataSource01等為使用DBCP等連接池配置的真實(shí)數(shù)據(jù)源DataSource masterSlaveDs0 = MasterSlaveDataSourceFactory.createDataSource("ms_0", masterDataSource0, slaveDataSource00, slaveDataSource01);DataSource masterSlaveDs1 = MasterSlaveDataSourceFactory.createDataSource("ms_1", masterDataSource1, slaveDataSource11, slaveDataSource11);// 構(gòu)建分庫(kù)分表數(shù)據(jù)源Map<String, DataSource> dataSourceMap = new HashMap<>(2);dataSourceMap.put("ms_0", masterSlaveDs0);dataSourceMap.put("ms_1", masterSlaveDs1);// 通過ShardingDataSourceFactory繼續(xù)創(chuàng)建ShardingDataSource
強(qiáng)制使用主庫(kù)時(shí)
HintManager hintManager = HintManager.getInstance();hintManager.setMasterRouteOnly();// 繼續(xù)JDBC操作
強(qiáng)制路由
HintManager hintManager = HintManager.getInstance();hintManager.addDatabaseShardingValue("t_order", "user_id", 1L);hintManager.addTableShardingValue("t_order", "order_id", order.getOrderId());hintManager.addDatabaseShardingValue("t_order_item", "user_id", 1L);hintManager.addTableShardingValue("t_order_item", "order_id", order.getOrderId());
事務(wù)
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