ShardingJDBC5.x解决移除默认数据源问题

前言

ShardingSphere-JDBC 在5.x版本移除了默认数据源配置, 那在项目中大多不需要分片的表, 怎么办？看看官方怎么说

github上也有issues

看了半天，很遗憾, 没有看到满意的解决方案

如果在项目里分了多个库，不需要分片的表我就想指定用一个数据源，怎么破？

low点的解决方案1

每个表都配置一下默认actualDataNode

server:
  port: 8080
spring:
  application:
    name: sharding-jdbc
  autoconfigure:
    exclude: com.alibaba.druid.spring.boot.autoconfigure.DruidDataSourceAutoConfigure
  datasource:
    driver-class-name: com.mysql.cj.jdbc.Driver
    url: jdbc:mysql://localhost:3306/sharding-jdbc?serverTimezone=UTC&useSSL=false&useUnicode=true&characterEncoding=UTF-8
    username: root
    password: root
  main:
    allow-bean-definition-overriding: true
  jpa:
    show-sql: false
    hibernate:
      ddl-auto: none
  shardingsphere:
    mode:
      # 运行模式类型。可选配置：Memory(不需要下面repository持久化)、Standalone、Cluster
      type: Memory
    datasource:
      names: ds_1,ds_2
      ds_1:
        type: com.alibaba.druid.pool.DruidDataSource
        driver-class-name: com.mysql.cj.jdbc.Driver
        # 注意： 使用druid作为连接池，这里要改成 url
        url: jdbc:mysql://192.168.32.110:3306/sharding-jdbc?serverTimezone=UTC&useSSL=false&useUnicode=true&characterEncoding=UTF-8
        username: root
        password: root
      ds_2:
        type: com.alibaba.druid.pool.DruidDataSource
        driver-class-name: com.mysql.cj.jdbc.Driver
        url: jdbc:mysql://192.168.32.111:3306/sharding-jdbc?serverTimezone=UTC&useSSL=false&useUnicode=true&characterEncoding=UTF-8
        username: root
        password: root
    rules:
      sharding:
        tables:
          # 5.0之后移除了默认数据源，如果在这里不指定不分片表的话，会由sharding内部自己找数据源
          tbl_test1:
            actual-data-nodes: ds_2.tbl_test1
          tbl_test2:
            actual-data-nodes: ds_2.tbl_test2
    props:
      sql-show: true

我项目里有100张表，只有两张表需要分片, 其他的表要配置98次，是不是有点low？

low点的解决方案2

那是不是可以完全基于API的方式使用sharding
在构建Sharding的AlgorithmProvidedShardingRuleConfiguration#tables(Collection

#自定义配置
sharding:
  exclude:
    # 不需要分片的表
    tables: tbl_test1,tbl_test2
  # 默认的数据源
  default:
    data-source-name: ds_2

    @Value("${sharding.default.data-source-name}")
    private String shardingDefaultDataSourceName;

    @Value("${sharding.exclude.tables}")
    private String shardingExcludeTables;

     @Bean
     public RuleConfiguration ruleConfiguration(){
         AlgorithmProvidedShardingRuleConfiguration ruleConfiguration = new AlgorithmProvidedShardingRuleConfiguration();

         String[] tables = shardingExcludeTables.split(",");
         for (String table : tables) {
             ruleConfiguration.getTables().add(new ShardingTableRuleConfiguration(table, shardingDefaultDataSourceName + "." + table));
         }
         // .... 省略需要分片的表配置
         return ruleConfiguration;
     }

API的方式没有配置文件方式灵活，而且这样解决，正常的表还需把表名配置到配置文件中，还是有点low

探索解决之道

既然上面那么麻烦，那是不是可以让系统自己去识别系统有多少张表, 已经在sharding中配置了哪些表，他们的差集就是就是不需要分片的表，把这些表的规则添加到Sharding的rule中，再指定我们自己想指定的默认数据源
本质上还是如解决方案2一样，向rule中添加不需要分片的表的规则，指定actualDataNode, 区别是不用自己去配置表，由系统来完成

想法有了之后，开始落地
先理解一下内部机制，从看源码开始，毋庸置疑从自动配置类读起

@Configuration
@ComponentScan("org.apache.shardingsphere.spring.boot.converter")
@EnableConfigurationProperties(SpringBootPropertiesConfiguration.class)
@ConditionalOnProperty(prefix = "spring.shardingsphere", name = "enabled", havingValue = "true", matchIfMissing = true)
@AutoConfigureBefore(DataSourceAutoConfiguration.class)
@RequiredArgsConstructor
public class ShardingSphereAutoConfiguration implements EnvironmentAware {
    
    private String schemaName;
    
    private final SpringBootPropertiesConfiguration props;
    
    private final Map dataSourceMap = new LinkedHashMap<>();

    @Bean
    public ModeConfiguration modeConfiguration() {
        return null == props.getMode() ? null : new ModeConfigurationYamlSwapper().swapToObject(props.getMode());
    }
    

    @Bean
    @Conditional(LocalRulesCondition.class)
    @Autowired(required = false)
    public DataSource shardingSphereDataSource(final ObjectProvider> rules, final ObjectProvider modeConfig) throws SQLException {
        Collection ruleConfigs = Optional.ofNullable(rules.getIfAvailable()).orElse(Collections.emptyList());
        return ShardingSphereDataSourceFactory.createDataSource(schemaName, modeConfig.getIfAvailable(), dataSourceMap, ruleConfigs, props.getProps());
    }

    @Bean
    @ConditionalOnMissingBean(DataSource.class)
    public DataSource dataSource(final ModeConfiguration modeConfig) throws SQLException {
        return !dataSourceMap.isEmpty() ? ShardingSphereDataSourceFactory.createDataSource(schemaName, modeConfig, dataSourceMap, Collections.emptyList(), props.getProps())
                : ShardingSphereDataSourceFactory.createDataSource(schemaName, modeConfig);
    }
    
  
    @Bean
    public TransactionTypeScanner transactionTypeScanner() {
        return new TransactionTypeScanner();
    }
    
    @Override
    public final void setEnvironment(final Environment environment) {
        dataSourceMap.putAll(DataSourceMapSetter.getDataSourceMap(environment));
        schemaName = SchemaNameSetter.getSchemaName(environment);
    }
}

很显然，sharding需要代理数据源才能解析sql, 在通过分片规则重新拼接sql再转发。RuleConfiguration下与分片规则相关的是AlgorithmProvidedShardingRuleConfiguration，如下
而自定义的分片规则就是tables里, Collection 如下

看明白了，来实现! 先获取系统中所有的表，借助jpa entityManager，可以拿到所有entity, 从而获取到所有的表名, InitializingBean 就不用多讲了, 再对Sharding的RuleConfigration后置处理一下，把不需要分片的表添加到rule中

@Component
public class EntityBeanUtil implements InitializingBean {

    private static Map, SingleTableEntityPersister> map = new ConcurrentHashMap<>(16);
    @Autowired
    private EntityManager entityManager;

    @Override
    public void afterPropertiesSet() throws Exception {
        EntityManagerFactory entityManagerFactory = entityManager.getEntityManagerFactory();
        SessionFactoryImpl sessionFactory = (SessionFactoryImpl) entityManagerFactory.unwrap(SessionFactory.class);
        MetamodelImplementor metamodel = sessionFactory.getMetamodel();
        Map entityPersisterMap = metamodel.entityPersisters();

        Set> entries = entityPersisterMap.entrySet();

        for (Map.Entry entry : entries) {
            // 全限定类名
            String className = entry.getKey();
            SingleTableEntityPersister entityPersister = (SingleTableEntityPersister) entry.getValue();
            // 表名
            String tableName = entityPersister.getTableName();

            map.put(Class.forName(className), entityPersister);
        }
    }

    public static Map, SingleTableEntityPersister> getEntityMap() {
        return map;
    }

    public static Set getAllTableNames() {
        return map.values().stream().map(SingleTableEntityPersister::getTableName).collect(Collectors.toSet());
    }
}

public class ShardingPostProcess {

    private final String defaultDatasourceName;

    ShardingPostProcess(String defaultDatasourceName) {
        this.defaultDatasourceName = defaultDatasourceName;
    }

    
    public void postProcess(RuleConfiguration rules) {
        if (rules instanceof AlgorithmProvidedShardingRuleConfiguration) {

            Collection autoTables = Optional.ofNullable(((AlgorithmProvidedShardingRuleConfiguration) rules).getAutoTables()).orElse(new ArrayList<>(0));
            Collection broadcastTables = Optional.ofNullable(((AlgorithmProvidedShardingRuleConfiguration) rules).getBroadcastTables()).orElse(new ArrayList<>(0));
            Collection tables = Optional.ofNullable(((AlgorithmProvidedShardingRuleConfiguration) rules).getTables()).orElse(new ArrayList<>(0));

            // 已配置分片规则的表
            Set shardingTables = autoTables.stream().map(ShardingAutoTableRuleConfiguration::getLogicTable).collect(Collectors.toSet());
            shardingTables.addAll(new HashSet<>(broadcastTables));
            shardingTables.addAll(tables.stream().map(ShardingTableRuleConfiguration::getLogicTable).collect(Collectors.toSet()));

            // 系统所有实体表名
            Set allTables = EntityBeanUtil.getAllTableNames();

            // 取差集
            Collection differenceSet = CollectionUtil.subtract(allTables, shardingTables);
            if (CollectionUtil.isEmpty(differenceSet)) {
                return;
            }

            if (((AlgorithmProvidedShardingRuleConfiguration) rules).getTables() == null) {
                ((AlgorithmProvidedShardingRuleConfiguration) rules).setTables(new ArrayList<>(differenceSet.size()));
            }
            for (String tableName : differenceSet) {
                ShardingTableRuleConfiguration config =
                        new ShardingTableRuleConfiguration(tableName, defaultDatasourceName + "." + tableName);
                ((AlgorithmProvidedShardingRuleConfiguration) rules).getTables().add(config);
            }
        }
    }
}

接下来就是重头戏了！

sharding的自动配置类需要注入数据源，这些分片规则都是保存在它数据源里的！刚开始我还没意识到哪有问题，我禁了sharding的autoConfig类，自己弄了一个配置类，与它的内容一样，在构建数据源的时候，我在规则里添加那些不需要分片表的规则，与我配置的自定义数据库相绑定，然后规则放到数据源中。但是！但是！问题来了数据源都没创建，jpa EntityManager怎么能注入呢，它是要依赖数据源的！ , 在创建数据源的时候又想用jpa EntityManager，这就是个伪命题！

...... 此处省略尝试的配置

思考了很久，终于还是想到了解决思路

既然不能互相矛盾，那肯定是要先让数据源创建出来的，在sharding的自动配置完成了之后，它为我们做的是将它的数据源放到了ioc，这样在上层ORM框架执行sql，会被它的数据源解析，分片，发送。那么我是不是可以在整个ioc初始化完之前，在sharding-datasource的bean生成之后、在我自己定义的EntityBeanUtil创建完之后，重新生成一下sharding的datasource, 此时我已经能拿到所有的表了，之前的sharing分片规则我也能拿到，最后再替换掉ioc里的 ShardingDatasource，问题就迎刃而解了

实操

## 自定义配置默认数据源
sharding:
  default:
    datasource: ds_2

ShardingPostProcess 这个类注入到spring容器只是起到一个过桥的作用,仅仅是在他创建的方法里去实现我替换Sharding 数据源的操作

@Configuration
@ComponentScan("org.apache.shardingsphere.spring.boot.converter")
@EnableConfigurationProperties(SpringBootPropertiesConfiguration.class)
@AutoConfigureAfter(value = ShardingSphereAutoConfiguration.class)
@RequiredArgsConstructor
public class SharingConfig implements BeanFactoryAware, EnvironmentAware {

    @Value("${sharding.default.datasource}")
    private String defaultDatasourceName;

    private String schemaName;

    private final SpringBootPropertiesConfiguration props;

    private final Map dataSourceMap = new LinkedHashMap<>();

    private DefaultListableBeanFactory beanFactory;

    @Bean
    @DependsOn(value = "entityBeanUtil")
    public ShardingPostProcess shardingPostProcess(final ObjectProvider> rules, final ObjectProvider modeConfig) throws SQLException {
        ShardingPostProcess shardingPostProcess = new ShardingPostProcess(defaultDatasourceName);

        // 后置处理添加自定义的规则，再重新构建dataSource
        Collection ruleConfigs = Optional.ofNullable(rules.getIfAvailable()).orElse(Collections.emptyList());
        ruleConfigs.forEach(shardingPostProcess::postProcess);
        DataSource dataSource = ShardingSphereDataSourceFactory.createDataSource(schemaName, modeConfig.getIfAvailable(), dataSourceMap, ruleConfigs, props.getProps());
		
		// 覆盖掉dataSource
        beanFactory.destroySingleton("shardingSphereDataSource");
        beanFactory.registerSingleton("shardingSphereDataSource", dataSource);

        return shardingPostProcess;
    }


    
    @Override
    public void setEnvironment(Environment environment) {
        dataSourceMap.putAll(DataSourceMapSetter.getDataSourceMap(environment));
        schemaName = SchemaNameSetter.getSchemaName(environment);
    }

    @Override
    public void setBeanFactory(BeanFactory beanFactory) throws BeansException {
        this.beanFactory = (DefaultListableBeanFactory) beanFactory;
    }
}

结语

到此搞定, 改一下自定义默认的数据源名，就可以实现需求了
测试环节就省略了，有兴趣实现一下还是很有意思的
项目地址 gitee
有问题欢迎留言交流

ShardingJDBC5.x解决移除默认数据源问题

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