2. sharding-jdbc源码之Configuration
阿飞Javaer，转载请注明原创出处，谢谢！
上篇文章sharding-jdbc源码之数据源介绍了通过Java硬编码创建ShardingDataSource。这篇文章通过分析sharding-jdbc-config-parent模块，学习如何通过YAML配置或者spring配置创建ShardingDataSource；sharding-jdbc-config-parent模块包含了三个子模块，关系如下图所示：
sharding-jdbc-config-parent
|__sharding-jdbc-config-common
|__sharding-jdbc-config-spring
|__sharding-jdbc-config-yaml
无论是yaml方式还是spring方式配置ShardingDataSource，最终都会转化为sharding-jdbc-config-common中定义的对象；接下来对两种方式进行源码分析：
YAML配置
可以通过
sharding-jdbc-example-config-yaml模块中YamlWithAssignedDataSourceMain.java进行debug；通过YamlWithAssignedDataSourceMain.java源码可知，yaml方式配置数据库的核心源码在YamlShardingDataSource中；
public final class YamlWithAssignedDataSourceMain {
public static void main(final String[] args) throws Exception {
YamlShardingDataSource dataSource = new YamlShardingDataSource(
new File(YamlWithAssignedDataSourceMain.class.getResource("/META-INF/withAssignedDataSource.yaml").getFile()));
... ...
}
}
说明：withAssignedDataSource.yaml的内容请自行查看源码；
com.dangdang.ddframe.rdb.sharding.config.yaml.api.YamlShardingDataSource.java位于sharding-jdbc-config-yaml模块中，核心源码如下：
public class YamlShardingDataSource extends ShardingDataSource {
// 通过yaml文件配置数据源的方式
public YamlShardingDataSource(final File yamlFile) throws IOException, SQLException {
// unmarshal(yamlFile)方法是解析yaml文件的核心源码，其作用是将yaml文件解释为YamlConfig（父类是ShardingRuleConfig）
super(new ShardingRuleBuilder(yamlFile.getName(), unmarshal(yamlFile)).build(), unmarshal(yamlFile).getProps());
}
... ...
private static YamlConfig unmarshal(final File yamlFile) throws IOException {
try (
FileInputStream fileInputStream = new FileInputStream(yamlFile);
InputStreamReader inputStreamReader = new InputStreamReader(fileInputStream, "UTF-8")
) {
// yaml解释依赖第三方组件：org.yaml.snakeyaml; config-all.yaml内容解释成ShardingRuleConfig
return new Yaml(new Constructor(YamlConfig.class)).loadAs(inputStreamReader, YamlConfig.class);
}
}
private static YamlConfig unmarshal(final byte[] yamlByteArray) throws IOException {
return new Yaml(new Constructor(YamlConfig.class)).loadAs(new ByteArrayInputStream(yamlByteArray), YamlConfig.class);
}
}
通过这段源码可知，接下来就会调用ShardingDataSource的构造方法，因为YamlShardingDataSource构造方法中调用了super()，而且YamlShardingDataSource继承自ShardingDataSource；
spring配置
可以通过
sharding-jdbc-example-config-spring模块中SpringNamespaceWithAssignedDataSourceMain.java进行debug；其源码就是加载applicationContextWithAssignedDataSource.xml文件，该文件中<rdb>节点即sharding-jdbc定义节点部分的内容如下：
<rdb:strategy id="databaseStrategy" sharding-columns="user_id" algorithm-expression="dbtbl_${user_id.longValue() % 2}"/>
<rdb:strategy id="orderTableStrategy" sharding-columns="order_id" algorithm-expression="t_order_${order_id.longValue() % 4}"/>
<rdb:strategy id="orderItemTableStrategy" sharding-columns="order_id" algorithm-class="com.dangdang.ddframe.rdb.sharding.example.config.spring.algorithm.SingleKeyModuloTableShardingAlgorithm"/>
<rdb:data-source id="shardingDataSource">
<rdb:sharding-rule data-sources="dbtbl_0,dbtbl_1,dbtbl_config">
<rdb:table-rules>
<rdb:table-rule logic-table="t_config" actual-tables="dbtbl_config.t_config"/>
<rdb:table-rule logic-table="t_order" actual-tables="dbtbl_${0..1}.t_order_${0..3}"
database-strategy="databaseStrategy" table-strategy="orderTableStrategy"/>
<rdb:table-rule logic-table="t_order_item" actual-tables="
dbtbl_${0..1}.t_order_item_0,
dbtbl_${0..1}.t_order_item_1,
dbtbl_${0..1}.t_order_item_2,
dbtbl_${0..1}.t_order_item_3"
database-strategy="databaseStrategy" table-strategy="orderItemTableStrategy"/>
</rdb:table-rules>
<rdb:default-database-strategy sharding-columns="none" algorithm-class="com.dangdang.ddframe.rdb.sharding.api.strategy.database.NoneDatabaseShardingAlgorithm"/>
<rdb:default-table-strategy sharding-columns="none" algorithm-class="com.dangdang.ddframe.rdb.sharding.api.strategy.table.NoneTableShardingAlgorithm"/>
</rdb:sharding-rule>
</rdb:data-source>
配置文件基于inline表达式，部分内容解读如下：
- 逻辑表表名为t_order，其实际表是
dbtbl_{0..1}.t_order_{0..3}；- t_order表的分表策略，通过table-strategy指定，即orderTableStrategy–根据order_id列的值对4取模；
- t_order_item分表策略，通过table-strategy指定，即orderItemTableStrategy–实现算法就是根据根据order_id列对4取模；具体实现请参考SingleKeyModuloTableShardingAlgorithm；
- 数据库的分库策略，通过database-strategy指定，即databaseStrategy–根据user_id列的值对2取模；
- 默认数据库和表的分库分表策略：不需要根据任何列水平切分（sharding-columns="none"）；
通过sharding-jdbc-config-spring模块中spring.handlers里的配置http\://www.dangdang.com/schema/ddframe/rdb=com.dangdang.ddframe.rdb.sharding.spring.namespace.handler.ShardingJdbcNamespaceHandler
可知，spring.xml中的<rdb>节点由ShardingJdbcNamespaceHandler进行解析，核心源码如下：
public final class ShardingJdbcNamespaceHandler extends NamespaceHandlerSupport {
@Override
public void init() {
// 注册<rdb:strategy>节点的解析器为ShardingJdbcStrategyBeanDefinitionParser
registerBeanDefinitionParser("strategy", new ShardingJdbcStrategyBeanDefinitionParser());
// 注册<rdb:data-source>节点的解析器为ShardingJdbcDataSourceBeanDefinitionParser
registerBeanDefinitionParser("data-source", new ShardingJdbcDataSourceBeanDefinitionParser());
// 注册<rdb:master-slave-data-source>节点的解析器为MasterSlaveDataSourceBeanDefinitionParser
registerBeanDefinitionParser("master-slave-data-source", new MasterSlaveDataSourceBeanDefinitionParser());
}
}
spring.xml中data-source节点剖析：
根据上面ShardingJdbcNamespaceHandler里的源码可知，<rdb:data-source>节点由ShardingJdbcDataSourceBeanDefinitionParser解析，核心源码如下；
// 自定义Parser一定要实现org.springframework.beans.factory.xml.AbstractBeanDefinitionParser才能作为spring.xml中节点中的解析器，这是spring的约定；
public class ShardingJdbcDataSourceBeanDefinitionParser extends AbstractBeanDefinitionParser {
@Override
// 这是解析入口，这时element是spring.xml中`<rdb:data-source>`节点；
protected AbstractBeanDefinition parseInternal(final Element element, final ParserContext parserContext) {
// 准备把`<rdb:data-source>`节点中数据解析成为SpringShardingDataSource
BeanDefinitionBuilder factory = BeanDefinitionBuilder.rootBeanDefinition(SpringShardingDataSource.class);
// 解析成SpringShardingDataSource且增加两个构造方法中属性的值（由后面SpringShardingDataSource.java定义可知，构造方法需要两个参数：一个是ShardingRuleConfig类型，一个是Properties类型）
factory.addConstructorArgValue(parseShardingRuleConfig(element, parserContext));
factory.addConstructorArgValue(parseProperties(element, parserContext));
factory.setDestroyMethodName("close");
return factory.getBeanDefinition();
}
// 这是解析SpringShardingDataSource构造方法中ShardingRuleConfig类型参数的值
private BeanDefinition parseShardingRuleConfig(final Element element, final ParserContext parserContext) {
// 先获取<rdb:sharding-rule>节点
Element shardingRuleElement = DomUtils.getChildElementByTagName(element, ShardingJdbcDataSourceBeanDefinitionParserTag.SHARDING_RULE_CONFIG_TAG);
// 将这个节点内容解析成ShardingRuleConfig（参数后面的ShardingRuleConfig.java定义）
BeanDefinitionBuilder factory = BeanDefinitionBuilder.rootBeanDefinition(ShardingRuleConfig.class);
// ShardingRuleConfig中dataSource属性赋值
factory.addPropertyValue("dataSource", parseDataSources(shardingRuleElement, parserContext));
// ShardingRuleConfig中defaultDataSourceName属性赋值
parseDefaultDataSource(factory, shardingRuleElement);
// ShardingRuleConfig中tables属性赋值
factory.addPropertyValue("tables", parseTableRulesConfig(shardingRuleElement));
// ShardingRuleConfig中bindingTables属性赋值
factory.addPropertyValue("bindingTables", parseBindingTablesConfig(shardingRuleElement));
// ShardingRuleConfig中defaultDatabaseStrategy属性赋值
factory.addPropertyValue("defaultDatabaseStrategy", parseDefaultDatabaseStrategyConfig(shardingRuleElement));
// ShardingRuleConfig中defaultTableStrategy属性赋值
factory.addPropertyValue("defaultTableStrategy", parseDefaultTableStrategyConfig(shardingRuleElement));
// ShardingRuleConfig中keyGeneratorClass属性赋值
parseKeyGenerator(factory, shardingRuleElement);
return factory.getBeanDefinition();
}
SpringShardingDataSource.java定义：
public class SpringShardingDataSource extends ShardingDataSource {
// parseInternal()中解析完spring.xml中的<rdb:data-source>节点后，调用这个构造方法
public SpringShardingDataSource(final ShardingRuleConfig shardingRuleConfig, final Properties props) throws SQLException {
super(new ShardingRuleBuilder(shardingRuleConfig).build(), props);
}
}
ShardingDataSource剖析
无论是yaml配置还是spring.xml配置，最终都会调用ShardingDataSource里的构造方法，接下来对其进行分析；
public class ShardingDataSource extends AbstractDataSourceAdapter implements AutoCloseable {
public ShardingDataSource(final ShardingRule shardingRule, final Properties props) throws SQLException {
super(shardingRule.getDataSourceRule().getDataSources());
shardingProperties = new ShardingProperties(null == props ? new Properties() : props);
// 默认值是CPU核心数
int executorSize = shardingProperties.getValue(ShardingPropertiesConstant.EXECUTOR_SIZE);
// ExecutorEngine的构造依赖于google-guava的MoreExecutors
executorEngine = new ExecutorEngine(executorSize);
// 是否有配置文件配置了sql_show
boolean showSQL = shardingProperties.getValue(ShardingPropertiesConstant.SQL_SHOW);
shardingContext = new ShardingContext(shardingRule, getDatabaseType(), executorEngine, showSQL);
}
...
}
通过该构造方法的源码可知： 申明的数据源集合，例如spring.xml中
<rdb:sharding-rule data-sources="dbtbl_0,dbtbl_1,dbtbl_config">，所有数据源必须是相同的数据库类型；要么全是MySQL，要么全是Oracle；否则抛出异常：Database type inconsistent with ‘%s’ and ‘%s’；其数据库类型根据connection.getMetaData().getDatabaseProductName()得到；
另外，通过这段源码可知，可配置的属性有sql_show和executor.size，定义在ShardingPropertiesConstant.java中：
- 两个属性在spring.xml中的配置参考：
<rdb:data-source id="shardingDataSource">
<rdb:sharding-rule data-sources="dbtbl_0,dbtbl_1,dbtbl_config">
... ...
</rdb:sharding-rule>
<rdb:props>
<prop key="sql.show">true</prop>
<prop key="executor.size">2</prop>
</rdb:props>
</rdb:data-source>
- 两个属性在yaml文件中的配置参考：
props:
sql.show: false
executor.size: 4
附ShardingRuleConfig.java定义：
@Getter
@Setter
public class ShardingRuleConfig {
private Map<String, DataSource> dataSource = new HashMap<>();
private String defaultDataSourceName;
private Map<String, TableRuleConfig> tables = new HashMap<>();
private List<BindingTableRuleConfig> bindingTables = new ArrayList<>();
private StrategyConfig defaultDatabaseStrategy;
private StrategyConfig defaultTableStrategy;
private String keyGeneratorClass;
}
Debug
以spring配置数据源的方式进行debug，Main方法为SpringNamespaceWithAssignedDataSourceMain.java，debug之前，需要执行sharding-jdbc-example-config-spring模块中的all_schema.sql脚本；
YAML解析&lombok实战
通过上面对sharding-jdbc源码的分析，发现sharding-jdbc支持yaml格式配置，且大量使用lombok简化源码，接下来简单实践yaml格式文件如何解析，以及lombok如何使用；
假设需要解析的yaml文件内容如下：
rdb:
oracle:
username: OracleUse&1
password: OrcUse*&1
driverClassName: oracle.jdbc.OracleDriver
url: jdbc:oracle:thin:@192.168.0.2:1521:xe
mysql:
username: MySQLUse&1
password: MyUse*&1
driverClassName: com.mysql.jdbc.Driver
url: jdbc:mysql://192.168.0.1:3306/financials_rules?autoCommit=true
nosql:
mongodb:
username: MongoUse&1
password: MgoUse*&1
redis:
password: RdsUse*&1
newsql:
解析yaml文件的核心代码如下：
public class DataSourceTest {
/**
* 这个yaml文件要放在resources目录下
*/
private static final String YAML_FILE_PATH = "datasource.yaml";
public static void main(String[] args) throws Exception {
System.out.println(JSON.toJSONString(
unmarshal(DataSourceTest.class.getClassLoader().getResourceAsStream(YAML_FILE_PATH))));
}
private static DataSourceConfig unmarshal(final InputStream is) throws IOException {
try (
InputStreamReader inputStreamReader = new InputStreamReader(is, "UTF-8")
) {
return new Yaml(new Constructor(DataSourceConfig.class)).loadAs(inputStreamReader, DataSourceConfig.class);
}
}
}
DataSourceConfig.java源码如下：
@Getter
@Setter
public class DataSourceConfig {
private Map<String, DataSourceItemConfig> rdb;
private Map<String, DataSourceItemConfig> nosql;
private Map<String, DataSourceItemConfig> newsql;
}
DataSourceItemConfig.java源码如下：
@Getter
@Setter
public class DataSourceItemConfig {
private String username;
private String password;
private String driverClassName;
private String url;
}
最终输出结果为：
{
"nosql": {
"mongodb": {
"password": "MgoUse*&1",
"username": "MongoUse&1"
},
"redis": {
"password": "RdsUse*&1"
}
},
"rdb": {
"oracle": {
"driverClassName": "oracle.jdbc.OracleDriver",
"password": "OrcUse*&1",
"url": "jdbc:oracle:thin:@192.168.0.2:1521:xe",
"username": "OracleUse&1"
},
"mysql": {
"driverClassName": "com.mysql.jdbc.Driver",
"password": "MyUse*&1",
"url": "jdbc:mysql://192.168.0.1:3306/financials_rules?autoCommit=true",
"username": "MySQLUse&1"
}
}
}
YAML&lombok Maven坐标
<dependency>
<groupId>org.yaml</groupId>
<artifactId>snakeyaml</artifactId>
<version>1.16</version>
</dependency>
<dependency>
<groupId>org.projectlombok</groupId>
<artifactId>lombok</artifactId>
<version>1.16.4</version>
<scope>provided</scope>
</dependency>
作者：阿飞的博客
来源：https://www.jianshu.com/p/57918e2df0d0
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