Sharding-JDBC的架构以及源码的示例分析

org.apache.shardingsphere.shardingjdbc.jdbc.core.statement.ShardingPreparedStatement.execute()

@Override
    public boolean execute() throws SQLException {
        try {
		//本地缓存清空
            clearPrevious();
		/**
		 * 路由
		 *
		 */
            shard();
		// 初始化 preparedStatement
            initPreparedStatementExecutor();
		// 执行sql
            return preparedStatementExecutor.execute();
        } finally {
            clearBatch();
        }
    }

org.apache.shardingsphere.core.BaseShardingEngine.shard(String, List<Object>)

 public SQLRouteResult shard(final String sql, final List<Object> parameters) {
        List<Object> clonedParameters = cloneParameters(parameters);
		// 根据SQL去路由
        SQLRouteResult result = executeRoute(sql, clonedParameters);
		// 改写sql
        result.getRouteUnits().addAll(HintManager.isDatabaseShardingOnly() ? convert(sql, clonedParameters, result) : rewriteAndConvert(sql, clonedParameters, result));
		// 打印路由后的sql
        if (shardingProperties.getValue(ShardingPropertiesConstant.SQL_SHOW)) {
            boolean showSimple = shardingProperties.getValue(ShardingPropertiesConstant.SQL_SIMPLE);
            SQLLogger.logSQL(sql, showSimple, result.getShardingStatement(), result.getRouteUnits());
        }
        return result;
    }

org.apache.shardingsphere.core.BaseShardingEngine.executeRoute(String, List<Object>)

 private SQLRouteResult executeRoute(final String sql, final List<Object> clonedParameters) {
        routingHook.start(sql);
        try {
            SQLRouteResult result = route(sql, clonedParameters);
            routingHook.finishSuccess(result, metaData.getTables());
            return result;
            // CHECKSTYLE:OFF
        } catch (final Exception ex) {
            // CHECKSTYLE:ON
            routingHook.finishFailure(ex);
            throw ex;
        }
    }

org.apache.shardingsphere.core.route.PreparedStatementRoutingEngine.route(List<Object>)

    public SQLRouteResult route(final List<Object> parameters) {
        if (null == sqlStatement) {
		// 解析SQL
            sqlStatement = shardingRouter.parse(logicSQL, true);
        }
		/**
		 * 第一步：根据上面异步解析出来的sqlStatement，结合配置的路由规则，找到对应的物理表表名
		 * 第二步：这里是主从（读写）路由，根据sql的类型（select、DML）决定走主库还是从库。
		 */
        return masterSlaveRouter.route(shardingRouter.route(logicSQL, parameters, sqlStatement));
    }

org.apache.shardingsphere.core.parse.SQLParseEngine.parse0(String, boolean)

private SQLStatement parse0(final String sql, final boolean useCache) {
        ……
		// 创建一个根据数据库匹配的解析引擎，解析sql。比如mysql的sql创建mysql的数据解析引擎。
        SQLStatement result = new SQLParseKernel(ParseRuleRegistry.getInstance(), databaseType, sql).parse();
        if (useCache) {
            cache.put(sql, result);
        }
        return result;
    }

org.apache.shardingsphere.core.parse.core.SQLParseKernel.parse()

    public SQLStatement parse() {
	// 解析sql
        SQLAST ast = parserEngine.parse();
	// 抽取sql 片段
        Collection<SQLSegment> sqlSegments = extractorEngine.extract(ast);
        Map<ParserRuleContext, Integer> parameterMarkerIndexes = ast.getParameterMarkerIndexes();
        return fillerEngine.fill(sqlSegments, parameterMarkerIndexes.size(), ast.getSqlStatementRule());
    }

org.apache.shardingsphere.core.route.router.sharding.ParsingSQLRouter.route(String, List<Object>, SQLStatement)

 public SQLRouteResult route(final String logicSQL, final List<Object> parameters, final SQLStatement sqlStatement) {
 	/**
	 * 根据sql类型，生成不同的优化引擎。比如我这里调试用的是select语句，生成就是ShardingSelectOptimizeEngine 实例。
	 * 对 语句进行优化
	 */
        ShardingOptimizedStatement shardingStatement = ShardingOptimizeEngineFactory.newInstance(sqlStatement).optimize(shardingRule, metaData.getTables(), logicSQL, parameters, sqlStatement);
		
        boolean needMergeShardingValues = isNeedMergeShardingValues(shardingStatement);
        if (shardingStatement instanceof ShardingConditionOptimizedStatement && needMergeShardingValues) {
            checkSubqueryShardingValues(shardingStatement, ((ShardingConditionOptimizedStatement) shardingStatement).getShardingConditions());
            mergeShardingConditions(((ShardingConditionOptimizedStatement) shardingStatement).getShardingConditions());
        }
		/**
		 *  这里获取一个路由引擎，这里有各种引擎，常见的有 StandardRoutingEngine、ComplexRoutingEngine
		 *  这次获取的就是 获取一个 StandardRoutingEngine 路由引擎。（shardingtable数目为1，或者所有的表都是有绑定关系的）
		 *  接着执行 StandardRoutingEngine.route方法
		 *
		 */
        RoutingResult routingResult = RoutingEngineFactory.newInstance(shardingRule, metaData.getDataSources(), shardingStatement).route();
        if (needMergeShardingValues) {
            Preconditions.checkState(1 == routingResult.getRoutingUnits().size(), "Must have one sharding with subquery.");
        }
		// 分布式主键插入
        if (shardingStatement instanceof ShardingInsertOptimizedStatement) {
            setGeneratedValues((ShardingInsertOptimizedStatement) shardingStatement);
        }
		// 加密
        EncryptOptimizedStatement encryptStatement = EncryptOptimizeEngineFactory.newInstance(sqlStatement)
                .optimize(shardingRule.getEncryptRule(), metaData.getTables(), logicSQL, parameters, sqlStatement);
        SQLRouteResult result = new SQLRouteResult(shardingStatement, encryptStatement);
        result.setRoutingResult(routingResult);
        return result;
    }

org.apache.shardingsphere.core.route.type.standard.StandardRoutingEngine.route()

public RoutingResult route() {
        if (isDMLForModify(optimizedStatement.getSQLStatement()) && !optimizedStatement.getTables().isSingleTable()) {
            throw new ShardingException("Cannot support Multiple-Table for '%s'.", optimizedStatement.getSQLStatement());
        }
		/**
		 * 1、根据逻辑表名去拿分表规则
		 * 2、根据分表规则 去拿DataNode（key 为 dataSourceName，value 为物理表表名）。
		 * 3、将上面的 dataNode 封装成 RoutingResult
		 */
        return generateRoutingResult(getDataNodes(shardingRule.getTableRule(logicTableName)));
    }