ShardingSphere~9

内部执行-官网流程图：SQL 解析 => 执行器优化 => SQL 路由 => SQL 改写 => SQL 执行 => 结果归并

对应5.0代码包shardingsphere-infra-***

SQL解析：

分为词法解析和语法解析。 先通过词法解析器将 SQL 拆分为一个个不可再分的单词。再使用语法解析器对 SQL 进行理解，并最终提炼出解析上下文。 解析上下文包括表、选择项、排序项、分组项、聚合函数、分页信息、查询条件以及可能需要修改的占位符的标记。

shardingsphere-sql-parser-*

shardingsphere-sql-parser-engine

依赖外部的部分，一个是shardingsphere-infra-optimize依赖于calciteSQL解析优化，另一个是ANTLR支持更丰富语法模板

SQL路由

分片路由：直接路由（hint）、标准路由(一般带key的或绑定的join)、笛卡尔路由(非绑定关系join)

SQL路由处理实现如下

 调用关系如下

读写分离路由具体实现

public final class ReadwriteSplittingDataSourceRouter {
    private final ReadwriteSplittingDataSourceRule rule;
    public String route(final SQLStatement sqlStatement) {
        if (isPrimaryRoute(sqlStatement)) {
            PrimaryVisitedManager.setPrimaryVisited();
            String autoAwareDataSourceName = rule.getAutoAwareDataSourceName();
            if (Strings.isNullOrEmpty(autoAwareDataSourceName)) {
                return rule.getWriteDataSourceName();
            }
            Optional<DataSourceNameAware> dataSourceNameAware = DataSourceNameAwareFactory.getInstance().getDataSourceNameAware();
            if (dataSourceNameAware.isPresent()) {
                return dataSourceNameAware.get().getPrimaryDataSourceName(autoAwareDataSourceName);
            }
        }
        String autoAwareDataSourceName = rule.getAutoAwareDataSourceName();
        if (Strings.isNullOrEmpty(autoAwareDataSourceName)) {
            return rule.getLoadBalancer().getDataSource(rule.getName(), rule.getWriteDataSourceName(), rule.getReadDataSourceNames());
        }
        Optional<DataSourceNameAware> dataSourceNameAware = DataSourceNameAwareFactory.getInstance().getDataSourceNameAware();
        if (dataSourceNameAware.isPresent()) {
            Collection<String> replicaDataSourceNames = dataSourceNameAware.get().getReplicaDataSourceNames(autoAwareDataSourceName);
            return rule.getLoadBalancer().getDataSource(rule.getName(), rule.getWriteDataSourceName(), new ArrayList<>(replicaDataSourceNames));
        }
        return rule.getLoadBalancer().getDataSource(rule.getName(), rule.getWriteDataSourceName(), rule.getReadDataSourceNames());
    }
    
    private boolean isPrimaryRoute(final SQLStatement sqlStatement) {
        return containsLockSegment(sqlStatement) || !(sqlStatement instanceof SelectStatement)
                || PrimaryVisitedManager.getPrimaryVisited() || HintManager.isWriteRouteOnly() || TransactionHolder.isTransaction();
    }
    
    private boolean containsLockSegment(final SQLStatement sqlStatement) {
        return sqlStatement instanceof SelectStatement && SelectStatementHandler.getLockSegment((SelectStatement) sqlStatement).isPresent();
    }
}

负载均衡策略

SQL改写

 处理结果集

 ShardingResultMergerEngine

    @Override
    public ResultMerger newInstance(final DatabaseType databaseType, final ShardingRule shardingRule, final ConfigurationProperties props, final SQLStatementContext sqlStatementContext) {
        if (sqlStatementContext instanceof SelectStatementContext) {
            return new ShardingDQLResultMerger(databaseType);
        } 
        if (sqlStatementContext.getSqlStatement() instanceof DALStatement) {
            return new ShardingDALResultMerger(shardingRule);
        }
        return new TransparentResultMerger();
    }

合并部分例

    @Override
    public MergedResult merge(final List<QueryResult> queryResults, final SQLStatementContext<?> sqlStatementContext, final ShardingSphereSchema schema) throws SQLException {
        if (1 == queryResults.size()) {
            return new IteratorStreamMergedResult(queryResults);
        }
        Map<String, Integer> columnLabelIndexMap = getColumnLabelIndexMap(queryResults.get(0));
        SelectStatementContext selectStatementContext = (SelectStatementContext) sqlStatementContext;
        selectStatementContext.setIndexes(columnLabelIndexMap);
        MergedResult mergedResult = build(queryResults, selectStatementContext, columnLabelIndexMap, schema);
        return decorate(queryResults, selectStatementContext, mergedResult);
    }

调用关系

    private MergedResult build(final List<QueryResult> queryResults, final SelectStatementContext selectStatementContext,
                               final Map<String, Integer> columnLabelIndexMap, final ShardingSphereSchema schema) throws SQLException {
        if (isNeedProcessGroupBy(selectStatementContext)) {
            return getGroupByMergedResult(queryResults, selectStatementContext, columnLabelIndexMap, schema);
        }
        if (isNeedProcessDistinctRow(selectStatementContext)) {
            setGroupByForDistinctRow(selectStatementContext);
            return getGroupByMergedResult(queryResults, selectStatementContext, columnLabelIndexMap, schema);
        }
        if (isNeedProcessOrderBy(selectStatementContext)) {
            return new OrderByStreamMergedResult(queryResults, selectStatementContext, schema);
        }
        return new IteratorStreamMergedResult(queryResults);
    }

流式合并和内存合并

    private MergedResult getGroupByMergedResult(final List<QueryResult> queryResults, final SelectStatementContext selectStatementContext,
                                                final Map<String, Integer> columnLabelIndexMap, final ShardingSphereSchema schema) throws SQLException {
        return selectStatementContext.isSameGroupByAndOrderByItems()
                ? new GroupByStreamMergedResult(columnLabelIndexMap, queryResults, selectStatementContext, schema)
                : new GroupByMemoryMergedResult(queryResults, selectStatementContext, schema);
    }

关于合并，官网内容非常详细