数仓调优实践丨SQL改写消除相关子查询

本文分享自华为云社区《【调优实践】SQL改写消除相关子查询》，作者： 门前一棵葡萄树 。

一、子查询

GaussDB(DWS)根据子查询在SQL语句中的位置把子查询分成了子查询、子链接两种形式。

• 子查询SubQuery：对应于查询解析树中的范围表RangeTblEntry，更通俗一些指的是出现在FROM语句后面的独立的SELECT语句。
• 子链接SubLink：对应于查询解析树中的表达式，更通俗一些指的是出现在where/on子句、targetlist里面的语句。

1.1 非相关子查询

子查询的执行不依赖于外层父查询的任何属性值。这样子查询具有独立性，可独自求解，形成一个子查询计划先于外层的查询求解。示例：

select t1.c1,t1.c2 from t1 where t1.c1 in ( select c2 from t2 where t2.c2 IN (2,3,4) );

1.2 相关子查询

子查询的执行依赖于外层父查询的一些属性值（如下列示例t2.c1 = t1.c1条件中的t1.c1）作为内层查询的一个AND-ed条件。这样的子查询不具备独立性，需要和外层查询按分组进行求解。

select t1.c1,t1.c2 from t1 where t1.c1 in ( select c2 from t2 where t2.c1 = t1.c1 AND t2.c2 in (2,3,4) );

二、调优实战

2.1 案例：

UPDATE t1 SET (c1,c2)=( SELECT COALESCE(t2.c1, t1.c2),c2 FROM t2 WHERE t1.i1 = t2.i1 -- 相关标量子查询 );

其中子查询SELECT COALESCE(t2.c1, t1.c2),c2 FROM t2 WHERE t1.i1 = t2.i1 依赖于外层父查询的t1表，因此属于相关子查询。执行计划：

QUERY PLAN ---------------------------------------------------------------------------------------------------------------------------------------------------------------- id | operation | A-time | A-rows | E-rows | E-distinct | Peak Memory | E-memory | A-width | E-width | E-costs ----+-----------------------------------------------+----------------+--------+--------+------------+----------------+----------+---------+---------+--------- 1 | -> Streaming (type: GATHER) | 8.998 | 0 | 1 | | 24KB | | | 17 | 9.83 2 | -> Update on public.t1 | [0.086, 0.096] | 2 | 2 | | [308KB, 308KB] | | | 17 | 9.74 3 | -> Seq Scan on public.t1 | [0.058, 0.074] | 2 | 2 | | [32KB, 32KB] | 1MB | | 17 | 3.73 4 | -> Result [3, SubPlan 1] | [0.033, 0.034] | 2 | 10 | | [16KB, 16KB] | 1MB | | 6 | 1.36 5 | -> Materialize | [4.167, 4.458] | 20 | 10 | | [16KB, 16KB] | 16MB | [24,24] | 6 | 1.36 6 | -> Streaming(type: BROADCAST) | [4.105, 4.406] | 10 | 10 | | [48KB, 48KB] | 2MB | | 6 | 1.33 7 | -> Seq Scan on public.t2 | [0.013, 0.013] | 5 | 5 | | [32KB, 32KB] | 1MB | | 6 | 1.02 8 | -> Result [3, SubPlan 2] | [0.006, 0.021] | 2 | 10 | | [16KB, 16KB] | 1MB | | 6 | 1.36 9 | -> Materialize | [0.055, 0.061] | 20 | 10 | | [16KB, 16KB] | 16MB | [24,24] | 6 | 1.36 10 | -> Streaming(type: BROADCAST) | [0.034, 0.040] | 10 | 10 | | [48KB, 48KB] | 2MB | | 6 | 1.33 11 | -> Seq Scan on public.t2 | [0.005, 0.009] | 5 | 5 | | [32KB, 32KB] | 1MB | | 6 | 1.02

2.2 子查询消除

改写策略就是解除子查询与父查询依赖关系，改写方案参考：

UPDATE t1 SET (c1,c2)=(t3.c1,t3.c2) FROM ( SELECT t2.i1,COALESCE(t2.c1, t1.c2) c1,t2.c2 FROM t1,t2 WHERE t1.i1 = t2.i1 )t3 WHERE t1.i1 = t3.i1;

改写后，子查询独立，不再依赖父查询中元素。执行计划：

QUERY PLAN ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- id | operation | A-time | A-rows | E-rows | E-distinct | Peak Memory | E-memory | A-width | E-width | E-costs ----+-----------------------------------------------------+----------------+--------+--------+------------+----------------+----------+---------+---------+--------- 1 | -> Streaming (type: GATHER) | 13.141 | 0 | 1 | | 24KB | | | 33 | 10.56 2 | -> Update on public.t1 | [6.242, 6.362] | 2 | 2 | | [308KB, 308KB] | | | 33 | 10.47 3 | -> Streaming(type: RESTORE) | [6.186, 6.310] | 2 | 2 | | [48KB, 48KB] | 2MB | | 33 | 4.46 4 | -> Nested Loop (5,11) | [4.082, 4.801] | 2 | 2 | | [32KB, 32KB] | 1MB | | 33 | 4.44 5 | -> Streaming(type: BROADCAST) | [3.804, 4.541] | 4 | 4 | | [48KB, 48KB] | 2MB | | 27 | 2.36 6 | -> Nested Loop (7,8) | [2.972, 4.267] | 2 | 2 | | [32KB, 32KB] | 1MB | | 27 | 2.20 7 | -> Seq Scan on public.t1 | [0.010, 0.011] | 2 | 2 | | [16KB, 16KB] | 1MB | | 14 | 1.01 8 | -> Materialize | [2.724, 4.055] | 6 | 4 | | [16KB, 16KB] | 16MB | [28,28] | 13 | 1.17 9 | -> Streaming(type: BROADCAST) | [2.667, 4.008] | 4 | 4 | | [48KB, 48KB] | 2MB | | 13 | 1.17 10 | -> Seq Scan on public.t1 | [0.008, 0.012] | 2 | 2 | | [16KB, 16KB] | 1MB | | 13 | 1.01 11 | -> Materialize | [0.018, 0.022] | 12 | 5 | | [16KB, 16KB] | 16MB | [32,32] | 14 | 2.03 12 | -> Seq Scan on public.t2 | [0.007, 0.009] | 5 | 5 |

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