GaussDB(DWS)运维：导致SQL执行不下推的改写方案

摘要：本文就针对因USING子句的书写方式可能导致MERGE INTO语句的执行不下推的场景，对USING子句的SQL语句进行改写一遍，整个SQL语句可以下推。

本文分享自华为云社区《GaussDB(DWS)运维 -- values子句做MERGE数据源导致SQL执行不下推的改写方案》，作者： 譡里个檔。

现网做实时接入的时候，有的时候会使用MERGE INTO语句实现类似UPSERT的功能。这种场景下MERGE INTO语句的USING部分的数据位VALUES子句，为了后续的SQL语句中描述方便，需要对VALUES子句的输出命名别名。USING子句的书写方式可能导致MERGE INTO语句的执行不下推，本文就针对因此导致的不下推的场景，对USING子句的SQL语句进行改写一遍，整个SQL语句可以下推。

预置条件

CREATE TABLE t1(name text, id INT) DISTRIBUTE BY HASH(id);

原始语句

MERGE INTO t1 USING (
 SELECT *
 FROM (VALUES ('json', 1), ('sam', 2)) AS val(name, id)
) tmp ON (t1.id = tmp.id)
WHEN MATCHED THEN
 UPDATE SET t1.name = tmp.name
WHEN NOT MATCHED THEN
 INSERT (name, id) VALUES(tmp.name, tmp.id);

SQL语句不下推，导致执行低效

postgres=# EXPLAIN VERBOSE MERGE INTO t1 USING (
postgres(#     SELECT *
postgres(#     FROM (VALUES ('json', 1), ('sam', 2)) AS val(name, id)
postgres(# ) tmp ON (t1.id = tmp.id)
postgres-# WHEN MATCHED THEN
postgres-#     UPDATE SET t1.name = tmp.name
postgres-# WHEN NOT MATCHED THEN
postgres-#     INSERT (name, id) VALUES(tmp.name, tmp.id);
                                                                            QUERY PLAN
-------------------------------------------------------------------------------------------------------------------------------------------------------------------
  id |                       operation                       | E-rows | E-distinct | E-width | E-costs
 ----+-------------------------------------------------------+--------+------------+---------+---------
 1 | -> Merge on public.t1                                | 2 | | 54 | 0.08
 2 | ->  Nested Loop Left Join (3, 4)                   | 2 | | 54 | 0.08
 3 | -> Values Scan on "*VALUES*" | 2 | | 36 | 0.03
 4 | -> Data Node Scan on t1 "_REMOTE_TABLE_QUERY_" | 2 | | 18 | 0.00
 SQL Diagnostic Information
 ------------------------------------------------------------
 SQL is not plan-shipping
         reason: Type of Record in non-real table can not be shipped
   Predicate Information (identified by plan id)
 -------------------------------------------------
 1 --Merge on public.t1
         Node expr: : $10
 2 --Nested Loop Left Join (3, 4)
 Join Filter: (t1.id = "*VALUES*".column2)
 Targetlist Information (identified by plan id)
 -----------------------------------------------------------------------------------------------------------------------------------------------------------------
 1 --Merge on public.t1
         Node/s: All datanodes
         Remote query: UPDATE ONLY public.t1 SET name = $7, id = $8 WHERE t1.ctid = $5 AND t1.xc_node_id = $6
         Node/s: All datanodes
         Remote query: INSERT INTO public.t1 (name, id) VALUES ($9, $10)
 2 --Nested Loop Left Join (3, 4)
         Output: "*VALUES*".column1, "*VALUES*".column2, t1.name, t1.id, t1.ctid, t1.xc_node_id, "*VALUES*".column1, t1.id, "*VALUES*".column1, "*VALUES*".column2
 3 --Values Scan on "*VALUES*"
         Output: "*VALUES*".column1, "*VALUES*".column2
 4 --Data Node Scan on t1 "_REMOTE_TABLE_QUERY_"
         Output: t1.name, t1.id, t1.ctid, t1.xc_node_id
         Node/s: All datanodes
         Remote query: SELECT name, id, ctid, xc_node_id FROM ONLY public.t1 WHERE true
 ====== Query Summary =====
 --------------------------
 Parser runtime: 0.079 ms
 Planner runtime: 1.392 ms
 Unique SQL Id: 1657855173
(40 rows)

改写方案

MERGE INTO t1 USING (
 WITH val(name, id) AS(
 VALUES ('json', 1), ('sam', 2)
    )
 SELECT * FROM val
) tmp ON (t1.id = tmp.id)
WHEN MATCHED THEN
 UPDATE SET t1.name = tmp.name
WHEN NOT MATCHED THEN
 INSERT (name, id) VALUES(tmp.name, tmp.id);

改写后下推

postgres=# EXPLAIN VERBOSE MERGE INTO t1 USING (
postgres(#     WITH val(name, id) AS(
postgres(#         VALUES ('json', 1), ('sam', 2)
postgres(#     )
postgres(#     SELECT * FROM val
postgres(# ) tmp ON (t1.id = tmp.id)
postgres-# WHEN MATCHED THEN
postgres-#     UPDATE SET t1.name = tmp.name
postgres-# WHEN NOT MATCHED THEN
postgres-#     INSERT (name, id) VALUES(tmp.name, tmp.id);
                                                                      QUERY PLAN
------------------------------------------------------------------------------------------------------------------------------------------------------
  id |                  operation                   | E-rows | E-distinct | E-memory | E-width | E-costs
 ----+----------------------------------------------+--------+------------+----------+---------+---------
 1 | ->  Streaming (type: GATHER)                 | 1 | | | 54 | 1.56
 2 | -> Merge on public.t1                    | 2 | | | 54 | 1.15
 3 | ->  Streaming(type: REDISTRIBUTE)      | 2 | | 2MB      | 54 | 1.15
 4 | ->  Nested Loop Left Join (5, 7)    | 2 | | 1MB      | 54 | 1.11
 5 | ->  Subquery Scan on tmp | 2 | | 1MB      | 36 | 0.08
 6 | -> Values Scan on "*VALUES*" | 24 | | 1MB      | 36 | 0.03
 7 | ->  Seq Scan on public.t1        | 2 | | 1MB      | 18 | 1.01
 Predicate Information (identified by plan id)
 ---------------------------------------------
 4 --Nested Loop Left Join (5, 7)
 Join Filter: (t1.id = tmp.id)
 5 --Subquery Scan on tmp
         Filter: (Hash By tmp.id)
 Targetlist Information (identified by plan id)
 ----------------------------------------------------------------------------------------------------------------------------------------------------
 1 --Streaming (type: GATHER)
         Node/s: All datanodes
 3 --Streaming(type: REDISTRIBUTE)
         Output: tmp.name, tmp.id, t1.name, t1.id, t1.ctid, t1.xc_node_id, tmp.name, tmp.id, (CASE WHEN (t1.ctid IS NULL) THEN tmp.id ELSE t1.id END)
         Distribute Key: (CASE WHEN (t1.ctid IS NULL) THEN tmp.id ELSE t1.id END)
         Spawn on: All datanodes
         Consumer Nodes: All datanodes
 4 --Nested Loop Left Join (5, 7)
         Output: tmp.name, tmp.id, t1.name, t1.id, t1.ctid, t1.xc_node_id, tmp.name, tmp.id, CASE WHEN (t1.ctid IS NULL) THEN tmp.id ELSE t1.id END
 5 --Subquery Scan on tmp
         Output: tmp.name, tmp.id
 6 --Values Scan on "*VALUES*"
         Output: "*VALUES*".column1, "*VALUES*".column2
 7 --Seq Scan on public.t1
         Output: t1.name, t1.id, t1.ctid, t1.xc_node_id
         Distribute Key: t1.id
 ====== Query Summary =====
 -------------------------------
 System available mem: 3112960KB
 Query Max mem: 3112960KB
 Query estimated mem: 6336KB
 Parser runtime: 0.107 ms
 Planner runtime: 1.185 ms
 Unique SQL Id: 780461632
(44 rows)

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