函数调用次数与性能

在查询语句中,如果 Select 子句调用了较为耗时的函数或子查询,需要特别考虑函数调用次数对于SQL整体执行时间的影响。

一、数据准备,SQL 语句

  • 模拟较耗时的用户函数

确保执行子查询的时长是1秒。

create or replace function f001()
returns int stable language sql
as
$$
select 1 from pg_sleep(1);
$$;
  • 模拟返回多行数据的子查询

结果集中,关联条件列含有重复值。

test=# create table t1 as select sn, id from (select generate_series(1, 3) sn),    (select generate_series(3, 8) id);
SELECT 18
test=# create table t2 as select generate_series(1, 5) id;
SELECT 5 test=# select * from t1;
sn | id
----+----
1 | 3
2 | 3
3 | 3
1 | 4
2 | 4
3 | 4
1 | 5
2 | 5
3 | 5
1 | 6
2 | 6
3 | 6
1 | 7
2 | 7
3 | 7
1 | 8
2 | 8
3 | 8
(18 rows) test=# select * from t2;
id
----
1
2
3
4
5
(5 rows)  

二、查询全体数据的优化方案

1、初始SQL

with a as (select sn, id  from t1 )
select a.*, (select id + f001() sq_sum from t2 b where b.id = a.id)
from a
where 1 = 1; sn | id | sq_sum
----+----+--------
1 | 3 | 4
2 | 3 | 4
3 | 3 | 4
1 | 4 | 5
2 | 4 | 5
3 | 4 | 5
1 | 5 | 6
2 | 5 | 6
3 | 5 | 6
1 | 6 |
2 | 6 |
3 | 6 |
1 | 7 |
2 | 7 |
3 | 7 |
1 | 8 |
2 | 8 |
3 | 8 | QUERY PLAN
-------------------------------------------------------------------------------------------------------------
Seq Scan on t1 (cost=0.00..101806.05 rows=2260 width=12) (actual time=1000.638..9008.584 rows=18 loops=1)
SubPlan 1
-> Seq Scan on t2 b (cost=0.00..45.03 rows=13 width=4) (actual time=500.465..500.468 rows=0 loops=18)
Filter: (id = t1.id)
Rows Removed by Filter: 4
Planning Time: 0.149 ms
Execution Time: 9008.667 ms
(7 rows)

对于t1 表的每条记录,都要访问一次t2 ,如果 t2 表有对应的满足条件的记录,就要调用一次函数。

2、CTE

使用临时表的结果进行连接,避免循环。注意,这里CTE 有materilaized 选项,主要是把耗时的部分先执行出结果,避免与其他部分查询合并,引发多次执行。

with a as (select sn, id  from t1),
b as materialized (select id, id + f001() sq_sum from t2 )
select a.*, (select sq_sum from b where b.id = a.id)
from a
where 1 = 1; QUERY PLAN
---------------------------------------------------------------------------------------------------------------
Seq Scan on t1 (cost=676.75..129868.35 rows=2260 width=12) (actual time=5004.377..5004.392 rows=18 loops=1)
CTE b
-> Seq Scan on t2 (cost=0.00..676.75 rows=2540 width=8) (actual time=1000.562..5004.348 rows=5 loops=1)
SubPlan 2
-> CTE Scan on b (cost=0.00..57.15 rows=13 width=4) (actual time=166.821..278.021 rows=0 loops=18)
Filter: (id = t1.id)
Rows Removed by Filter: 4
Planning Time: 0.107 ms
Execution Time: 5004.441 ms
(9 rows)

3、LEFT JOIN 子查询

与上例一样,还是利用materialize 特性,避免了函数的多次调用。

with a as (select sn, id from t1)
select a.*, b.sq_sum
from a left join (select id, id + f001() sq_sum from t2 ) b on b.id = a.id
where 1 = 1 ; QUERY PLAN
-------------------------------------------------------------------------------------------------------------------
Nested Loop Left Join (cost=0.00..86821.70 rows=28702 width=12) (actual time=3002.905..5005.627 rows=18 loops=1)
Join Filter: (t2.id = t1.id)
Rows Removed by Join Filter: 81
-> Seq Scan on t1 (cost=0.00..32.60 rows=2260 width=8) (actual time=0.007..0.011 rows=18 loops=1)
-> Materialize (cost=0.00..689.45 rows=2540 width=8) (actual time=55.621..278.088 rows=5 loops=18)
-> Seq Scan on t2 (cost=0.00..676.75 rows=2540 width=8) (actual time=1001.176..5005.568 rows=5 loops=1)
Planning Time: 0.180 ms
Execution Time: 5005.650 ms
(8 rows)

三、查询局部数据(过滤主表的条件)的优化方案

1、初始SQL

with a as (select sn, id from t1)
select a.*, (select id + f001() sq_sum from t2 b where b.id = a.id)
from a
where 1 = 1 and a.id = 3; sn | id | sq_sum
----+----+--------
1 | 3 | 4
2 | 3 | 4
3 | 3 | 4
(3 rows) QUERY PLAN
--------------------------------------------------------------------------------------------------------------
Seq Scan on t1 (cost=0.00..533.61 rows=11 width=12) (actual time=1000.356..3002.635 rows=3 loops=1)
Filter: (id = 3)
Rows Removed by Filter: 15
SubPlan 1
-> Seq Scan on t2 b (cost=0.00..45.03 rows=13 width=4) (actual time=1000.859..1000.866 rows=1 loops=3)
Filter: (id = t1.id)
Rows Removed by Filter: 4
Planning Time: 0.164 ms
Execution Time: 3002.657 ms
(9 rows)

2、CTE

with a as (select sn, id from t1),
b as materialized (select id, id + f001() sq_sum from t2)
select a.*, (select sq_sum from b where b.id = a.id) sq_sum
from a
where 1 = 1 and a.id=3 ; QUERY PLAN
---------------------------------------------------------------------------------------------------------------
Seq Scan on t1 (cost=676.75..1343.65 rows=11 width=12) (actual time=5004.958..5004.965 rows=3 loops=1)
Filter: (id = 3)
Rows Removed by Filter: 15
CTE b
-> Seq Scan on t2 (cost=0.00..676.75 rows=2540 width=8) (actual time=1001.387..5004.930 rows=5 loops=1)
SubPlan 2
-> CTE Scan on b (cost=0.00..57.15 rows=13 width=4) (actual time=1001.132..1668.316 rows=1 loops=3)
Filter: (id = t1.id)
Rows Removed by Filter: 4
Planning Time: 0.105 ms
Execution Time: 5004.983 ms
(11 rows)

3、LEFT JOIN 子查询

explain analyse
with a as (select sn, id from t1)
select a.*, b.sq_sum
from a left join (select id, id + f001() sq_sum from t2) b on b.id = a.id
where 1 = 1 and a.id = 3 ; QUERY PLAN
----------------------------------------------------------------------------------------------------------------
Nested Loop Left Join (cost=0.00..85.46 rows=143 width=12) (actual time=1000.972..1000.980 rows=3 loops=1)
Join Filter: (t2.id = t1.id)
-> Seq Scan on t1 (cost=0.00..38.25 rows=11 width=8) (actual time=0.008..0.009 rows=3 loops=1)
Filter: (id = 3)
Rows Removed by Filter: 15
-> Materialize (cost=0.00..45.10 rows=13 width=8) (actual time=333.654..333.656 rows=1 loops=3)
-> Seq Scan on t2 (cost=0.00..45.03 rows=13 width=8) (actual time=1000.959..1000.964 rows=1 loops=1)
Filter: (id = 3)
Rows Removed by Filter: 4
Planning Time: 0.107 ms
Execution Time: 1000.996 ms
(11 rows)

四、查询局部数据(过滤从表的条件)的优化方案

1、初始SQL

with a as (select sn, id from (select generate_series(1, 3) sn), (select generate_series(3, 8) id))
select a.*, (select id + f001() sq_sum from (select generate_series(1, 5) id) b where b.id = a.id) sq_sum
from a
where 1 = 1 and sq_sum = 6 ;

sn | id | sq_sum
----+----+--------
1 | 5 | 6
2 | 5 | 6
3 | 5 | 6
(3 行记录) 时间:6007.526 ms (00:06.008)
QUERY PLAN
----------------------------------------------------------------------------------------------------------------------------
Nested Loop (cost=0.00..3.43 rows=3 width=12) (actual time=4004.455..6006.681 rows=3 loops=1)
-> Subquery Scan on "SYSINTERNAL-4-1" (cost=0.00..2.27 rows=1 width=4) (actual time=3003.273..3003.289 rows=1 loops=1)
Filter: ((SubPlan 2) = 6)
Rows Removed by Filter: 5
-> ProjectSet (cost=0.00..0.05 rows=6 width=4) (actual time=0.001..0.005 rows=6 loops=1)
-> Result (cost=0.00..0.01 rows=1 width=0) (actual time=0.000..0.001 rows=1 loops=1)
SubPlan 2
-> Subquery Scan on b_1 (cost=0.00..0.36 rows=1 width=4) (actual time=500.541..500.544 rows=0 loops=6)
Filter: (b_1.id = "SYSINTERNAL-4-1".id)
Rows Removed by Filter: 4
-> ProjectSet (cost=0.00..0.04 rows=5 width=4) (actual time=0.001..0.003 rows=5 loops=6)
-> Result (cost=0.00..0.01 rows=1 width=0) (actual time=0.000..0.001 rows=1 loops=6)
-> ProjectSet (cost=0.00..0.03 rows=3 width=4) (actual time=0.002..0.006 rows=3 loops=1)
-> Result (cost=0.00..0.01 rows=1 width=0) (actual time=0.000..0.001 rows=1 loops=1)
SubPlan 1
-> Subquery Scan on b (cost=0.00..0.36 rows=1 width=4) (actual time=1001.116..1001.122 rows=1 loops=3)
Filter: (b.id = "SYSINTERNAL-4-1".id)
Rows Removed by Filter: 4
-> ProjectSet (cost=0.00..0.04 rows=5 width=4) (actual time=0.001..0.006 rows=5 loops=3)
-> Result (cost=0.00..0.01 rows=1 width=0) (actual time=0.000..0.001 rows=1 loops=3)
Planning Time: 0.121 ms
Execution Time: 6006.709 ms
(22 行记录) 时间:6007.303 ms (00:06.007)

2、CTE

explain analyse
with a as (select sn, id from (select generate_series(1, 3) sn), (select generate_series(3, 8) id)),
b as (select id, id + f001() sq_sum from generate_series(1, 5) id)
select a.*, (select sq_sum from b where b.id = a.id) sq_sum
from a
where 1 = 1 and sq_sum = 6 ; QUERY PLAN
-------------------------------------------------------------------------------------------------------------------------------
Nested Loop (cost=1.31..2.54 rows=3 width=12) (actual time=5005.414..5005.422 rows=3 loops=1)
CTE b
-> Function Scan on generate_series id (cost=0.00..1.31 rows=5 width=8) (actual time=1001.093..5005.376 rows=5 loops=1)
-> Subquery Scan on "SYSINTERNAL-4-1" (cost=0.00..0.80 rows=1 width=4) (actual time=5005.406..5005.410 rows=1 loops=1)
Filter: ((SubPlan 3) = 6)
Rows Removed by Filter: 5
-> ProjectSet (cost=0.00..0.05 rows=6 width=4) (actual time=0.002..0.005 rows=6 loops=1)
-> Result (cost=0.00..0.01 rows=1 width=0) (actual time=0.000..0.001 rows=1 loops=1)
SubPlan 3
-> CTE Scan on b b_1 (cost=0.00..0.11 rows=1 width=4) (actual time=500.540..834.232 rows=0 loops=6)
Filter: (id = "SYSINTERNAL-4-1".id)
Rows Removed by Filter: 4
-> ProjectSet (cost=0.00..0.03 rows=3 width=4) (actual time=0.002..0.003 rows=3 loops=1)
-> Result (cost=0.00..0.01 rows=1 width=0) (actual time=0.000..0.000 rows=1 loops=1)
SubPlan 2
-> CTE Scan on b (cost=0.00..0.11 rows=1 width=4) (actual time=0.001..0.001 rows=1 loops=3)
Filter: (id = "SYSINTERNAL-4-1".id)
Rows Removed by Filter: 4
Planning Time: 0.143 ms
Execution Time: 5005.449 ms
(20 行记录) 时间:5006.115 ms (00:05.006)

3、LEFT JOIN

explain analyse
with a as (select sn, id from (select generate_series(1, 3) sn), (select generate_series(3, 8) id))
select a.*, b.sq_sum
from a left join (select id, id + f001() sq_sum from generate_series(1, 5) id) b on b.id = a.id
where 1 = 1 and sq_sum = 6 ; QUERY PLAN
-----------------------------------------------------------------------------------------------------------------------------------------------
Nested Loop (cost=1.39..1.62 rows=3 width=12) (actual time=5005.285..5005.291 rows=3 loops=1)
-> Hash Join (cost=1.39..1.53 rows=1 width=8) (actual time=5005.281..5005.285 rows=1 loops=1)
Hash Cond: ((generate_series(3, 8)) = b.id)
-> ProjectSet (cost=0.00..0.05 rows=6 width=4) (actual time=0.002..0.005 rows=6 loops=1)
-> Result (cost=0.00..0.01 rows=1 width=0) (actual time=0.001..0.001 rows=1 loops=1)
-> Hash (cost=1.38..1.38 rows=1 width=8) (actual time=5005.270..5005.270 rows=1 loops=1)
Buckets: 1024 Batches: 1 Memory Usage: 9kB
-> Subquery Scan on b (cost=0.00..1.38 rows=1 width=8) (actual time=5005.264..5005.266 rows=1 loops=1)
Filter: (b.sq_sum = 6)
Rows Removed by Filter: 4
-> Function Scan on generate_series id (cost=0.00..1.31 rows=5 width=8) (actual time=1001.089..5005.254 rows=5 loops=1)
-> ProjectSet (cost=0.00..0.03 rows=3 width=4) (actual time=0.002..0.003 rows=3 loops=1)
-> Result (cost=0.00..0.01 rows=1 width=0) (actual time=0.000..0.001 rows=1 loops=1)
Planning Time: 0.113 ms
Execution Time: 5005.320 ms
(15 行记录) 时间:5005.873 ms (00:05.006)

4、LATERAL 连接 CTE

explain analyse
with a as (select sn, id from (select generate_series(1, 3) sn), (select generate_series(3, 8) id)),
b as (select id, id + f001() sq_sum from generate_series(1, 5) id)
select a.*, b.sq_sum
from a join lateral (select * from b where b.id = a.id ) b on true
where 1 = 1 and sq_sum = 6;
QUERY PLAN
-------------------------------------------------------------------------------------------------------------------------------
Nested Loop (cost=1.44..1.67 rows=3 width=12) (actual time=5005.492..5005.499 rows=3 loops=1)
CTE b
-> Function Scan on generate_series id (cost=0.00..1.31 rows=5 width=8) (actual time=1001.103..5005.440 rows=5 loops=1)
-> Hash Join (cost=0.12..0.27 rows=1 width=8) (actual time=5005.485..5005.489 rows=1 loops=1)
Hash Cond: ((generate_series(3, 8)) = b.id)
-> ProjectSet (cost=0.00..0.05 rows=6 width=4) (actual time=0.002..0.006 rows=6 loops=1)
-> Result (cost=0.00..0.01 rows=1 width=0) (actual time=0.000..0.001 rows=1 loops=1)
-> Hash (cost=0.11..0.11 rows=1 width=8) (actual time=5005.472..5005.472 rows=1 loops=1)
Buckets: 1024 Batches: 1 Memory Usage: 9kB
-> CTE Scan on b (cost=0.00..0.11 rows=1 width=8) (actual time=5005.457..5005.459 rows=1 loops=1)
Filter: (sq_sum = 6)
Rows Removed by Filter: 4
-> ProjectSet (cost=0.00..0.03 rows=3 width=4) (actual time=0.004..0.005 rows=3 loops=1)
-> Result (cost=0.00..0.01 rows=1 width=0) (actual time=0.001..0.001 rows=1 loops=1)
Planning Time: 0.205 ms
Execution Time: 5005.531 ms
(16 行记录) 时间:5006.765 ms (00:05.007)

5、LATERAL 连接子查询

explain analyse
with a as (select sn, id from (select generate_series(1, 3) sn), (select generate_series(3, 8) id))
select a.*, b.sq_sum
from a left join lateral (select id, id + f001() sq_sum from generate_series(1, 5) id where id = a.id ) b on true
where 1 = 1 and sq_sum = 6 ; QUERY PLAN
---------------------------------------------------------------------------------------------------------------------------------------
Nested Loop (cost=0.00..2.44 rows=18 width=12) (actual time=3003.267..3003.280 rows=3 loops=1)
-> Nested Loop (cost=0.00..2.15 rows=6 width=8) (actual time=3003.257..3003.268 rows=1 loops=1)
-> ProjectSet (cost=0.00..0.05 rows=6 width=4) (actual time=0.002..0.007 rows=6 loops=1)
-> Result (cost=0.00..0.01 rows=1 width=0) (actual time=0.000..0.002 rows=1 loops=1)
-> Subquery Scan on b (cost=0.00..0.33 rows=1 width=4) (actual time=500.541..500.542 rows=0 loops=6)
Filter: (b.sq_sum = 6)
Rows Removed by Filter: 0
-> Function Scan on generate_series id (cost=0.00..0.32 rows=1 width=8) (actual time=500.539..500.540 rows=0 loops=6)
Filter: (id = (generate_series(3, 8)))
Rows Removed by Filter: 4
-> Materialize (cost=0.00..0.08 rows=3 width=4) (actual time=0.007..0.009 rows=3 loops=1)
-> ProjectSet (cost=0.00..0.03 rows=3 width=4) (actual time=0.005..0.006 rows=3 loops=1)
-> Result (cost=0.00..0.01 rows=1 width=0) (actual time=0.001..0.002 rows=1 loops=1)
Planning Time: 0.125 ms
Execution Time: 3003.306 ms
(15 行记录) 时间:3003.950 ms (00:03.004)

总结

  • Select 子句中,表达式会逐行运算,总时长与结果集成正比。
  • CTE子句,先计算全部结果,然后关联主表,总时长是可控。
  • 使用子查询和 LATERAL 连接,可以避免结果集的重复计算。

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