Postgresql 计划不周的查询运行时间过长

Question

我有一个复杂的查询，它在下面被大大简化，在“aarch64-unknown-linux-gnu 上的 PostgreSQL 11.9 上运行，由 aarch64-unknown-linux-gnu-gcc (GCC) 7.4.0, 64-bit 编译"，在 AWS Aurora Serverless 2xlarge 服务器（8 核，64GB RAM）上运行。

我有以下...

mv_journey，一个具有约 5.5 亿行的物化视图，其中包含有关具有起点和目的地的旅程的信息，以及有关这些信息的一些度量（旅程花费了多长时间等），用列定义 @ 987654321@ 和 from_region 标识起点，to_id 和 to_region 标识目的地。

place_from 和 place_to，在 CTE 的初始步骤中从函数 fn_location_get 计算得出，包含 id 和 region (分别映射到from_id、from_region 和to_id、to_region）。这些还包含来自该区域的汇总级别，例如country、continent。通常这些返回约 100 到 20,000 行。

稍后在 CTE 中，我使用 place_from 和 place_to 过滤 550M mv_journey 行，并使用 group by 创建基于旅程的汇总报告，例如从一个国家到另一个国家。

简化的查询是这样的。

WITH place_from AS (

  select * 
  from fn_location_get(...)

), place_to AS (

  select * 
  from fn_location_get(...)

)

select [many dimension columns...]
  , [a few aggregated measure columns]
from mv_journey j
  inner join place_from o on j.from_id = o.id
    and j.from_region = o.region
  inner join place_to d on j.from_id = d.id
    and j.from_region = d.region
where service_type_id = ?
group by [many dimension columns...]

我在 mv_journey 上有索引

CREATE INDEX idx_mv_journey_from ON mv_journey (from_id, from_region);
CREATE INDEX idx_mv_journey_to ON mv_journey (to_id, to_region);

当我运行查询（使用 SET LOCAL work_mem = '2048MB' 调用快速排序）时，place_from (92) 中有少量行，place_to (~18,000) 中有大量行，查询运行时间约为 25以下查询计划的秒数（其中包括 CTE 中生成 place_from 和 place_to 的步骤）。

"GroupAggregate  (cost=530108.64..530129.64 rows=30 width=686) (actual time=13097.187..25408.707 rows=92 loops=1)"
"  Group Key: [many dimension columns...]"
"  CTE place_from"
"    ->  Function Scan on fn_location_get (cost=0.25..10.25 rows=1000 width=396) (actual time=34.275..34.331 rows=92 loops=1)"
"  CTE place_to"
"    ->  Function Scan on fn_location_get (cost=0.25..10.25 rows=1000 width=396) (actual time=96.287..97.428 rows=18085 loops=1)"
"  ->  Sort  (cost=530088.14..530088.22 rows=30 width=622) (actual time=12935.329..13295.468 rows=1871349 loops=1)"
"        Sort Key: [many dimension columns...]"
"        Sort Method: quicksort  Memory: 826782kB"
"        ->  Merge Join  (cost=529643.68..530087.41 rows=30 width=622) (actual time=4708.780..6021.449 rows=1871349 loops=1)"
"              Merge Cond: ((j.to_id = d.id) AND (j.to_region = d.region))"
"              ->  Sort  (cost=529573.85..529719.16 rows=58124 width=340) (actual time=4583.265..4788.625 rows=1878801 loops=1)"
"                    Sort Key: j.to_id, j.to_region"
"                    Sort Method: quicksort  Memory: 623260kB"
"                    ->  Nested Loop  (cost=0.57..524974.25 rows=58124 width=340) (actual time=34.324..3079.815 rows=1878801 loops=1)"
"                          ->  CTE Scan on place_from o  (cost=0.00..20.00 rows=1000 width=320) (actual time=34.277..34.432 rows=92 loops=1)"
"                          ->  Index Scan using idx_mv_journey_from on mv_journey j (cost=0.57..524.37 rows=58 width=60) (actual time=0.018..30.022 rows=20422 loops=92)"
"                                Index Cond: ((from_id = o.id) AND (from_region = o.region))"
"                                Filter: (service_type_id = 'ALL'::text)"
"                                Rows Removed by Filter: 81687"
"              ->  Sort  (cost=69.83..72.33 rows=1000 width=320) (actual time=125.505..223.780 rows=1871350 loops=1)"
"                    Sort Key: d.id, d.region"
"                    Sort Method: quicksort  Memory: 3329kB"
"                    ->  CTE Scan on place_to d  (cost=0.00..20.00 rows=1000 width=320) (actual time=96.292..103.677 rows=18085 loops=1)"
"Planning Time: 0.546 ms"
"Execution Time: 25501.827 ms"

问题是，当我交换 from/to 中的位置时，即place_from (~18,000) 中的大量行和place_to (92) 中的少量行，查询将永远进行。顺便说一句，mv_journey 预计在两种情况下匹配的行数相同 - 一个方向的预期记录不会多于另一方向。

如果没有运行几个小时并且 PGAdmin 4 失去与服务器的连接，我还没有完成第二个查询。因此，我什至无法对其进行EXPLAIN ANALYZE。不过我有EXPLAIN:

"GroupAggregate  (cost=474135.40..474152.90 rows=25 width=686)"
"  Group Key: [many dimension columns...]"
"  CTE place_from"
"    ->  Function Scan on fn_location_get  (cost=0.25..10.25 rows=1000 width=396)"
"  CTE place_to"
"    ->  Function Scan on fn_location_get (cost=0.25..10.25 rows=1000 width=396)"
"  ->  Sort  (cost=474114.90..474114.96 rows=25 width=622)"
"        Sort Key: [many dimension columns...]"
"        ->  Merge Join  (cost=473720.23..474114.31 rows=25 width=622)"
"              Merge Cond: ((j.to_id = d.id) AND (j.to_region = d.region))## Heading ##"
"              ->  Sort  (cost=473650.40..473779.18 rows=51511 width=340)"
"                    Sort Key: j.to_id, j.to_region"
"                    ->  Nested Loop  (cost=0.57..469619.00 rows=51511 width=340)"
"                          ->  CTE Scan on place_from o  (cost=0.00..20.00 rows=1000 width=320)"
"                          ->  Index Scan using idx_mv_journey_from on mv_journey j   (cost=0.57..469.08 rows=52 width=60)"
"                                Index Cond: ((from_id = o.id) AND (from_region = o.region))"
"                                Filter: (service_type_id = 'ALL'::text)"
"              ->  Sort  (cost=69.83..72.33 rows=1000 width=320)"
"                    Sort Key: d.id, d.region"
"                    ->  CTE Scan on place_to d  (cost=0.00..20.00 rows=1000 width=320)"

我的假设是，如果我在 from/to 的两侧都有等效的索引，那么 Postgres 将使用镜像相反的查询计划，对源进行合并连接，并使用 idx_mv_journey_to 进行嵌套循环连接目的地。

但看起来查询规划器的行数估计值在两个查询中都存在偏差。尽管如此，第一个查询表现如此出色似乎只是运气。

我尝试了以下方法，但都没有成功

• 交换内部连接语句，使目标连接在前
• ALTER TABLE mv_journey ALTER COLUMN to_id SET STATISTICS 1000; ANALYZE mv_journey
• ALTER TABLE mv_journey ALTER COLUMN from_id SET STATISTICS 1000; ANALYZE mv_journey

我猜计划是在 CTE 执行开始之前完成的？这就是为什么它不知道创建place_from 和place_to 集的fn_location_get 调用会产生什么？

fn_location_get 是一个复杂的函数，它有自己的递归 CTE，我不想将它的逻辑从函数中引入到这个 CTE 中。

摆脱这种混乱的最好方法是什么？

Answer 1

最直接的方法是创建两个临时表作为函数调用的结果，手动分析它们，然后针对临时表而不是函数调用运行查询。

Answer 2

我在写这个问题时想出了一个答案......不要使用 CTE，而是使用临时表。

DROP TABLE IF EXISTS place_from;
CREATE TEMP TABLE place_from AS
select * 
from fn_location_get(...);

DROP TABLE IF EXISTS place_to;
CREATE TEMP TABLE place_to AS
select * 
from fn_location_get(...);

select [many dimension columns...]
  , [a few aggregated measure columns]
from mv_journey j
  inner join place_from o on j.from_id = o.id
    and j.from_region = o.region
  inner join place_to d on j.from_id = d.id
    and j.from_region = d.region
where service_type_id = ?
group by [many dimension columns...]

我认为这很有效，因为当报告 select 的查询计划完成时，临时表的行数是已知的，并且可以制定更好的查询计划。

但是，行数估计仍然不准确。足以选择正确的计划，但不准确。

"GroupAggregate  (cost=200682.98..200706.78 rows=34 width=686) (actual time=21233.486..33200.052 rows=92 loops=1)"
"  Group Key: [many dimension columns...]"
"  ->  Sort  (cost=200682.98..200683.07 rows=34 width=622) (actual time=21077.807..21443.739 rows=1802571 loops=1)"
"        Sort Key: [many dimension columns...]"
"        Sort Method: quicksort  Memory: 800480kB"
"        ->  Merge Join  (cost=200555.00..200682.12 rows=34 width=622) (actual time=4820.798..6106.722 rows=1802571 loops=1)"
"              Merge Cond: ((from_id = o.id) AND (from_region = o.region))"
"              ->  Sort  (cost=199652.79..199677.24 rows=9779 width=340) (actual time=4794.354..5003.954 rows=1810023 loops=1)"
"                    Sort Key: j.from_id, j.from_region"
"                    Sort Method: quicksort  Memory: 603741kB"
"                    ->  Nested Loop  (cost=0.57..199004.67 rows=9779 width=340) (actual time=0.044..3498.767 rows=1810023 loops=1)"
"                          ->  Seq Scan on place_to d  (cost=0.00..11.90 rows=190 width=320) (actual time=0.006..0.078 rows=92 loops=1)"
"                          ->  Index Scan using idx_mv_journey_to on mv_journey j  (cost=0.57..1046.82 rows=51 width=60) (actual time=0.020..35.055 rows=19674 loops=92)"
"                                Index Cond: ((j.to_id = d.id) AND (j.to_region = d.region))"
"                                Filter: (service_type_id = 'ALL'::text)"
"                                Rows Removed by Filter: 78697"
"              ->  Sort  (cost=902.20..920.02 rows=7125 width=320) (actual time=26.434..121.106 rows=1802572 loops=1)"
"                    Sort Key: o.id, o.region"
"                    Sort Method: quicksort  Memory: 3329kB"
"                    ->  Seq Scan on place_from o  (cost=0.00..446.25 rows=7125 width=320) (actual time=0.016..4.205 rows=18085 loops=1)"
"Planning Time: 0.792 ms"
"Execution Time: 33286.461 ms"

更新：按照 jjanes 的建议，在 CREATE 之后添加手动 ANALYZE 时，现在的估计值符合预期。