替代SQL count子查询

Question

我有以下查询:

SELECT DISTINCT 
    e.id, 
    folder, 
    subject, 
    in_reply_to, 
    message_id, 
    "references", 
    e.updated_at,
    (
        select count(*)  
        from emails  
        where 
        (
            select "references"[1] 
            from emails 
            where message_id = e.message_id
        ) = ANY ("references") 
        or message_id = 
        (
            select "references"[1] 
            from emails 
            where message_id = e.message_id
        )
    )
FROM "emails" e
INNER JOIN "email_participants" 
    ON ("email_participants"."email_id" = e."id") 
WHERE (("user_id" = 220) 
AND ("folder" = 'INBOX')) 
ORDER BY e."updated_at" DESC 
LIMIT 10 OFFSET 0;

这是上面查询的解释分析输出.

查询很好,直到我在下面添加了count子查询:

(
    select count(*)  
    from emails  
    where 
    (
        select "references"[1] 
        from emails 
        where message_id = e.message_id
    ) = ANY ("references") 
    or message_id = 
    (
        select "references"[1] 
        from emails 
        where message_id = e.message_id
    )
)

实际上我已经尝试过更简单的子查询,它似乎是花费时间的聚合函数本身.

那么我可以将count子查询附加到每个结果上吗？我应该在初始查询运行后更新结果吗？

这是一个将创建表的pastebin,并在最后运行性能不佳的查询以显示输出应该是什么.

Answer 1

扩展 Paul Guyot 的答案，您可以将子查询移动到派生表中，这应该执行得更快，因为它在一次扫描（加上联接）中获取消息计数，而不是每行 1 次扫描。

SELECT DISTINCT 
    e.id, 
    e.folder, 
    e.subject, 
    in_reply_to, 
    e.message_id, 
    e."references", 
    e.updated_at,
    t1.message_count
FROM "emails" e
INNER JOIN "email_participants" 
    ON ("email_participants"."email_id" = e."id") 
INNER JOIN (
    SELECT COUNT(e2.id) message_count, e.message_id
    FROM emails e
    LEFT JOIN emails e2 ON (ARRAY[e."references"[1]] <@ e2."references"
    OR e2.message_id = e."references"[1])
    GROUP BY e.message_id
) t1 ON t1.message_id = e.message_id
WHERE (("user_id" = 220) 
AND ("folder" = 'INBOX')) 
ORDER BY e."updated_at" DESC 
LIMIT 10 OFFSET 0;

使用pastebin数据进行小提琴 - http://www.sqlfiddle.com/#!15/c6298/7

下面是 postgres 为在相关子查询中获取计数与通过连接派生表获取计数而生成的查询计划。我使用了自己的一张表，但我认为结果应该是相似的。

相关子查询

"Limit  (cost=0.00..1123641.81 rows=1000 width=8) (actual time=11.237..5395.237 rows=1000 loops=1)"
"  ->  Seq Scan on visit v  (cost=0.00..44996236.24 rows=40045 width=8) (actual time=11.236..5395.014 rows=1000 loops=1)"
"        SubPlan 1"
"          ->  Aggregate  (cost=1123.61..1123.62 rows=1 width=0) (actual time=5.393..5.393 rows=1 loops=1000)"
"                ->  Seq Scan on visit v2  (cost=0.00..1073.56 rows=20018 width=0) (actual time=0.002..4.280 rows=21393 loops=1000)"
"                      Filter: (company_id = v.company_id)"
"                      Rows Removed by Filter: 18653"
"Total runtime: 5395.369 ms"

连接派生表

"Limit  (cost=1173.74..1211.81 rows=1000 width=12) (actual time=21.819..22.629 rows=1000 loops=1)"
"  ->  Hash Join  (cost=1173.74..2697.72 rows=40036 width=12) (actual time=21.817..22.465 rows=1000 loops=1)"
"        Hash Cond: (v.company_id = visit.company_id)"
"        ->  Seq Scan on visit v  (cost=0.00..973.45 rows=40045 width=8) (actual time=0.010..0.198 rows=1000 loops=1)"
"        ->  Hash  (cost=1173.71..1173.71 rows=2 width=12) (actual time=21.787..21.787 rows=2 loops=1)"
"              Buckets: 1024  Batches: 1  Memory Usage: 1kB"
"              ->  HashAggregate  (cost=1173.67..1173.69 rows=2 width=4) (actual time=21.783..21.784 rows=3 loops=1)"
"                    ->  Seq Scan on visit  (cost=0.00..973.45 rows=40045 width=4) (actual time=0.003..6.695 rows=40046 loops=1)"
"Total runtime: 22.806 ms"