我有两个表：campaign和stats。 stats表格包含我为每个广告系列汇总的每日统计信息，没什么特别的。
我索引了我能想到的所有字段，但是没有一个索引可以用来说明。我知道Postgres可能会选择不使用索引，但它仍然看起来很可疑，而且查询也不是很快。我该如何帮助它？
EXPLAIN ANALYZE SELECT "campaign"."id", "campaign"."name", "campaign"."status", SUM("stats"."impressions") AS "impressions"
FROM "campaign"
LEFT OUTER JOIN "stats" ON
("stats"."date" >= '2016-03-27'::date)
AND ("stats"."date" <= '2016-04-25'::date)
AND ("campaign"."id" = "stats"."campaign_id")
GROUP BY "campaign"."id"
ORDER BY "campaign"."status" ASC, "campaign"."created" DESC
LIMIT 25;
查询计划：
Limit (cost=6445.26..6445.32 rows=25 width=53) (actual time=642.134..642.422 rows=25 loops=1)
-> Sort (cost=6445.26..6446.80 rows=617 width=53) (actual time=642.113..642.209 rows=25 loops=1)
Sort Key: campaign.status, campaign.created
Sort Method: top-N heapsort Memory: 28kB
-> HashAggregate (cost=6421.68..6427.85 rows=617 width=53) (actual time=634.619..637.342 rows=617 loops=1)
Group Key: campaign.id
-> Hash Right Join (cost=58.88..6269.08 rows=30519 width=53) (actual time=9.986..481.628 rows=31142 loops=1)
Hash Cond: (stats.campaign_id = campaign.id)
-> Seq Scan on stats (cost=0.00..5790.56 rows=30519 width=8) (actual time=0.044..172.346 rows=31027 loops=1)
Filter: ((date >= '2016-03-27'::date) AND (date <= '2016-04-25'::date))
Rows Removed by Filter: 22299
-> Hash (cost=51.17..51.17 rows=617 width=49) (actual time=9.325..9.325 rows=617 loops=1)
Buckets: 1024 Batches: 1 Memory Usage: 52kB
-> Seq Scan on campaign (cost=0.00..51.17 rows=617 width=49) (actual time=0.043..4.490 rows=617 loops=1)
Planning time: 1.778 ms
Execution time: 643.217 ms
表：
Table "public.campaign"
Column | Type | Modifiers
----------------------+--------------------------+---------------------------------------------------------------
id | integer | not null default nextval('campaign_id_seq'::regclass)
name | character varying(255) | not null
created | timestamp with time zone | not null
status | character varying(32) | not null
Indexes:
"campaign_pkey" PRIMARY KEY, btree (id)
"campaign_9acb4454" btree (status)
"campaign_9bea82de" btree (product_id)
"campaign_created_7aea656cce4d74c_uniq" btree (created)
Foreign-key constraints:
TABLE "stats" CONSTRAINT "stats_campaign_id_dabb6227_fk_campaign_id" FOREIGN KEY (campaign_id) REFERENCES campaign(id) DEFERRABLE INITIALLY DEFERRED
Table "public.stats"
Column | Type | Modifiers
-----------------+-------------------------+------------------------------------------------------------
id | integer | not null default nextval('stats_id_seq'::regclass)
date | date | not null
impressions | integer | not null
campaign_id | integer | not null
Indexes:
"stats_pkey" PRIMARY KEY, btree (id)
"stats_date_1de4ab17_uniq" btree (date)
"stats_f14acec3" btree (campaign_id)
Foreign-key constraints:
"stats_campaign_id_dabb6227_fk_campaign_id" FOREIGN KEY (campaign_id) REFERENCES campaign(id) DEFERRABLE INITIALLY DEFERRED
===============
编辑：
如果条件从JOIN移出到WHERE：
，则查询计划Limit (cost=10252.48..10252.55 rows=25 width=252) (actual time=921.152..921.423 rows=25 loops=1)
-> Sort (cost=10252.48..10254.03 rows=617 width=252) (actual time=921.142..921.230 rows=25 loops=1)
Sort Key: campaign.status, campaign.created
Sort Method: top-N heapsort Memory: 37kB
-> HashAggregate (cost=10161.03..10235.07 rows=617 width=252) (actual time=910.690..916.553 rows=550 loops=1)
Group Key: campaign.id
-> Hash Right Join (cost=58.88..6575.05 rows=30519 width=252) (actual time=7.655..708.881 rows=31075 loops=1)
Hash Cond: (stats.campaign_id = campaign.id)
Filter: ((stats.date IS NULL) OR ((stats.date >= '2016-03-27'::date) AND (stats.date <= '2016-04-25'::date)))
Rows Removed by Filter: 22299
-> Seq Scan on stats (cost=0.00..5526.71 rows=52771 width=56) (actual time=0.009..249.230 rows=53326 loops=1)
-> Hash (cost=51.17..51.17 rows=617 width=204) (actual time=7.588..7.588 rows=617 loops=1)
Buckets: 1024 Batches: 1 Memory Usage: 128kB
-> Seq Scan on campaign (cost=0.00..51.17 rows=617 width=204) (actual time=0.009..3.124 rows=617 loops=1)
Planning time: 0.604 ms
Execution time: 922.323 ms
答案 0 :(得分：1)
您可以考虑这样编写查询：
SELECT c."id", c."name", c."status",
(SELECT SUM(s."impressions")
FROM "stats" s
WHERE c."id" = s."campaign_id" AND
s."date" >= '2016-03-27'::date AND
s."date" <= '2016-04-25'::date
) as "impressions"
FROM "campaign" c
ORDER BY c."status" ASC, c."created" DESC ;
然后最好的索引是campaign(status, created desc, name, id)和stats(campaign_id, date, impressions)。注意：这些都是多列索引，它们完全覆盖了查询（意味着所有访问的列都在索引中）。
Postgres优化器很好。但是，不要认为以查询形式优化外部聚合是足够好的。因为它可以使用ORDER BY的索引，所以使用相关子查询的此版本可能比使用显式GROUP BY的版本更快。
答案 1 :(得分：1)
如果您先限制，则可以加快速度，但如果要对stats聚合进行排序
WITH top_campaign (
SELECT *
FROM "campaign"
ORDER BY "campaign"."status" ASC, "campaign"."created" DESC
LIMIT 25
)
SELECT "campaign"."id", "campaign"."name", "campaign"."status", SUM("stats"."impressions") AS "impressions"
FROM "top_campaign" as "campaign"
LEFT OUTER JOIN "stats" ON ("campaign"."id" = "stats"."campaign_id") AND ("stats"."date" >= '2016-03-27'::date) AND ("stats"."date" <= '2016-04-25'::date)
GROUP BY "campaign"."id"
ORDER BY "campaign"."status" ASC, "campaign"."created" DESC