请帮我优化以下查询:
EXPLAIN ANALYZE
SELECT
"subscriptions"."id" AS t0_r0,
"subscriptions"."created_at" AS t0_r3,
"subscriptions"."updated_at" AS t0_r4,
"subscriptions"."next_date" AS t0_r5,
"subscriptions"."number_of_games" AS t0_r6,
"subscriptions"."renewal_date" AS t0_r7,
"subscriptions"."type" AS t0_r8,
"subscriptions"."order_id" AS t0_r9,
"orders"."id" AS t1_r0,
"orders"."customer_id" AS t1_r1,
"orders"."created_at" AS t1_r2,
"orders"."updated_at" AS t1_r3,
"orders"."payment_id" AS t1_r4,
"orders"."status" AS t1_r5,
"orders"."col13" AS t1_r13,
"orders"."col14" AS t1_r14,
"orders"."col15" AS t1_r15,
"orders"."active_subscription_id" AS t1_r21,
"orders"."product_id" AS t1_r22
FROM
"subscriptions"
INNER JOIN "orders" ON "orders"."id" = "subscriptions"."order_id"
WHERE
"subscriptions"."type" IN ('Const1')
AND "orders"."status" = 'confirm'
AND "orders"."product_id" IN (1, 95, 79, 22)
AND ("subscriptions"."renewal_date" BETWEEN '2017-09-23' AND '2017-09-29') AND (orders.active_subscription_id = subscriptions.id)
AND ("subscriptions"."number_of_games" >= 5)
AND ("subscriptions"."id" NOT IN (
SELECT subscriptions.id
FROM "subscriptions"
INNER JOIN "orders" ON "orders"."id" = "subscriptions"."order_id"
INNER JOIN "table1" ON "table1"."order_id" = "orders"."id"
WHERE "subscriptions"."type" IN ('Const1')
AND "orders"."status" = 'confirm'
AND "orders"."product_id" IN (1, 95, 79, 22)
AND "table1"."col1" IN ('1041', '1042')
AND ("subscriptions"."renewal_date" BETWEEN '2017-09-23' AND '2017-09-29')
AND (orders.active_subscription_id = subscriptions.id)
AND ("subscriptions"."number_of_games" >= 5))
) ;
最初有b树索引:
CREATE INDEX index_table1_on_order_id ON table1 USING btree (order_id);
CREATE INDEX index_orders_on_active_subscription_id ON orders USING btree (active_subscription_id);
CREATE INDEX index_orders_on_status ON orders USING btree (status);
CREATE INDEX orders_payment_id_idx ON orders USING btree (payment_id);
CREATE INDEX index_subscriptions_on_order_id ON subscriptions USING btree (order_id);
名称为“id”的所有列都是主键。 执行计划:
Nested Loop (cost=18699.70..38236.80 rows=1 width=466) (actual time=11185.634..11336.548 rows=3352 loops=1)
-> Seq Scan on subscriptions (cost=18699.28..37754.22 rows=57 width=76) (actual time=11185.610..11309.520 rows=3356 loops=1)
Filter: ((renewal_date >= '2017-09-23'::date) AND (renewal_date <= '2017-09-29'::date) AND (number_of_games >= 5) AND (NOT (hashed SubPlan 1)) AND ((type)::text = 'Const1'::text))
Rows Removed by Filter: 522626
SubPlan 1
-> Nested Loop (cost=0.85..18699.28 rows=1 width=4) (actual time=6743.644..11185.269 rows=31 loops=1)
-> Nested Loop (cost=0.42..18697.21 rows=1 width=12) (actual time=0.150..1792.440 rows=3383 loops=1)
-> Seq Scan on subscriptions subscriptions_1 (cost=0.00..17740.06 rows=114 width=8) (actual time=0.114..145.256 rows=3387 loops=1)
Filter: ((renewal_date >= '2017-09-23'::date) AND (renewal_date <= '2017-09-29'::date) AND (number_of_games >= 5) AND ((type)::text = 'Const1'::text))
Rows Removed by Filter: 522595
-> Index Scan using index_orders_on_active_subscription_id on orders orders_1 (cost=0.42..8.39 rows=1 width=8) (actual time=0.471..0.484 rows=1 loops=3387)
Index Cond: (active_subscription_id = subscriptions_1.id)
Filter: (((status)::text = 'confirm'::text) AND (subscriptions_1.order_id = id) AND (product_id = ANY ('{1,95,79,22}'::integer[])))
Rows Removed by Filter: 0
-> Index Scan using index_table1_on_order_id on table1 (cost=0.43..2.05 rows=1 width=4) (actual time=2.775..2.775 rows=0 loops=3383)
Index Cond: (order_id = orders_1.id)
Filter: ((col1)::text = ANY ('{1041,1042}'::text[]))
Rows Removed by Filter: 5
-> Index Scan using index_orders_on_active_subscription_id on orders (cost=0.42..8.46 rows=1 width=390) (actual time=0.007..0.007 rows=1 loops=3356)
Index Cond: (active_subscription_id = subscriptions.id)
Filter: (((status)::text = 'confirm'::text) AND (subscriptions.order_id = id) AND (product_id = ANY ('{1,95,79,22}'::integer[])))
Rows Removed by Filter: 0
Planning time: 3.928 ms
Execution time: 11337.023 ms
创建以下索引:
CREATE INDEX index_subscriptions_on_renewal_date ON subscriptions USING btree (renewal_date);
并没有让事情变得更好。即使重写查询也不会改善性能:
EXPLAIN ANALYZE
With subscriptions_1 as (
SELECT
"subscriptions"."id" AS t0_r0,
"subscriptions"."created_at" AS t0_r3,
"subscriptions"."updated_at" AS t0_r4,
"subscriptions"."next_date" AS t0_r5,
"subscriptions"."number_of_games" AS t0_r6,
"subscriptions"."renewal_date" AS t0_r7,
"subscriptions"."type" AS t0_r8,
"subscriptions"."order_id" AS t0_r9
FROM
"subscriptions"
WHERE
"subscriptions"."type" IN ('Const1')
AND ("subscriptions"."renewal_date" >= '2017-09-23' AND "subscriptions"."renewal_date" <= '2017-09-29')
AND ("subscriptions"."number_of_games" >= 5)
ORDER BY "subscriptions"."id"
)
SELECT
Subscriptions_1.*,
"orders"."id" AS t1_r0,
"orders"."customer_id" AS t1_r1,
"orders"."created_at" AS t1_r2,
"orders"."updated_at" AS t1_r3,
"orders"."payment_id" AS t1_r4,
"orders"."status" AS t1_r5,
"orders"."col13" AS t1_r13,
"orders"."col14" AS t1_r14,
"orders"."col15" AS t1_r15,
"orders"."active_subscription_id" AS t1_r21,
"orders"."product_id" AS t1_r22
FROM
Subscriptions_1
INNER JOIN "orders" ON "orders"."id" = subscriptions_1.t0_r9
WHERE
"orders"."status" = 'confirm'
AND "orders"."product_id" IN (1,95,79,22)
AND (orders.active_subscription_id = subscriptions_1.t0_r0)
AND (subscriptions_1.t0_r0 NOT IN (SELECT subscriptions_1.t0_r0 FROM subscriptions_1 INNER JOIN "orders" ON "orders"."id" = subscriptions_1.t0_r9 INNER JOIN "table1" ON "table1"."order_id" = "orders"."id" WHERE "orders"."status" = 'confirm' AND "orders"."product_id" IN (1,95,79,22) AND "table1"."col1" IN ('1041', '1042') AND (orders.active_subscription_id = subscriptions_1.t0_r0))
) ;
答案 0 :(得分:1)
该计划非常糟糕,因为PostgreSQL低估了结果行的数量(1而不是subscriptions
和orders
之间的联接中的实际3383。)
这导致PostgreSQL为table1
的连接选择一个嵌套循环连接,这是你的11秒中的9个。
有几种方法:
在受影响的所有表格上运行ANALYZE
,可能会增加default_statistics_target
。也许新的统计数据会带来更好的估计。
如果这没有帮助,请创建索引ON table1(order_id, col1::text)
,这将尽可能加快嵌套循环连接。
残酷的方式:为此一个查询设置enable_nestloop
至off
。