sql - 如何优化 PostgreSQL COUNT GROUP BY 查询？

Question

我有一个包含大约 30 万条记录的 parameters_products 表。是否可以优化此查询？

SELECT parameter_id AS id,
       COUNT(product_id) AS COUNT
FROM "parameters_products"
WHERE product_id IN
    (SELECT product_id
     FROM parameters_products
     WHERE parameter_id IN ('2'))
GROUP BY parameter_id

查询输出:

2;274669

EXPLAIN ANALYZE VERBOSE...输出:

HashAggregate  (cost=23628.54..23628.56 rows=2 width=8) (actual time=2231.367..2231.368 rows=1 loops=1)
  Output: parameters_products.parameter_id, count(parameters_products.product_id)
  Group Key: parameters_products.parameter_id
  ->  Hash Semi Join  (cost=9607.86..22256.43 rows=274421 width=8) (actual time=692.586..1893.261 rows=274669 loops=1)
        Output: parameters_products.parameter_id, parameters_products.product_id
        Hash Cond: (parameters_products.product_id = parameters_products_1.product_id)
        ->  Seq Scan on public.parameters_products  (cost=0.00..4356.28 rows=299728 width=8) (actual time=0.025..353.358 rows=299728 loops=1)
              Output: parameters_products.parameter_id, parameters_products.product_id
        ->  Hash  (cost=5105.60..5105.60 rows=274421 width=4) (actual time=692.331..692.331 rows=274669 loops=1)
              Output: parameters_products_1.product_id
              Buckets: 16384  Batches: 4  Memory Usage: 2425kB
              ->  Seq Scan on public.parameters_products parameters_products_1  (cost=0.00..5105.60 rows=274421 width=4) (actual time=0.013..344.656 rows=274669 loops=1)
                    Output: parameters_products_1.product_id
                    Filter: (parameters_products_1.parameter_id = 2)
                    Rows Removed by Filter: 25059
Planning time: 0.279 ms
Execution time: 2231.499 ms

PostgreSQL 9.4.1 和 VACUUM 已启用。

刚刚试过这个查询，但它也很慢:

SELECT pp1.parameter_id,
       count(pp1.product_id)
FROM parameters_products pp1
LEFT JOIN parameters_products pp2 ON pp1.product_id = pp2.product_id
WHERE pp2.parameter_id IN (2)
GROUP BY pp1.parameter_id

--

HashAggregate  (cost=23742.42..23742.44 rows=2 width=8) (actual time=2361.654..2361.654 rows=1 loops=1)
  Output: pp1.parameter_id, count(pp1.product_id)
  Group Key: pp1.parameter_id
  ->  Hash Join  (cost=9607.86..22370.31 rows=274421 width=8) (actual time=715.409..2012.345 rows=274669 loops=1)
        Output: pp1.parameter_id, pp1.product_id
        Hash Cond: (pp1.product_id = pp2.product_id)
        ->  Seq Scan on public.parameters_products pp1  (cost=0.00..4356.28 rows=299728 width=8) (actual time=0.012..360.789 rows=299728 loops=1)
              Output: pp1.parameter_id, pp1.product_id
        ->  Hash  (cost=5105.60..5105.60 rows=274421 width=4) (actual time=715.176..715.176 rows=274669 loops=1)
              Output: pp2.product_id
              Buckets: 16384  Batches: 4  Memory Usage: 2425kB
              ->  Seq Scan on public.parameters_products pp2  (cost=0.00..5105.60 rows=274421 width=4) (actual time=0.009..353.386 rows=274669 loops=1)
                    Output: pp2.product_id
                    Filter: (pp2.parameter_id = 2)
                    Rows Removed by Filter: 25059
Planning time: 0.135 ms
Execution time: 2361.735 ms

索引:

CREATE INDEX parameters_products_parameter_id_idx
  ON parameters_products
  USING btree
  (parameter_id);

CREATE INDEX parameters_products_product_id_idx
  ON parameters_products
  USING btree
  (product_id);

CREATE INDEX parameters_products_product_id_parameter_id_idx
  ON parameters_products
  USING btree
  (product_id, parameter_id);

---

EXPLAIN ANALYZE VERBOSE
SELECT pp1.parameter_id
FROM parameters_products pp1
LEFT JOIN parameters_products pp2 ON pp1.product_id = pp2.product_id

-

Hash Left Join  (cost=9241.88..22699.06 rows=299728 width=4) (actual time=727.683..2080.798 rows=299728 loops=1)
  Output: pp1.parameter_id
  Hash Cond: (pp1.product_id = pp2.product_id)
  ->  Seq Scan on public.parameters_products pp1  (cost=0.00..4324.28 rows=299728 width=8) (actual time=0.031..355.656 rows=299728 loops=1)
        Output: pp1.parameter_id, pp1.product_id
  ->  Hash  (cost=4324.28..4324.28 rows=299728 width=4) (actual time=727.579..727.579 rows=299728 loops=1)
        Output: pp2.product_id
        Buckets: 16384  Batches: 4  Memory Usage: 2644kB
        ->  Seq Scan on public.parameters_products pp2  (cost=0.00..4324.28 rows=299728 width=4) (actual time=0.008..350.797 rows=299728 loops=1)
              Output: pp2.product_id
Planning time: 0.472 ms
Execution time: 2392.582 ms

---

SET enable_seqscan = OFF;

减少了执行时间，但幅度不大。

Answer 1

我要尝试的第一件事是用 EXISTS 替换 IN:

SELECT parameter_id AS id,
       COUNT(product_id) AS COUNT
FROM parameters_products pp
WHERE EXISTS (SELECT 1
              FROM parameters_products pp2
              WHERE pp2.product_id = pp.product_id AND
                    pp2.parameter_id = 2
             ) 
GROUP BY parameter_id;

并且，确保您在 parameters_products(product_id, parameter_id) 上有一个索引。

另一个想法是使用窗口函数:

select parameter_id, count(*)
from (select pp.*,
             sum(case when pp.parameter_id = 2 then 1 else 0 end) over (partition by product_id) as cnt2
      from parameters_products pp
     ) pp
where cnt2 > 0
group by parameter_id;