我有一个vote_pairs视图，如下所示：
CREATE VIEW vote_pairs AS
SELECT
v1.name as name1,
v2.name as name2,
...
FROM votes AS v1
JOIN votes AS v2
ON v1.topic_id = v2.topic_id;
并且，votes表中的行数约为100k，此视图中的查询大约需要3秒钟才能执行。
但是，当我在名称上添加额外的过滤器时：
… ON v1.topic_id = v2.topic_id AND v1.name < v2.name;
运行时翻两番，在vote_pairs之间完成查询需要大约12秒钟。
无论限制的位置如何，此运行时都是一致的...例如，如果将过滤器移动到外部查询的WHERE子句，则查询速度同样慢：
SELECT * FROM vote_pairs WHERE name1 < name2;
发生了什么事？ Postgres的词典比较速度慢吗？这是别的吗？我怎样才能提高这个查询的速度？
投票表：
CREATE TABLE votes (
topic_id INTEGER REFERENCES topics(id),
name VARCHAR(64),
vote VARCHAR(12)
)
CREATE INDEX votes_topic_name ON votes (topic_id, name);
CREATE INDEX votes_name ON votes (name);
没有名称过滤器的EXPLAIN ANALYZE的输出：
db=# CREATE OR REPLACE VIEW vote_pairs AS
db-# SELECT
db-# v1.name as name1,
db-# v2.name as name2
db-# FROM votes AS v1
db-# JOIN votes AS v2
db-# ON v1.topic_id = v2.topic_id;
CREATE VIEW
db=# EXPLAIN ANALYZE SELECT * FROM vote_pairs; QUERY PLAN
-----------------------------------------------------------------------------------------------------------------------------
Hash Join (cost=3956.38..71868.56 rows=5147800 width=28) (actual time=51.810..1236.673 rows=5082750 loops=1)
Hash Cond: (v1.topic_id = v2.topic_id)
-> Seq Scan on votes v1 (cost=0.00..1882.50 rows=112950 width=18) (actual time=0.019..18.358 rows=112950 loops=1)
-> Hash (cost=1882.50..1882.50 rows=112950 width=18) (actual time=50.671..50.671 rows=112950 loops=1)
-> Seq Scan on votes v2 (cost=0.00..1882.50 rows=112950 width=18) (actual time=0.004..20.306 rows=112950 loops=1)
Total runtime: 1495.963 ms
(6 rows)
使用过滤器：
db=# CREATE OR REPLACE VIEW vote_pairs AS
db-# SELECT
db-# v1.name as name1,
db-# v2.name as name2
db-# FROM votes AS v1
db-# JOIN votes AS v2
db-# ON v1.topic_id = v2.topic_id AND v1.name < v2.name;
CREATE VIEW
db=# EXPLAIN ANALYZE SELECT * FROM vote_pairs;
QUERY PLAN
-----------------------------------------------------------------------------------------------------------------------------
Hash Join (cost=3956.38..84738.06 rows=1715933 width=28) (actual time=66.688..6900.478 rows=2484900 loops=1)
Hash Cond: (v1.topic_id = v2.topic_id)
Join Filter: ((v1.name)::text < (v2.name)::text)
-> Seq Scan on votes v1 (cost=0.00..1882.50 rows=112950 width=18) (actual time=0.023..24.539 rows=112950 loops=1)
-> Hash (cost=1882.50..1882.50 rows=112950 width=18) (actual time=65.603..65.603 rows=112950 loops=1)
-> Seq Scan on votes v2 (cost=0.00..1882.50 rows=112950 width=18) (actual time=0.004..26.756 rows=112950 loops=1)
Total runtime: 7048.740 ms
(7 rows)
EXPLAIN（ANALYZE，BUFFERS）：
db=# EXPLAIN (ANALYZE, BUFFERS) SELECT * FROM vote_pairs;
QUERY PLAN
-----------------------------------------------------------------------------------------------------------------------------
Hash Join (cost=3956.38..71345.89 rows=5152008 width=28) (actual time=56.230..1204.522 rows=5082750 loops=1)
Hash Cond: (v1.topic_id = v2.topic_id)
Buffers: shared hit=129 read=1377 written=2, temp read=988 written=974
-> Seq Scan on votes v1 (cost=0.00..1882.50 rows=112950 width=18) (actual time=0.008..20.492 rows=112950 loops=1)
Buffers: shared hit=77 read=676
-> Hash (cost=1882.50..1882.50 rows=112950 width=18) (actual time=55.742..55.742 rows=112950 loops=1)
Buckets: 2048 Batches: 8 Memory Usage: 752kB
Buffers: shared hit=52 read=701 written=2, temp written=480
-> Seq Scan on votes v2 (cost=0.00..1882.50 rows=112950 width=18) (actual time=0.004..22.954 rows=112950 loops=1)
Buffers: shared hit=52 read=701 written=2
Total runtime: 1499.302 ms
(11 rows)
db=# EXPLAIN (ANALYZE, BUFFERS) SELECT * FROM vote_pairs WHERE name1 > name2;
QUERY PLAN
-----------------------------------------------------------------------------------------------------------------------------
Hash Join (cost=3956.38..84225.91 rows=1717336 width=28) (actual time=51.214..6422.592 rows=2484900 loops=1)
Hash Cond: (v1.topic_id = v2.topic_id)
Join Filter: ((v1.name)::text > (v2.name)::text)
Rows Removed by Join Filter: 2597850
Buffers: shared hit=32 read=1477, temp read=988 written=974
-> Seq Scan on votes v1 (cost=0.00..1882.50 rows=112950 width=18) (actual time=0.008..22.605 rows=112950 loops=1)
Buffers: shared hit=27 read=726
-> Hash (cost=1882.50..1882.50 rows=112950 width=18) (actual time=50.678..50.678 rows=112950 loops=1)
Buckets: 2048 Batches: 8 Memory Usage: 752kB
Buffers: shared hit=2 read=751, temp written=480
-> Seq Scan on votes v2 (cost=0.00..1882.50 rows=112950 width=18) (actual time=0.005..21.337 rows=112950 loops=1)
Buffers: shared hit=2 read=751
Total runtime: 6573.308 ms
(13 rows)
杂项说明：
VACCUM FULL和ANALYZE votes已经投放答案 0 :(得分：5)
是的，文字比较有时很慢。您可以尝试：
SELECT * FROM vote_pairs WHERE name1 > name2 collate "C";
这应该更快一些，因为它不会考虑特定于语言环境的比较规则。此外，您的解释分析结果表明您的shared_buffers可能设置得太低。
答案 1 :(得分：1)
我猜测会增加缓慢度，因为v1.name < v2.name过滤器会为跨产品联接中的每一行添加一些固定的操作集。
更有效的操作是检查v1.name <> v2.name，但是您会得到重复的结果，例如(A,B), (B,A)。 然后我们可以将v1.name < v2.name添加回WHERE子句，该子句会修剪重复项，并且由于我们的简化过滤器，希望能够减少行数。
试试这个：
CREATE OR REPLACE VIEW vote_pairs AS
SELECT
v1.name as name1,
v2.name as name2
FROM votes AS v1
JOIN votes AS v2
ON v1.topic_id = v2.topic_id AND v1.name <> v2.name
WHERE v1.name < v2.name;
（编辑：似乎COLLATE "C"是可行的方法，但我会留下这个答案，因为这是减少行暴露于慢速操作的好方法。）