PostgreSQL中的词典排序非常慢？

我有一个vote_pairs视图,看起来像这样：

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,在投票表中有大约100k行,跨此视图的查询大约需要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;

运行时间翻了四倍,在vote_pairs上完成查询需要大约12秒.

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,则查询同样很慢：

SELECT * FROM vote_pairs WHERE name1 < name2;

这是怎么回事？ Postgres的词典比较速度慢吗？这是别的吗？我怎么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)

并使用过滤器：

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：

>已经运行了VACCUM FULL和ANALYZE投票
> 8.4.11和9.2.3都以相同的方式运行

是的,文本比较有时很慢.你可能想尝试：

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.

PostgreSQL中的词典排序非常慢？

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