PostgreSQL支持hstore来存放KEY-VALUE这类数据,其实也类似于ARRAY或者JSON类型。要高效的使用这类数据,当然离不开高效的索引。我们今天就来看看两类不同的索引
PostgreSQL 支持hstore 来存放KEY->VALUE这类数据, 其实也类似于ARRAY或者JSON类型。 要高效的使用这类数据,当然离不开高效的索引。我们今天就来看看两类不同的索引对于同一种检索请求的性能问题。
假如我们有这样一个原始表,基于str1字段有一个BTREE索引。
t_girl=# \d status_check; Table "ytt.status_check" Column | Type | Modifiers --------+-----------------------+----------- is_yes | boolean | not null str1 | character varying(20) | not null str2 | character varying(20) | not null Indexes: "index_status_check_str1" btree (str1)里面有10W条记录。 数据大概如下,
t_girl=# select * from status_check limit 2; is_yes | str1 | str2 --------+------+---------------------- f | 0 | cfcd208495d565ef66e7 t | 1 | c4ca4238a0b923820dcc (2 rows) Time: 0.617 ms t_girl=#存放hstore类型的status_check_hstore 表结构,基于str1_str2字段有一个GIST索引。
Table "ytt.status_check_hstore" Column | Type | Modifiers -----------+---------+----------- is_yes | boolean | str1_str2 | hstore | Indexes: "idx_str_str2_gist" gist (str1_str2) t_girl=# select * from status_check_hstore limit 2; is_yes | str1_str2 --------+----------------------------- f | "0"=>"cfcd208495d565ef66e7" t | "1"=>"c4ca4238a0b923820dcc" (2 rows) Time: 39.874 ms接下来我们要得到跟查询原始表一样的结果,当然原始表的查询非常高效。 表语句以及结果如下,
t_girl=# select * from status_check where str1 in ('10','23','33'); is_yes | str1 | str2 --------+------+---------------------- t | 10 | d3d9446802a44259755d t | 23 | 37693cfc748049e45d87 f | 33 | 182be0c5cdcd5072bb18 (3 rows) Time: 0.690 ms上面的语句用了不到1毫秒。
接下来我们对hstore表进行查询,
t_girl=# select is_yes,skeys(str1_str2),svals(str1_str2) from status_check_hstore where str1_str2 ?| array['10','23','33']; is_yes | skeys | svals --------+-------+---------------------- t | 10 | d3d9446802a44259755d t | 23 | 37693cfc748049e45d87 f | 33 | 182be0c5cdcd5072bb18 (3 rows) Time: 40.256 ms我的天,比原始表的查询慢了几十倍。
看下查询计划,把所有行都扫描了一遍。
QUERY PLAN ----------------------------------------------------------------------------------- Bitmap Heap Scan on status_check_hstore (cost=5.06..790.12 rows=100000 width=38) Recheck Cond: (str1_str2 ?| '{10,23,33}'::text[]) -> Bitmap Index Scan on idx_str_str2_gist (cost=0.00..5.03 rows=100 width=0) Index Cond: (str1_str2 ?| '{10,23,33}'::text[]) (4 rows) Time: 0.688 ms我们想办法来优化这条语句, 如果把这条语句变成跟原始语句一样的话,那么是否就可以用到BTREE索引了?

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