数据库

postgresql 中的 like 查询优化方案
数据库 2024/11/5 佚名
3 2

当时数量量比较庞大的时候，做模糊查询效率很慢，为了优化查询效率，尝试如下方法做效率对比

一、对比情况说明：

1、数据量100w条数据

2、执行sql

二、对比结果

explain analyze SELECT
 c_patent,
 c_applyissno,
 d_applyissdate,
 d_applydate,
 c_patenttype_dimn,
 c_newlawstatus,
 c_abstract 
FROM
 public.t_knowl_patent_zlxx_temp 
WHERE
 c_applicant LIKE '%本溪满族自治县连山关镇安平安养殖场%';

1、未建索时执行计划：

"Gather (cost=1000.00..83803.53 rows=92 width=1278) (actual time=217.264..217.264 rows=0 loops=1)
 Workers Planned: 2
 Workers Launched: 2
 -> Parallel Seq Scan on t_knowl_patent_zlxx (cost=0.00..82794.33 rows=38 width=1278) (actual time=212.355..212.355 rows=0 loops=3)
  Filter: ((c_applicant)::text ~~ '%本溪满族自治县连山关镇安平安养殖场%'::text)
  Rows Removed by Filter: 333333
Planning time: 0.272 ms
Execution time: 228.116 ms"

2、btree索引

建索引语句

CREATE INDEX idx_public_t_knowl_patent_zlxx_applicant ON public.t_knowl_patent_zlxx(c_applicant varchar_pattern_ops);

执行计划

"Gather (cost=1000.00..83803.53 rows=92 width=1278) (actual time=208.253..208.253 rows=0 loops=1)
 Workers Planned: 2
 Workers Launched: 2
 -> Parallel Seq Scan on t_knowl_patent_zlxx (cost=0.00..82794.33 rows=38 width=1278) (actual time=203.573..203.573 rows=0 loops=3)
  Filter: ((c_applicant)::text ~~ '%本溪满族自治县连山关镇安平安养殖场%'::text)
  Rows Removed by Filter: 333333
Planning time: 0.116 ms
Execution time: 218.189 ms"

但是如果将查询sql稍微改动一下，把like查询中的前置%去掉是这样的

Index Scan using idx_public_t_knowl_patent_zlxx_applicant on t_knowl_patent_zlxx_temp (cost=0.55..8.57 rows=92 width=1278) (actual time=0.292..0.292 rows=0 loops=1)
 Index Cond: (((c_applicant)::text ~>=~ '本溪满族自治县连山关镇安平安养殖场'::text) AND ((c_applicant)::text ~<~ '本溪满族自治县连山关镇安平安养殖圻'::text))
 Filter: ((c_applicant)::text ~~ '本溪满族自治县连山关镇安平安养殖场%'::text)
Planning time: 0.710 ms
Execution time: 0.378 ms

3、gin索引

创建索引语句(postgresql要求在9.6版本及以上)

create extension pg_trgm;
CREATE INDEX idx_public_t_knowl_patent_zlxx_applicant ON public.t_knowl_patent_zlxx USING gin (c_applicant gin_trgm_ops);

执行计划

Bitmap Heap Scan on t_knowl_patent_zlxx (cost=244.71..600.42 rows=91 width=1268) (actual time=0.649..0.649 rows=0 loops=1)
 Recheck Cond: ((c_applicant)::text ~~ '%本溪满族自治县连山关镇安平安养殖场%'::text)
 -> Bitmap Index Scan on idx_public_t_knowl_patent_zlxx_applicant (cost=0.00..244.69 rows=91 width=0) (actual time=0.647..0.647 rows=0 loops=1)
  Index Cond: ((c_applicant)::text ~~ '%本溪满族自治县连山关镇安平安养殖场%'::text)
Planning time: 0.673 ms
Execution time: 0.740 ms

三、结论

btree索引可以让后置% "abc%"的模糊匹配走索引，gin + gp_trgm可以让前后置% "%abc%" 走索引。但是gin 索引也有弊端，以下情况可能导致无法命中：

搜索字段少于3个字符时，不会命中索引，这是gin自身机制导致。

当搜索字段过长时，比如email检索，可能也不会命中索引，造成原因暂时未知。

补充：PostgreSQL LIKE 查询效率提升实验

一、未做索引的查询效率

作为对比，先对未索引的查询做测试

EXPLAIN ANALYZE select * from gallery_map where author = '曹志耘';
             QUERY PLAN             
-----------------------------------------------------------------------------------------------------------------
 Seq Scan on gallery_map (cost=0.00..7002.32 rows=1025 width=621) (actual time=0.011..39.753 rows=1031 loops=1)
 Filter: ((author)::text = '曹志耘'::text)
 Rows Removed by Filter: 71315
 Planning time: 0.194 ms
 Execution time: 39.879 ms
(5 rows)
 
Time: 40.599 ms
EXPLAIN ANALYZE select * from gallery_map where author like '曹志耘';
             QUERY PLAN             
-----------------------------------------------------------------------------------------------------------------
 Seq Scan on gallery_map (cost=0.00..7002.32 rows=1025 width=621) (actual time=0.017..41.513 rows=1031 loops=1)
 Filter: ((author)::text ~~ '曹志耘'::text)
 Rows Removed by Filter: 71315
 Planning time: 0.188 ms
 Execution time: 41.669 ms
(5 rows)
 
Time: 42.457 ms
 
EXPLAIN ANALYZE select * from gallery_map where author like '曹志耘%';
             QUERY PLAN             
-----------------------------------------------------------------------------------------------------------------
 Seq Scan on gallery_map (cost=0.00..7002.32 rows=1028 width=621) (actual time=0.017..41.492 rows=1031 loops=1)
 Filter: ((author)::text ~~ '曹志耘%'::text)
 Rows Removed by Filter: 71315
 Planning time: 0.307 ms
 Execution time: 41.633 ms
(5 rows)
 
Time: 42.676 ms

很显然都会做全表扫描

二、创建btree索引

PostgreSQL默认索引是btree

CREATE INDEX ix_gallery_map_author ON gallery_map (author);
 
EXPLAIN ANALYZE select * from gallery_map where author = '曹志耘';  
                QUERY PLAN                
-------------------------------------------------------------------------------------------------------------------------------------
 Bitmap Heap Scan on gallery_map (cost=36.36..2715.37 rows=1025 width=621) (actual time=0.457..1.312 rows=1031 loops=1)
 Recheck Cond: ((author)::text = '曹志耘'::text)
 Heap Blocks: exact=438
 -> Bitmap Index Scan on ix_gallery_map_author (cost=0.00..36.10 rows=1025 width=0) (actual time=0.358..0.358 rows=1031 loops=1)
   Index Cond: ((author)::text = '曹志耘'::text)
 Planning time: 0.416 ms
 Execution time: 1.422 ms
(7 rows)
 
Time: 2.462 ms
 
EXPLAIN ANALYZE select * from gallery_map where author like '曹志耘';
                QUERY PLAN                
-------------------------------------------------------------------------------------------------------------------------------------
 Bitmap Heap Scan on gallery_map (cost=36.36..2715.37 rows=1025 width=621) (actual time=0.752..2.119 rows=1031 loops=1)
 Filter: ((author)::text ~~ '曹志耘'::text)
 Heap Blocks: exact=438
 -> Bitmap Index Scan on ix_gallery_map_author (cost=0.00..36.10 rows=1025 width=0) (actual time=0.560..0.560 rows=1031 loops=1)
   Index Cond: ((author)::text = '曹志耘'::text)
 Planning time: 0.270 ms
 Execution time: 2.295 ms
(7 rows)
 
Time: 3.444 ms
EXPLAIN ANALYZE select * from gallery_map where author like '曹志耘%';
             QUERY PLAN             
-----------------------------------------------------------------------------------------------------------------
 Seq Scan on gallery_map (cost=0.00..7002.32 rows=1028 width=621) (actual time=0.015..41.389 rows=1031 loops=1)
 Filter: ((author)::text ~~ '曹志耘%'::text)
 Rows Removed by Filter: 71315
 Planning time: 0.260 ms
 Execution time: 41.518 ms
(5 rows)
 
Time: 42.430 ms
EXPLAIN ANALYZE select * from gallery_map where author like '%研究室';
             QUERY PLAN             
-----------------------------------------------------------------------------------------------------------------
 Seq Scan on gallery_map (cost=0.00..7002.32 rows=2282 width=621) (actual time=0.064..52.824 rows=2152 loops=1)
 Filter: ((author)::text ~~ '%研究室'::text)
 Rows Removed by Filter: 70194
 Planning time: 0.254 ms
 Execution time: 53.064 ms
(5 rows)
 
Time: 53.954 ms

可以看到，等于、like的全匹配是用到索引的，like的模糊查询还是全表扫描

三、创建gin索引

CREATE EXTENSION pg_trgm;
 
CREATE INDEX ix_gallery_map_author ON gallery_map USING gin (author gin_trgm_ops);
EXPLAIN ANALYZE select * from gallery_map where author like '曹%'; 
                QUERY PLAN                
-------------------------------------------------------------------------------------------------------------------------------------
 Bitmap Heap Scan on gallery_map (cost=19.96..2705.69 rows=1028 width=621) (actual time=0.419..1.771 rows=1031 loops=1)
 Recheck Cond: ((author)::text ~~ '曹%'::text)
 Heap Blocks: exact=438
 -> Bitmap Index Scan on ix_gallery_map_author (cost=0.00..19.71 rows=1028 width=0) (actual time=0.312..0.312 rows=1031 loops=1)
   Index Cond: ((author)::text ~~ '曹%'::text)
 Planning time: 0.358 ms
 Execution time: 1.916 ms
(7 rows)
 
Time: 2.843 ms
EXPLAIN ANALYZE select * from gallery_map where author like '%耘%'; 
             QUERY PLAN             
-----------------------------------------------------------------------------------------------------------------
 Seq Scan on gallery_map (cost=0.00..7002.32 rows=1028 width=621) (actual time=0.015..51.641 rows=1031 loops=1)
 Filter: ((author)::text ~~ '%耘%'::text)
 Rows Removed by Filter: 71315
 Planning time: 0.268 ms
 Execution time: 51.957 ms
(5 rows)
 
Time: 52.899 ms
EXPLAIN ANALYZE select * from gallery_map where author like '%研究室%';
                QUERY PLAN                
-------------------------------------------------------------------------------------------------------------------------------------
 Bitmap Heap Scan on gallery_map (cost=31.83..4788.42 rows=2559 width=621) (actual time=0.914..4.195 rows=2402 loops=1)
 Recheck Cond: ((author)::text ~~ '%研究室%'::text)
 Heap Blocks: exact=868
 -> Bitmap Index Scan on ix_gallery_map_author (cost=0.00..31.19 rows=2559 width=0) (actual time=0.694..0.694 rows=2402 loops=1)
   Index Cond: ((author)::text ~~ '%研究室%'::text)
 Planning time: 0.306 ms
 Execution time: 4.403 ms
(7 rows)
 
Time: 5.227 ms

gin_trgm索引的效果好多了

由于pg_trgm的索引是把字符串切成多个3元组，然后使用这些3元组做匹配，所以gin_trgm索引对于少于3个字符（包括汉字）的查询，只有前缀匹配会走索引

另外，还测试了btree_gin，效果和btree一样

注意：

gin_trgm要求数据库必须使用UTF-8编码

demo_v1 # \l demo_v1
        List of databases
 Name | Owner | Encoding | Collate | Ctype | Access privileges
---------+-----------+----------+-------------+-------------+-------------------
 demo_v1 | wmpp_user | UTF8  | en_US.UTF-8 | en_US.UTF-8 |

以上为个人经验，希望能给大家一个参考，也希望大家多多支持。如有错误或未考虑完全的地方，望不吝赐教。

标签：
postgresql,like查询优化
免责声明：本站文章均来自网站采集或用户投稿，网站不提供任何软件下载或自行开发的软件！ 如有用户或公司发现本站内容信息存在侵权行为，请邮件告知！ 858582#qq.com
白云城资源网 Copyright www.dyhadc.com

评论“postgresql 中的 like 查询优化方案”

暂无“postgresql 中的 like 查询优化方案”评论...
www.dyhadc.com 白云城资源网
129,905影音资源
244,626技术资源
111,817软件资源
578,645站长资源
一句话新闻
一口气升级7个大模型SaaS应用，百度智能云：突出一个“开箱即用” - 2024/11/5

这一波大模型产业落地浪潮里，不少企业其实处在 “干瞪眼“的状态。

一种情况是，很多大模型产品看得见却摸不着，在台上一个个遥遥领先——今天Sora技精四座，明天英伟达的机器人又赢得满堂彩，可是到了台下一问：啥时候能用上啊？答曰：遥遥无期。

另一种情况是，企业想用上大模型，却又难免瞻前顾后——既要考虑场景融合，又得兼顾安全性，还要考虑打通现有系统，再加上各种部署成本和繁琐的采购流程……最后只能拂袖：罢了，再等等吧。

稳了！魔兽国服回归的3条重磅消息！官宣时间再确认！

昨天有一位朋友在大神群里分享，自己亚服账号被封号之后居然弹出了国服的封号信息对话框。

这里面让他访问的是一个国服的战网网址，com.cn和后面的zh都非常明白地表明这就是国服战网。

而他在复制这个网址并且进行登录之后，确实是网易的网址，也就是我们熟悉的停服之后国服发布的暴雪游戏产品运营到期开放退款的说明。这是一件比较奇怪的事情，因为以前都没有出现这样的情况，现在突然提示跳转到国服战网的网址，是不是说明了简体中文客户端已经开始进行更新了呢？

更新日志

友情链接

杰晶网络 DDR爱好者之家 南强小屋 黑松山资源网 白云城资源网 更多链接
白云城资源网 Copyright www.dyhadc.com