在PostgreSQL中使用ltree处理层次结构数据的方法
在本文中,我们将学习如何使用postgresql的ltree模块,该模块允许以分层的树状结构存储数据。
什么是ltree?
ltree是postgresql模块。它实现了一种数据类型ltree,用于表示存储在分层树状结构中的数据的标签。提供了用于搜索标签树的广泛工具。
为什么选择ltree?
- ltree实现了一个物化路径,对于insert / update / delete来说非常快,而对于select操作则较快
- 通常,它比使用经常需要重新计算分支的递归cte或递归函数要快
- 如内置的查询语法和专门用于查询和导航树的运算符
- 索引!!!
初始数据
首先,您应该在数据库中启用扩展。您可以通过以下命令执行此操作:
create extension ltree;
让我们创建表并向其中添加一些数据:
create table comments (user_id integer, description text, path ltree); insert into comments (user_id, description, path) values ( 1, md5(random()::text), '0001'); insert into comments (user_id, description, path) values ( 2, md5(random()::text), '0001.0001.0001'); insert into comments (user_id, description, path) values ( 2, md5(random()::text), '0001.0001.0001.0001'); insert into comments (user_id, description, path) values ( 1, md5(random()::text), '0001.0001.0001.0002'); insert into comments (user_id, description, path) values ( 5, md5(random()::text), '0001.0001.0001.0003'); insert into comments (user_id, description, path) values ( 6, md5(random()::text), '0001.0002'); insert into comments (user_id, description, path) values ( 6, md5(random()::text), '0001.0002.0001'); insert into comments (user_id, description, path) values ( 6, md5(random()::text), '0001.0003'); insert into comments (user_id, description, path) values ( 8, md5(random()::text), '0001.0003.0001'); insert into comments (user_id, description, path) values ( 9, md5(random()::text), '0001.0003.0002'); insert into comments (user_id, description, path) values ( 11, md5(random()::text), '0001.0003.0002.0001'); insert into comments (user_id, description, path) values ( 2, md5(random()::text), '0001.0003.0002.0002'); insert into comments (user_id, description, path) values ( 5, md5(random()::text), '0001.0003.0002.0003'); insert into comments (user_id, description, path) values ( 7, md5(random()::text), '0001.0003.0002.0002.0001'); insert into comments (user_id, description, path) values ( 20, md5(random()::text), '0001.0003.0002.0002.0002'); insert into comments (user_id, description, path) values ( 31, md5(random()::text), '0001.0003.0002.0002.0003'); insert into comments (user_id, description, path) values ( 22, md5(random()::text), '0001.0003.0002.0002.0004'); insert into comments (user_id, description, path) values ( 34, md5(random()::text), '0001.0003.0002.0002.0005'); insert into comments (user_id, description, path) values ( 22, md5(random()::text), '0001.0003.0002.0002.0006');
另外,我们应该添加一些索引:
create index path_gist_comments_idx on comments using gist(path); create index path_comments_idx on comments using btree(path);
正如您看到的那样,我建立comments表时带有path字段,该字段包含该表的tree全部路径。如您所见,对于树分隔符,我使用4个数字和点。
让我们在commenets表中找到path以‘0001.0003'的记录:
$ select user_id, path from comments where path <@ '0001.0003'; user_id | path ---------+-------------------------- 6 | 0001.0003 8 | 0001.0003.0001 9 | 0001.0003.0002 11 | 0001.0003.0002.0001 2 | 0001.0003.0002.0002 5 | 0001.0003.0002.0003 7 | 0001.0003.0002.0002.0001 20 | 0001.0003.0002.0002.0002 31 | 0001.0003.0002.0002.0003 22 | 0001.0003.0002.0002.0004 34 | 0001.0003.0002.0002.0005 22 | 0001.0003.0002.0002.0006 (12 rows)
让我们通过explain命令检查这个sql:
$ explain analyze select user_id, path from comments where path <@ '0001.0003'; query plan ---------------------------------------------------------------------------------------------------- seq scan on comments (cost=0.00..1.24 rows=2 width=38) (actual time=0.013..0.017 rows=12 loops=1) filter: (path <@ '0001.0003'::ltree) rows removed by filter: 7 total runtime: 0.038 ms (4 rows)
让我们禁用seq scan进行测试:
$ set enable_seqscan=false; set $ explain analyze select user_id, path from comments where path <@ '0001.0003'; query plan ----------------------------------------------------------------------------------------------------------------------------------- index scan using path_gist_comments_idx on comments (cost=0.00..8.29 rows=2 width=38) (actual time=0.023..0.034 rows=12 loops=1) index cond: (path <@ '0001.0003'::ltree) total runtime: 0.076 ms (3 rows)
现在sql慢了,但是能看到sql是怎么使用index的。
第一个sql语句使用了sequence scan,因为在表中没有太多的数据。
我们可以将select “path <@ ‘0001.0003'” 换种实现方法:
$ select user_id, path from comments where path ~ '0001.0003.*'; user_id | path ---------+-------------------------- 6 | 0001.0003 8 | 0001.0003.0001 9 | 0001.0003.0002 11 | 0001.0003.0002.0001 2 | 0001.0003.0002.0002 5 | 0001.0003.0002.0003 7 | 0001.0003.0002.0002.0001 20 | 0001.0003.0002.0002.0002 31 | 0001.0003.0002.0002.0003 22 | 0001.0003.0002.0002.0004 34 | 0001.0003.0002.0002.0005 22 | 0001.0003.0002.0002.0006 (12 rows)
你不应该忘记数据的顺序,如下的例子:
$ insert into comments (user_id, description, path) values ( 9, md5(random()::text), '0001.0003.0001.0001'); $ insert into comments (user_id, description, path) values ( 9, md5(random()::text), '0001.0003.0001.0002'); $ insert into comments (user_id, description, path) values ( 9, md5(random()::text), '0001.0003.0001.0003'); $ select user_id, path from comments where path ~ '0001.0003.*'; user_id | path ---------+-------------------------- 6 | 0001.0003 8 | 0001.0003.0001 9 | 0001.0003.0002 11 | 0001.0003.0002.0001 2 | 0001.0003.0002.0002 5 | 0001.0003.0002.0003 7 | 0001.0003.0002.0002.0001 20 | 0001.0003.0002.0002.0002 31 | 0001.0003.0002.0002.0003 22 | 0001.0003.0002.0002.0004 34 | 0001.0003.0002.0002.0005 22 | 0001.0003.0002.0002.0006 9 | 0001.0003.0001.0001 9 | 0001.0003.0001.0002 9 | 0001.0003.0001.0003 (15 rows)
现在进行排序:
$ select user_id, path from comments where path ~ '0001.0003.*' order by path; user_id | path ---------+-------------------------- 6 | 0001.0003 8 | 0001.0003.0001 9 | 0001.0003.0001.0001 9 | 0001.0003.0001.0002 9 | 0001.0003.0001.0003 9 | 0001.0003.0002 11 | 0001.0003.0002.0001 2 | 0001.0003.0002.0002 7 | 0001.0003.0002.0002.0001 20 | 0001.0003.0002.0002.0002 31 | 0001.0003.0002.0002.0003 22 | 0001.0003.0002.0002.0004 34 | 0001.0003.0002.0002.0005 22 | 0001.0003.0002.0002.0006 5 | 0001.0003.0002.0003 (15 rows)
可以在lquery的非星号标签的末尾添加几个修饰符,以使其比完全匹配更匹配:
“ @”-不区分大小写匹配,例如a @匹配a
“ *”-匹配任何带有该前缀的标签,例如foo *匹配foobar
“%”-匹配以下划线开头的单词
$ select user_id, path from comments where path ~ '0001.*{1,2}.0001|0002.*' order by path; user_id | path ---------+-------------------------- 2 | 0001.0001.0001 2 | 0001.0001.0001.0001 1 | 0001.0001.0001.0002 5 | 0001.0001.0001.0003 6 | 0001.0002.0001 8 | 0001.0003.0001 9 | 0001.0003.0001.0001 9 | 0001.0003.0001.0002 9 | 0001.0003.0001.0003 9 | 0001.0003.0002 11 | 0001.0003.0002.0001 2 | 0001.0003.0002.0002 7 | 0001.0003.0002.0002.0001 20 | 0001.0003.0002.0002.0002 31 | 0001.0003.0002.0002.0003 22 | 0001.0003.0002.0002.0004 34 | 0001.0003.0002.0002.0005 22 | 0001.0003.0002.0002.0006 5 | 0001.0003.0002.0003 (19 rows)
我们来为parent ‘0001.0003'找到所有直接的childrens,见下:
$ select user_id, path from comments where path ~ '0001.0003.*{1}' order by path; user_id | path ---------+---------------- 8 | 0001.0003.0001 9 | 0001.0003.0002 (2 rows)
为parent ‘0001.0003'找到所有的childrens,见下:
$ select user_id, path from comments where path ~ '0001.0003.*' order by path; user_id | path ---------+-------------------------- 6 | 0001.0003 8 | 0001.0003.0001 9 | 0001.0003.0001.0001 9 | 0001.0003.0001.0002 9 | 0001.0003.0001.0003 9 | 0001.0003.0002 11 | 0001.0003.0002.0001 2 | 0001.0003.0002.0002 7 | 0001.0003.0002.0002.0001 20 | 0001.0003.0002.0002.0002 31 | 0001.0003.0002.0002.0003 22 | 0001.0003.0002.0002.0004 34 | 0001.0003.0002.0002.0005 22 | 0001.0003.0002.0002.0006 5 | 0001.0003.0002.0003 (15 rows)
为children ‘0001.0003.0002.0002.0005'找到parent:
$ select user_id, path from comments where path = subpath('0001.0003.0002.0002.0005', 0, -1) order by path; user_id | path ---------+--------------------- 2 | 0001.0003.0002.0002 (1 row)
如果你的路径不是唯一的,你会得到多条记录。
概述
可以看出,使用ltree的物化路径非常简单。在本文中,我没有列出ltree的所有可能用法。它不被视为全文搜索问题ltxtquery。但是您可以在postgresql官方文档()中找到它。
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