详细聊一聊mysql的树形结构存储以及查询

本文主要研究一下mysql的树形结构存储及查询

存储parent

这种方式就是每个节点存储自己的parent_id信息

建表及数据准备


 	CREATE TABLE `menu` (
 	     `id` int(11) NOT NULL AUTO_INCREMENT,
 	     `name` varchar(50) NOT NULL,
 	     `parent_id` int(11) NOT NULL DEFAULT '0',
 	     PRIMARY KEY (`id`)
 	) ENGINE=InnoDB;
 	 
 	INSERT INTO `menu` (`id`, `name`, `parent_id`) VALUES
 	(1, 'level1a', 0),
 	(2, 'level1b', 0),
 	(3, 'level2a-1a',1),
 	(4, 'level2b-1a',1),
 	(5, 'level2a-1b', 2),
 	(6, 'level2b-1b', 2),
 	(7, 'level3-2a1a', 3),
 	(8, 'level3-2b1a', 4),
 	(9, 'level3-2a1b', 5),
 	(10, 'level3-2b1b', 6);

查询


 	-- 查询跟节点下的所有节点
 	SELECT t1.name AS lev1, t2.name as lev2, t3.name as lev3
 	FROM menu AS t1
 	LEFT JOIN menu AS t2 ON t2.parent_id = t1.id
 	LEFT JOIN menu AS t3 ON t3.parent_id = t2.id
 	WHERE t1.name = 'level1a';
 	 
 	+---------+------------+-------------+
 	| lev1 | lev2 | lev3 |
 	+---------+------------+-------------+
 	| level1a | level2a-1a | level3-2a1a |
 	| level1a | level2b-1a | level3-2b1a |
 	+---------+------------+-------------+
 	 
 	-- 查询叶子节点
 	SELECT t1.name FROM
 	menu AS t1 LEFT JOIN menu as t2
 	ON t1.id = t2.parent_id
 	WHERE t2.id IS NULL;
 	 
 	+-------------+
 	| name |
 	+-------------+
 	| level3-2a1a |
 	| level3-2b1a |
 	| level3-2a1b |
 	| level3-2b1b |
 	+-------------+

存储及修改上比较方便,就是要在sql里头查询树比较费劲,一般是加载到内存由应用自己构造

存储path

这种方式在存储parent的基础上,额外存储path,即从根节点到该节点的路径

建表及数据准备


 	CREATE TABLE `menu_path` (
 	     `id` int(11) NOT NULL AUTO_INCREMENT,
 	     `name` varchar(50) NOT NULL,
 	     `parent_id` int(11) NOT NULL DEFAULT '0',
 	     `path` varchar(255) NOT NULL DEFAULT '',
 	     PRIMARY KEY (`id`)
 	) ENGINE=InnoDB;
 	 
 	INSERT INTO `menu_path` (`id`, `name`, `parent_id`, `path`) VALUES
 	(1, 'level1a', 0, '1/'),
 	(2, 'level1b', 0, '2/'),
 	(3, 'level2a-1a',1, '1/3'),
 	(4, 'level2b-1a',1, '1/4'),
 	(5, 'level2a-1b', 2, '2/5'),
 	(6, 'level2b-1b', 2, '2/6'),
 	(7, 'level3-2a1a', 3, '1/3/7'),
 	(8, 'level3-2b1a', 4, '1/4/8'),
 	(9, 'level3-2a1b', 5, '2/5/9'),
 	(10, 'level3-2b1b', 6, '2/6/10');

查询


 	-- 查询某个节点的所有子节点
 	select * from menu_path where path like '1/%'
 	+----+-------------+-----------+-------+
 	| id | name | parent_id | path |
 	+----+-------------+-----------+-------+
 	| 1 | level1a | 0 | 1/ |
 	| 3 | level2a-1a | 1 | 1/3 |
 	| 4 | level2b-1a | 1 | 1/4 |
 	| 7 | level3-2a1a | 3 | 1/3/7 |
 	| 8 | level3-2b1a | 4 | 1/4/8 |
 	+----+-------------+-----------+-------+

查找某个节点及其子节点比较方面,就是修改比较费劲,特别是节点移动,所有子节点的path都得跟着修改

MPTT(Modified Preorder Tree Traversal)

详细聊一聊mysql的树形结构存储以及查询插图

不存储parent_id,改为存储lft,rgt,它们的值由树的先序遍历顺序决定

建表及数据准备


 	CREATE TABLE `menu_preorder` (
 	     `id` int(11) NOT NULL,
 	     `name` varchar(50) NOT NULL,
 	     `lft` int(11) NOT NULL DEFAULT '0',
 	     `rgt` int(11) NOT NULL DEFAULT '0',
 	     PRIMARY KEY (`id`)
 	) ENGINE=InnoDB;
 	 
 	                     1(level1a)14
 	             2(level2a)7 8(level2b)13
 	3(level3a-2a)4 5(level3b-2a)6 9(level3c-2b)10 11(level3d-2b)12
 	 
 	INSERT INTO `menu_preorder` (`id`, `name`, `lft`, `rgt`) VALUES
 	(1, 'level1a', 1, 14),
 	(2, 'level2a',2, 7),
 	(3, 'level2b',8, 13),
 	(4, 'level3a-2a', 3, 4),
 	(5, 'level3b-2a', 5, 6),
 	(6, 'level3c-2b', 9, 10),
 	(7, 'level3d-2b', 11, 12);
 	 
 	select * from menu_preorder
 	+----+------------+-----+-----+
 	| id | name | lft | rgt |
 	+----+------------+-----+-----+
 	| 1 | level1a | 1 | 14 |
 	| 2 | level2a | 2 | 7 |
 	| 3 | level2b | 8 | 13 |
 	| 4 | level3a-2a | 3 | 4 |
 	| 5 | level3b-2a | 5 | 6 |
 	| 6 | level3c-2b | 9 | 10 |
 	| 7 | level3d-2b | 11 | 12 |
 	+----+------------+-----+-----+

查询


 	-- 查询某个节点及其子节点,比如level2b
 	select * from menu_preorder where lft between 8 and 13
 	+----+------------+-----+-----+
 	| id | name | lft | rgt |
 	+----+------------+-----+-----+
 	| 3 | level2b | 8 | 13 |
 	| 6 | level3c-2b | 9 | 10 |
 	| 7 | level3d-2b | 11 | 12 |
 	+----+------------+-----+-----+
 	 
 	-- 查询所有叶子节点
 	SELECT name
 	FROM menu_preorder
 	WHERE rgt = lft + 1;
 	 
 	+------------+
 	| name |
 	+------------+
 	| level3a-2a |
 	| level3b-2a |
 	| level3c-2b |
 	| level3d-2b |
 	+------------+
 	 
 	-- 查询某个节点及其父节点
 	SELECT parent.*
 	FROM menu_preorder AS node,
 	menu_preorder AS parent
 	WHERE node.lft BETWEEN parent.lft AND parent.rgt
 	AND node.name = 'level2b'
 	ORDER BY parent.lft;
 	 
 	+----+---------+-----+-----+
 	| id | name | lft | rgt |
 	+----+---------+-----+-----+
 	| 1 | level1a | 1 | 14 |
 	| 3 | level2b | 8 | 13 |
 	+----+---------+-----+-----+
 	 
 	-- 树形结构展示
 	SELECT CONCAT( REPEAT(' ', COUNT(parent.name) - 1), node.name) AS name
 	FROM menu_preorder AS node,
 	menu_preorder AS parent
 	WHERE node.lft BETWEEN parent.lft AND parent.rgt
 	GROUP BY node.name
 	ORDER BY node.lft;
 	 
 	+--------------+
 	| name |
 	+--------------+
 	| level1a |
 	| level2a |
 	| level3a-2a |
 	| level3b-2a |
 	| level2b |
 	| level3c-2b |
 	| level3d-2b |
 	+--------------+

好处是通过lft进行范围(该节点的lft,rgt作为范围)查找就可以,缺点就是增删节点导致很多节点的lft及rgt都要修改

小结

存储parent的方式最为场景,一般树形结构数据量不大的话,直接在应用层内存构造树形结构和搜索
存储path的好处是可以借助path来查找节点及其子节点,缺点就是移动node需要级联所有子节点的path,比较费劲
MPTT的方式好处是通过lft进行范围(该节点的lft,rgt作为范围)查找就可以,缺点就是增删节点导致很多节点的lft及rgt都要修改

doc

Managing Hierarchical Data in MySQL
hierarchical-data-database
hierarchical-data-database-2
hierarchical-data-database-3

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