从MySQL中的分层数据生成基于深度的树(无CTE) [英] Generating Depth based tree from Hierarchical Data in MySQL (no CTEs)
问题描述
好几天以来，我一直在MySQL中解决这个问题，但是我无法弄清楚.你们有什么建议吗?
Hi For many days I have been working on this problem in MySQL, however I can not figure it out. Do any of you have suggestions?
基本上，我有一个类别表，其域如下:id，name(类别名称)和parent(类别父级的ID).
Basically, I have a category table with domains like: id, name (name of category), and parent (id of parent of the category).
示例数据:
1 Fruit 0
2 Apple 1
3 pear 1
4 FujiApple 2
5 AusApple 2
6 SydneyAPPLE 5
....
有许多级别，可能超过3个级别.我想创建一个根据层次结构将数据分组的sql查询:父级>子级>孙子级>等.
There are many levels, possibly more than 3 levels. I want to create an sql query that groups the datas according to he hierarchy: parent > child > grandchild > etc.
它应该输出树形结构，如下所示:
It should output the tree structure, as follows:
1 Fruit 0
^ 2 Apple 1
^ 4 FujiApple 2
- 5 AusApple 2
^ 6 SydneyApple 5
- 3 pear 1
我可以使用单个SQL查询来执行此操作吗?我尝试并确实起作用的替代方法如下:
Can I do this using a single SQL query? The alternative, which I tried and does work, is the following:
SELECT * FROM category WHERE parent=0
此后，我再次遍历数据，并选择parent = id所在的行.这似乎是一个不好的解决方案.因为是mySQL，所以不能使用CTE.
After this, I loop through the data again, and select the rows where parent=id. This seems like a bad solution. Because it is mySQL, CTEs cannot be used.
推荐答案
如果使用存储过程，则可以在从php到mysql的单个调用中完成此操作:
You can do it in a single call from php to mysql if you use a stored procedure:
mysql> call category_hier(1);
+--------+---------------+---------------+----------------------+-------+
| cat_id | category_name | parent_cat_id | parent_category_name | depth |
+--------+---------------+---------------+----------------------+-------+
| 1 | Location | NULL | NULL | 0 |
| 3 | USA | 1 | Location | 1 |
| 4 | Illinois | 3 | USA | 2 |
| 5 | Chicago | 3 | USA | 2 |
+--------+---------------+---------------+----------------------+-------+
4 rows in set (0.00 sec)
$sql = sprintf("call category_hier(%d)", $id);
希望这会有所帮助:)
drop table if exists categories;
create table categories
(
cat_id smallint unsigned not null auto_increment primary key,
name varchar(255) not null,
parent_cat_id smallint unsigned null,
key (parent_cat_id)
)
engine = innodb;
测试数据:
insert into categories (name, parent_cat_id) values
('Location',null),
('USA',1),
('Illinois',2),
('Chicago',2),
('Color',null),
('Black',3),
('Red',3);
程序:
drop procedure if exists category_hier;
delimiter #
create procedure category_hier
(
in p_cat_id smallint unsigned
)
begin
declare v_done tinyint unsigned default 0;
declare v_depth smallint unsigned default 0;
create temporary table hier(
parent_cat_id smallint unsigned,
cat_id smallint unsigned,
depth smallint unsigned default 0
)engine = memory;
insert into hier select parent_cat_id, cat_id, v_depth from categories where cat_id = p_cat_id;
/* http://dev.mysql.com/doc/refman/5.0/en/temporary-table-problems.html */
create temporary table tmp engine=memory select * from hier;
while not v_done do
if exists( select 1 from categories p inner join hier on p.parent_cat_id = hier.cat_id and hier.depth = v_depth) then
insert into hier
select p.parent_cat_id, p.cat_id, v_depth + 1 from categories p
inner join tmp on p.parent_cat_id = tmp.cat_id and tmp.depth = v_depth;
set v_depth = v_depth + 1;
truncate table tmp;
insert into tmp select * from hier where depth = v_depth;
else
set v_done = 1;
end if;
end while;
select
p.cat_id,
p.name as category_name,
b.cat_id as parent_cat_id,
b.name as parent_category_name,
hier.depth
from
hier
inner join categories p on hier.cat_id = p.cat_id
left outer join categories b on hier.parent_cat_id = b.cat_id
order by
hier.depth, hier.cat_id;
drop temporary table if exists hier;
drop temporary table if exists tmp;
end #
测试运行:
delimiter ;
call category_hier(1);
call category_hier(2);
使用Yahoo geoplanet放置数据的某些性能测试
drop table if exists geoplanet_places;
create table geoplanet_places
(
woe_id int unsigned not null,
iso_code varchar(3) not null,
name varchar(255) not null,
lang varchar(8) not null,
place_type varchar(32) not null,
parent_woe_id int unsigned not null,
primary key (woe_id),
key (parent_woe_id)
)
engine=innodb;
mysql> select count(*) from geoplanet_places;
+----------+
| count(*) |
+----------+
| 5653967 |
+----------+
所以表中有560万行(位置)，让我们看看从php调用的邻接表实现/存储过程是如何处理的.
so that's 5.6 million rows (places) in the table let's see how the adjacency list implementation/stored procedure called from php handles that.
1 records fetched with max depth 0 in 0.001921 secs
250 records fetched with max depth 1 in 0.004883 secs
515 records fetched with max depth 1 in 0.006552 secs
822 records fetched with max depth 1 in 0.009568 secs
918 records fetched with max depth 1 in 0.009689 secs
1346 records fetched with max depth 1 in 0.040453 secs
5901 records fetched with max depth 2 in 0.219246 secs
6817 records fetched with max depth 1 in 0.152841 secs
8621 records fetched with max depth 3 in 0.096665 secs
18098 records fetched with max depth 3 in 0.580223 secs
238007 records fetched with max depth 4 in 2.003213 secs
总的来说，我对那些寒冷的运行时感到非常满意，因为我什至不会开始考虑将数万行数据返回到我的前端，而是宁愿动态地构建树，每次调用只获取几个级别.哦，以防万一您以为innodb的速度要比myisam慢-我测试过的myisam实现在所有方面的速度都快一倍.
Overall i'm pretty pleased with those cold runtimes as I wouldn't even begin to consider returning tens of thousands of rows of data to my front end but would rather build the tree dynamically fetching only several levels per call. Oh and just incase you were thinking innodb is slower than myisam - the myisam implementation I tested was twice as slow in all counts.
更多内容: http://pastie.org/1672733
希望这会有所帮助:)
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