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从MySQL中的分层数据生成基于深度的树(无CTE)

mysql

嗨,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?

基本上,我有一个类别表,其域如:idname(类别名称)和parent(类别的父代ID)。

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。

它应该输出树结构,如下所示:

1 Fruit 0
 ^ 2 Apple 1
   ^ 4 FujiApple 2
   - 5 AusApple 2
     ^ 6 SydneyApple 5
 - 3 pear 1

我可以使用一个SQL查询吗?我尝试并起作用的替代方法如下:

SELECT * FROM category WHERE parent=0

此后,我再次遍历数据,然后选择parent = id所在的行。这似乎是一个糟糕的解决方案。因为它是mySQL,所以不能使用CTE。


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2020-05-17

共1个答案

小编典典

如果使用存储过程,则可以在一次从php到mysql的调用中完成:

呼叫范例

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);

希望这可以帮助 :)

完整脚本

测试表结构:

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放置数据的一些性能测试

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。

     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比myisam慢-
我测试的myisam实现在所有方面都慢了一倍。

此处有更多内容:http :
//pastie.org/1672733

希望这可以帮助 :)

2020-05-17