MySQL - Recursing a tree structure
There's a good-looking article over at mysql.com outlining various ways of managing hierarchical data. I think it provides a full solution to your question, and shows various less simple, but faster approaches (e.g. Nested Sets).
Generating Depth based tree from Hierarchical Data in MySQL (no CTEs)
You can do it in a single call from php to mysql if you use a stored procedure:
Example calls
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);
Hope this helps :)
Full script
Test table structure:
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;
Test data:
insert into categories (name, parent_cat_id) values
('Location',null),
('USA',1),
('Illinois',2),
('Chicago',2),
('Color',null),
('Black',3),
('Red',3);
Procedure:
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 #
Test runs:
delimiter ;
call category_hier(1);
call category_hier(2);
Some performance testing using Yahoo geoplanet places data
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 |
+----------+
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
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.
More stuff here : http://pastie.org/1672733
Hope this helps :)
Mysql, functions for tree-structure
Copied from this popular link:
CREATE TABLE nested_category (
category_id INT AUTO_INCREMENT PRIMARY KEY,
name VARCHAR(20) NOT NULL,
lft INT NOT NULL,
rgt INT NOT NULL
);
INSERT INTO nested_category VALUES(1,'ELECTRONICS',1,20),(2,'TELEVISIONS',2,9),(3,'TUBE',3,4),
(4,'LCD',5,6),(5,'PLASMA',7,8),(6,'PORTABLE ELECTRONICS',10,19),(7,'MP3 PLAYERS',11,14),(8,'FLASH',12,13),
(9,'CD PLAYERS',15,16),(10,'2 WAY RADIOS',17,18);
SELECT * FROM nested_category ORDER BY category_id;
+-------------+----------------------+-----+-----+
| category_id | name | lft | rgt |
+-------------+----------------------+-----+-----+
| 1 | ELECTRONICS | 1 | 20 |
| 2 | TELEVISIONS | 2 | 9 |
| 3 | TUBE | 3 | 4 |
| 4 | LCD | 5 | 6 |
| 5 | PLASMA | 7 | 8 |
| 6 | PORTABLE ELECTRONICS | 10 | 19 |
| 7 | MP3 PLAYERS | 11 | 14 |
| 8 | FLASH | 12 | 13 |
| 9 | CD PLAYERS | 15 | 16 |
| 10 | 2 WAY RADIOS | 17 | 18 |
+-------------+----------------------+-----+-----+
You can use this to find all parents from node FLASH
:
Retrieving a Single Path
With the nested set model, we can retrieve a single path without
having multiple self-joins:
SELECT parent.name
FROM nested_category AS node,
nested_category AS parent
WHERE node.lft BETWEEN parent.lft AND parent.rgt
AND node.name = 'FLASH'
ORDER BY node.lft;
+----------------------+
| name |
+----------------------+
| ELECTRONICS |
| PORTABLE ELECTRONICS |
| MP3 PLAYERS |
| FLASH |
+----------------------+
This works because the child's left
will be in between its parents' left
and right
.
You can read further or search for modified preorder tree traversal.
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