Mysql: Optimizing finding super node in nested set tree

Question

I have hierarchical data in a nested set model (table:projects):

My table (projects):

id, lft, rgt
1, 1, 6
2, 2, 3
3, 4, 5
4, 7, 10
5, 8, 9
6, 11, 12
7, 13, 14
...

Pretty printed:

 1
  2
  3
 4
  5
 6
 7

To find the nearest super node of node 3 (knowing its lft value), i can do

explain
SELECT projects.*
FROM projects
WHERE 4 BETWEEN projects.lft AND projects.rgt

Which gives me a list of the projects in the path down to node 3. Then by grouping and finding MAX(projects.lft) of the results, i get the nearest super node. However, I cannot seem to get this query to run fast, it wont use the indexes i've defined. EXPLAIN says:

+----+-------------+----------+-------+----------------+----------+---------+------+------+--------------------------+
| id | select_type | table    | type  | possible_keys  | key      | key_len | ref  | rows | Extra                    |
+----+-------------+----------+-------+----------------+----------+---------+------+------+--------------------------+
|  1 | SIMPLE      | projects | index | lft,rgt,lftRgt | idLftRgt | 12      | NULL |   10 | Using where; Using index | 
+----+-------------+----------+-------+----------------+----------+---------+------+------+--------------------------+

Mysql understands what index to use, but still has to loop through all 10 rows (or 100k in my actual table).

How can i get MySql to optimize this query properly? I include a test script beneath.

DROP TABLE IF EXISTS projects; 
CREATE TABLE projects (
    id INT NOT NULL ,
    lft INT NOT NULL ,
    rgt INT NOT NULL ,
    PRIMARY KEY ( id )
) ENGINE = MYISAM ;
ALTER TABLE projects ADD INDEX lft (lft);
ALTER TABLE projects ADD INDEX rgt (rgt);
ALTER TABLE projects ADD INDEX lftRgt (lft, rgt);
ALTER TABLE projects ADD INDEX idLftRgt (id, lft, rgt);

INSERT INTO projects (id,lft,rgt) VALUES (1,1,6);
INSERT INTO projects (id,lft,rgt) VALUES (2,2,3);
INSERT INTO projects (id,lft,rgt) VALUES (3,4,5);
INSERT INTO projects (id,lft,rgt) VALUES (4,7,10);
INSERT INTO projects (id,lft,rgt) VALUES (5,8,9);
INSERT INTO projects (id,lft,rgt) VALUES (6,11,12);
INSERT INTO projects (id,lft,rgt) VALUES (7,13,14);
INSERT INTO projects (id,lft,rgt) VALUES (8,15,16);
INSERT INTO projects (id,lft,rgt) VALUES (9,17,18);
INSERT INTO projects (id,lft,rgt) VALUES (10,19,20);

explain
SELECT projects.*
FROM projects
WHERE 4 BETWEEN projects.lft AND projects.rgt

Answer 1

To optimize nested set queries in MySQL, you should create a SPATIAL (R-Tree) index on the set boxes:

ALTER TABLE projects ADD sets LINESTRING;

UPDATE  projects
SET     sets = LineString(Point(-1, lft), Point(1, rgt));

ALTER TABLE projects MODIFY sets LINESTRING NOT NULL;

CREATE SPATIAL INDEX sx_projects_sets ON projects (sets);

SELECT  hp.*
FROM    projects hp
WHERE   MBRWithin(Point(0, 4), hp.sets)
ORDER BY
        lft;

See this article in my blog for more detail:

• Adjacency list vs. nested sets: MySQL

Answer 2

If you can't use the spatial index, then these two indexes:

ALTER TABLE projects ADD INDEX lftRgt (lft, rgt);
ALTER TABLE projects ADD INDEX idLftRgt (id, lft, rgt);

Should be unique. That will help the database a lot.

ALTER TABLE projects ADD INDEX lft (lft);

Is not necessary - it's a duplicate of lftRgt.

Answer 3

Came across this while trying to find help on indexing for nested sets.

I landed up with a different solution, which is bulky but easily fully indexed. However it will make updates even slower. However I am posting it here as it might help others.

We have a table of product categories, which can have sub categories, etc. This data is quite static.

I set up a table caching the relationships between categories containing the category and a row for each parent category (including this particular category), along with the difference in depth.

When a change is made to the actual category table I just trigger a procedure to rebuild the cached table.

Then anything that is checking for the parent / child relationship can just use the cache to link directly between a category and all its children (or a child and all its parents).

The actual category table.

CREATE TABLE `category` (
  `id` int(11) NOT NULL AUTO_INCREMENT,
  `name` varchar(128) NOT NULL,
  `depth` int(11) NOT NULL,
  `left_index` int(4) NOT NULL,
  `right_index` int(4) NOT NULL,
  `mmg_code` varchar(30) NOT NULL
  PRIMARY KEY (`id`),
  UNIQUE KEY `mmg_code` (`mmg_code`),
  UNIQUE KEY `left_index_right_index` (`left_index`,`right_index`),
  UNIQUE KEY `depth_left_index_right_index` (`depth`,`left_index`,`right_index`)
) ENGINE=InnoDB DEFAULT CHARSET=latin1;


DELIMITER ;;

CREATE TRIGGER `category_ai` AFTER INSERT ON `category` FOR EACH ROW
CALL `proc_rebuild_category_parents_cache`();;

CREATE TRIGGER `category_au` AFTER UPDATE ON `category` FOR EACH ROW
CALL `proc_rebuild_category_parents_cache`();;

DELIMITER ;

The simple cache table:-

CREATE TABLE `category_parents_cache` (
  `id` int(11) NOT NULL AUTO_INCREMENT,
  `category_id` int(11) NOT NULL,
  `parent_category_id` int(11) NOT NULL,
  `depth_difference` int(11) NOT NULL,
  PRIMARY KEY (`id`),
  KEY `category_id` (`category_id`),
  KEY `parent_category_id` (`parent_category_id`)
) ENGINE=InnoDB DEFAULT CHARSET=latin1;

The procedure:-

BEGIN
    TRUNCATE category_parents_cache;

    INSERT INTO category_parents_cache (id, category_id, parent_category_id, depth_difference)
    SELECT NULL, 
            child_category.id AS category_id, 
            category.id AS parent_category_id, 
            child_category.depth - category.depth AS depth_difference 
    FROM category
    INNER JOIN category child_category ON child_category.left_index BETWEEN category.left_index AND category.right_index
    ORDER BY category.id, child_category.id;
END

This could probably be usefully improved if the table is large and commonly updated.