我目前正在尝试优化MySQL查询,该查询在10,000行以上的表上运行速度有点慢。
CREATE TABLE IF NOT EXISTS `person` (
`_id` int(11) unsigned NOT NULL AUTO_INCREMENT,
`_oid` char(8) NOT NULL,
`firstname` varchar(255) NOT NULL,
`lastname` varchar(255) NOT NULL,
PRIMARY KEY (`_id`),
KEY `_oid` (`_oid`)
) ENGINE=MyISAM DEFAULT CHARSET=utf8;
CREATE TABLE IF NOT EXISTS `person_cars` (
`_id` int(11) NOT NULL AUTO_INCREMENT,
`_oid` char(8) NOT NULL,
`idx` varchar(255) NOT NULL,
`val` blob NOT NULL,
PRIMARY KEY (`_id`),
KEY `_oid` (`_oid`),
KEY `idx` (`idx`),
KEY `val` (`val`(64))
) ENGINE=MyISAM DEFAULT CHARSET=utf8;
# Insert some 10000+ rows…
INSERT INTO `person` (`_oid`,`firstname`,`lastname`)
VALUES
('1', 'John', 'Doe'),
('2', 'Jack', 'Black'),
('3', 'Jim', 'Kirk'),
('4', 'Forrest', 'Gump');
INSERT INTO `person_cars` (`_oid`,`idx`,`val`)
VALUES
('1', '0', 'BMW'),
('1', '1', 'PORSCHE'),
('2', '0', 'BMW'),
('3', '1', 'MERCEDES'),
('3', '0', 'TOYOTA'),
('3', '1', 'NISSAN'),
('4', '0', 'OLDMOBILE');
SELECT `_person`.`_oid`,
`_person`.`firstname`,
`_person`.`lastname`,
`_person_cars`.`cars[0]`,
`_person_cars`.`cars[1]`
FROM `person` `_person`
LEFT JOIN (
SELECT `_person`.`_oid`,
IFNULL(GROUP_CONCAT(IF(`_person_cars`.`idx`=0, `_person_cars`.`val`, NULL)), NULL) AS `cars[0]`,
IFNULL(GROUP_CONCAT(IF(`_person_cars`.`idx`=1, `_person_cars`.`val`, NULL)), NULL) AS `cars[1]`
FROM `person` `_person`
JOIN `person_cars` `_person_cars` ON `_person`.`_oid` = `_person_cars`.`_oid`
GROUP BY `_person`.`_oid`
) `_person_cars` ON `_person_cars`.`_oid` = `_person`.`_oid`
WHERE `cars[0]` = 'BMW' OR `cars[1]` = 'BMW';
上面的SELECT查询在运行MySQL 5.1.53的虚拟机上需要大约170ms。大约两个表中每个表中有10,000行。
当我解释上述查询时,结果会因每个表中的行数而异:
+----+-------------+--------------+-------+---------------+------+---------+------+------+---------------------------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+--------------+-------+---------------+------+---------+------+------+---------------------------------------------+
| 1 | PRIMARY | <derived2> | ALL | NULL | NULL | NULL | NULL | 4 | Using where |
| 1 | PRIMARY | _person | ALL | _oid | NULL | NULL | NULL | 4 | Using where; Using join buffer |
| 2 | DERIVED | _person_cars | ALL | _oid | NULL | NULL | NULL | 7 | Using temporary; Using filesort |
| 2 | DERIVED | _person | index | _oid | _oid | 24 | NULL | 4 | Using where; Using index; Using join buffer |
+----+-------------+--------------+-------+---------------+------+---------+------+------+---------------------------------------------+
大约10,000行给出以下结果:
+----+-------------+--------------+------+---------------+------+---------+------------------------+------+---------------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+--------------+------+---------------+------+---------+------------------------+------+---------------------------------+
| 1 | PRIMARY | <derived2> | ALL | NULL | NULL | NULL | NULL | 6613 | Using where |
| 1 | PRIMARY | _person | ref | _oid | _oid | 24 | _person_cars._oid | 10 | |
| 2 | DERIVED | _person_cars | ALL | _oid | NULL | NULL | NULL | 9913 | Using temporary; Using filesort |
| 2 | DERIVED | _person | ref | _oid | _oid | 24 | test._person_cars._oid | 10 | Using index |
+----+-------------+--------------+------+---------------+------+---------+------------------------+------+---------------------------------+
当我省略WHERE子句或者LEFT JOIN另一个类似于person_cars
的表时,事情变得更糟。
有没有人知道如何优化SELECT查询以使事情更快一点?
答案 0 :(得分:1)
这很慢,因为这会强制对人进行三次全表扫描,然后将它们连接在一起:
LEFT JOIN (
...
GROUP BY `_person`.`_oid` -- the group by here
) `_person_cars` ...
WHERE ... -- and the where clauses on _person_cars.
考虑到where子句,左连接实际上是一个内部连接。并且你可以在实际发生的人加入之前推动条件。这种联接也不必要地应用了两次。
这会使它更快,但是如果你有一个by / limit子句,那么由于子查询中的group by,它仍会导致对人进行全表扫描(即仍然不好):
JOIN (
SELECT `_person_cars`.`_oid`,
IFNULL(GROUP_CONCAT(IF(`_person_cars`.`idx`=0, `_person_cars`.`val`, NULL)), NULL) AS `cars[0]`,
IFNULL(GROUP_CONCAT(IF(`_person_cars`.`idx`=1, `_person_cars`.`val`, NULL)), NULL) AS `cars[1]`
FROM `person_cars`
GROUP BY `_person_cars`.`_oid`
HAVING IFNULL(GROUP_CONCAT(IF(`_person_cars`.`idx`=0, `_person_cars`.`val`, NULL)), NULL) = 'BMW' OR
IFNULL(GROUP_CONCAT(IF(`_person_cars`.`idx`=1, `_person_cars`.`val`, NULL)), NULL) = 'BMW'
) `_person_cars` ... -- smaller number of rows
如果您通过/ limit应用订单,您将通过两个查询获得更好的结果,即:
SELECT `_person`.`_oid`,
`_person`.`firstname`,
`_person`.`lastname`
FROM `_person`
JOIN `_person_cars`
ON `_person_cars`.`_oid` = `_person`.`_oid`
AND `_person_cars`.`val` = 'BMW'
GROUP BY -- pre-sort the result before grouping, so as to not do the work twice
`_person`.`lastname`,
`_person`.`firstname`,
-- eliminate users with multiple BMWs
`_person`.`_oid`
ORDER BY `_person`.`lastname`,
`_person`.`firstname`,
`_person`.`_oid`
LIMIT 10
然后使用生成的ID选择带有IN()子句的汽车。
哦,您的vals
列可能应该是varchar。
答案 1 :(得分:0)
检查此
SELECT
p._oid AS oid,
p.firstname AS firstname,
p.lastname AS lastname,
pc.val AS car1,
pc2.val AS car2
FROM person AS p
LEFT JOIN person_cars AS pc
ON pc._oid = p._oid
AND pc.idx = 0
LEFT JOIN person_cars AS pc2
ON pc2._oid = p._oid
AND pc2.idx = 1
WHERE pc.val = 'BMW'
OR pc2.val = 'BWM'