我正在尝试优化mysql db中的sql查询。尝试了不同的重写方式,添加/删除索引,但似乎没有什么能减少负载。也许我错过了什么。 查询:
select co.country_name as state, ci.city_name as city, ci.city_id, ci.country_id,
count(l.id) as num
FROM cities ci
INNER JOIN countries co ON (ci.country_id = co.country_id)
INNER JOIN dancers l ON (l.city_id = ci.city_id AND l.closed = 0 AND l.approved = 1 )
WHERE 1 AND ci.main=1
GROUP BY ci.city_id
ORDER BY city
持续时间:2.01秒 - 2.20秒 优化查询:
select co.country_name as state, ci.city_name as city, ci.city_id, ci.country_id, count(l.id) as num from
(select ci1.city_name, ci1.city_id, ci1.country_id from cities ci1
where ci1.main=1) as ci
INNER JOIN countries co ON (ci.country_id = co.country_id)
INNER JOIN dancers l ON (l.city_id = ci.city_id AND l.closed = 0 AND l.approved = 1 ) GROUP BY ci.city_id ORDER BY city
持续时间:0.82秒 - 0.90秒
但是我觉得这个查询可以进一步优化但是没有让ideea如何优化它。有3个表
Table 1 : countries ( country_id, country_name)
Table 2 : cities ( city_id, city_name, main, country_id)
Table 3 : dancers ( id, country_id, city_id, closed, approved)
我正在努力让所有拥有main = 1的城市和每个城市都计算加入国家/地区的所有城市的个人资料以获取country_name。
欢迎任何想法,谢谢。
稍后编辑: - 第一次查询解释
+----+-------------+-------+-------------+---------------------------------------------------------------------+-----------------+---------+------------------+-------+--------------------------------------------------------------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+-------------+---------------------------------------------------------------------+-----------------+---------+------------------+-------+--------------------------------------------------------------------------------+
| 1 | SIMPLE | l | index_merge | city_id,closed,approved,city_id_2 | closed,approved | 1,2 | NULL | 75340 | Using intersect(closed,approved); Using where; Using temporary; Using filesort |
| 1 | SIMPLE | ci | eq_ref | PRIMARY,state_id_2,state_id,city_name,lat,city_name_shorter,city_id | PRIMARY | 4 | db.l.city_id | 1 | Using where |
| 1 | SIMPLE | co | eq_ref | PRIMARY | PRIMARY | 4 | db.ci.country_id | 1 | Using where |
+----+-------------+-------+-------------+---------------------------------------------------------------------+-----------------+---------+------------------+-------+--------------------------------------------------------------------------------+
第二个查询说明:
+----+-------------+------------+------+-----------------------------------+-------------+---------+------------------+-------+------------------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+------------+------+-----------------------------------+-------------+---------+------------------+-------+------------------------------------+
| 1 | PRIMARY | co | ALL | PRIMARY | NULL | NULL | NULL | 51 | Using temporary; Using filesort |
| 1 | PRIMARY | <derived2> | ref | <auto_key1> | <auto_key1> | 4 | db.co.country_id | 176 | Using where |
| 1 | PRIMARY | l | ref | city_id,closed,approved,city_id_2 | city_id_2 | 4 | ci.city_id | 44 | Using index condition; Using where |
| 2 | DERIVED | ci1 | ALL | NULL | NULL | NULL | NULL | 11765 | Using where |
+----+-------------+------------+------+-----------------------------------+-------------+---------+------------------+-------+------------------------------------+
@used_by_already查询说明:
+----+-------------+------------+-------------+-----------------------------------+-----------------+---------+------------------+-------+--------------------------------------------------------------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+------------+-------------+-----------------------------------+-----------------+---------+------------------+-------+--------------------------------------------------------------------------------+
| 1 | PRIMARY | co | ALL | PRIMARY | NULL | NULL | NULL | 51 | NULL |
| 1 | PRIMARY | <derived2> | ref | <auto_key0> | <auto_key0> | 4 | db.co.country_id | 565 | Using where |
| 2 | DERIVED | l | index_merge | city_id,closed,approved,city_id_2 | closed,approved | 1,2 | NULL | 75341 | Using intersect(closed,approved); Using where; Using temporary; Using filesort |
| 2 | DERIVED | ci1 | eq_ref | PRIMARY,state_id_2,city_id | PRIMARY | 4 | db.l.city_id | 1 | Using where |
+----+-------------+------------+-------------+-----------------------------------+-----------------+---------+------------------+-------+--------------------------------------------------------------------------------+
答案 0 :(得分:1)
我建议你试试这个:
SELECT
co.country_name AS state
, ci.city_name AS city
, ci.city_id
, ci.country_id
, ci.num
FROM (
SELECT
ci1.city_id
, ci1.city_name
, ci1.country_id
, COUNT(l.id) AS num
FROM cities ci1
INNER JOIN dancers l ON l.city_id = ci1.city_id
AND l.closed = 0
AND l.approved = 1
WHERE ci1.main = 1
GROUP BY
ci1.city_id
, ci1.city_name
, ci1.country_id
) AS ci
INNER JOIN countries co ON ci.country_id = co.country_id
;
如果需要,您可以提供解释计划输出以供进一步分析。在优化知道哪些索引存在并让他解释计划时,是必需品。
不是,MySQL确实允许非标准的GROUP BY语法(其中只有group by子句中包含选择列表中的一个或一些列)。 在最新版本的MySQL中,GROUP BY的默认行为已更改为SQL标准语法(其中选择列表中的所有“非聚合”列必须包含在group by子句下)。虽然现有查询使用非标准组语法,但此处提供的查询不符合。