MySQL查询优化，大表，使用临时filesort
问题描述：
我需要你的帮助，优化查询。一个表是一个有数百万条目的日志表，我试图将我的查询分解为< 1。我的查询应该给出一个全面的概述，因此应该很快。我确信我可以在脚本的帮助下对列表进行多个简单查询。但是，脚本可以做什么，我可以认为 - 我希望至少。也许并不是所有的部分都是最好的，但是我被困在一个使临时表和文件夹（我发现真的很糟糕）的查询中。随着阅读周围我发现使用一些整洁和良好的索引，但现在我卡在一个特定的点。MySQL查询优化，大表，使用临时filesort
让我告诉你它的结果我的最终查询：
SELECT
ps.SERVER_ID,
ps.FULLNAME,
SUM(CASE WHEN pml.ID_TYPE = 3 THEN 1 ELSE 0 END) 'amount_warning',
SUM(CASE WHEN pml.ID_TYPE = 4 THEN 1 ELSE 0 END) 'amount_error',
SUM(CASE WHEN pml.ID_TYPE = 5 THEN 1 ELSE 0 END) 'amount_alert',
SUM(CASE WHEN pml.ID_TYPE = 7 THEN 1 ELSE 0 END) 'amount_critical'
FROM
PAR_SERVER ps
INNER JOIN
PAR_MONITORINGv2_LOG pml ON ps.SERVER_ID = pml.SERVER_ID
WHERE
pml.CREATED_DATE > date_sub(NOW() , INTERVAL 7 DAY)
GROUP BY
ps.SERVER_ID;
这里是我所得到的：
mysql> [thequeryabove]
[...]
59 rows in set (11.69 sec)
mysql> explain [thequeryabove]
+----+-------------+-------+--------+-----------------------------+---------+---------+---------------------------+---------+----------------------------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+--------+-----------------------------+---------+---------+---------------------------+---------+----------------------------------------------+
| 1 | SIMPLE | pml | ALL | SERVER_ID,SERVER_ID-ID_TYPE | NULL | NULL | NULL | 4014447 | Using where; Using temporary; Using filesort |
| 1 | SIMPLE | ps | eq_ref | PRIMARY | PRIMARY | 4 | database.pml.SERVER_ID | 1 | |
+----+-------------+-------+--------+-----------------------------+---------+---------+---------------------------+---------+----------------------------------------------+
2 rows in set (0.00 sec)
这是我当前的表设置：
mysql> describe PAR_SERVER;
+----------------+--------------+------+-----+---------+----------------+
| Field | Type | Null | Key | Default | Extra |
+----------------+--------------+------+-----+---------+----------------+
| SERVER_ID | int(255) | NO | PRI | NULL | auto_increment |
| FULLNAME | varchar(255) | YES | | NULL | |
| SHORTNAME | varchar(255) | YES | MUL | NULL | |
+----------------+--------------+------+-----+---------+----------------+
3 rows in set (0.00 sec)
mysql> show indexes from PAR_SERVER;
+------------+------------+-----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+
| Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment |
+------------+------------+-----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+
| PAR_SERVER | 0 | PRIMARY | 1 | SERVER_ID | A | 142 | NULL | NULL | | BTREE | |
| PAR_SERVER | 1 | shortname | 1 | SHORTNAME | A | 142 | NULL | NULL | YES | BTREE | |
+------------+------------+-----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+
2 rows in set (0.00 sec)
mysql> select count(*) from PAR_SERVER;
+----------+
| count(*) |
+----------+
| 142 |
+----------+
1 row in set (0.00 sec)
mysql> describe PAR_MONITORINGv2_LOG;
+--------------+----------+------+-----+---------+----------------+
| Field | Type | Null | Key | Default | Extra |
+--------------+----------+------+-----+---------+----------------+
| ID | int(11) | NO | PRI | NULL | auto_increment |
| ID_TYPE | int(11) | NO | MUL | NULL | |
| ID_SERVICE | int(11) | NO | MUL | NULL | |
| SERVER_ID | int(11) | NO | MUL | NULL | |
| MESSAGE | tinytext | NO | | NULL | |
| CREATED_DATE | datetime | NO | | NULL | |
+--------------+----------+------+-----+---------+----------------+
6 rows in set (0.00 sec)
mysql> show indexes from PAR_MONITORINGv2_LOG;
+----------------------+------------+-------------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+
| Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment |
+----------------------+------------+-------------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+
| PAR_MONITORINGv2_LOG | 0 | PRIMARY | 1 | ID | A | 3998188 | NULL | NULL | | BTREE | |
| PAR_MONITORINGv2_LOG | 1 | ID_TYPE | 1 | ID_TYPE | A | 7 | NULL | NULL | | BTREE | |
| PAR_MONITORINGv2_LOG | 1 | ID_SERVICE | 1 | ID_SERVICE | A | 5 | NULL | NULL | | BTREE | |
| PAR_MONITORINGv2_LOG | 1 | SERVER_ID | 1 | SERVER_ID | A | 66 | NULL | NULL | | BTREE | |
| PAR_MONITORINGv2_LOG | 1 | SERVER_ID-ID_TYPE | 1 | SERVER_ID | A | 66 | NULL | NULL | | BTREE | |
| PAR_MONITORINGv2_LOG | 1 | SERVER_ID-ID_TYPE | 2 | ID_TYPE | A | 258 | NULL | NULL | | BTREE | |
+----------------------+------------+-------------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+
6 rows in set (0.00 sec)
mysql> select count(*) from PAR_MONITORINGv2_LOG;
+----------+
| count(*) |
+----------+
| 3998386 |
+----------+
1 row in set (0.00 sec)
这里有时间结果一步一步打破我的查询。固定每个部分花费这么长时间后，我可能会逐步加深。但是现在只有运行时间为2.30秒的查询目前对这个问题很有意思。
mysql> SELECT ps.SERVER_ID, ps.FULLNAME FROM PAR_SERVER ps INNER JOIN PAR_MONITORINGv2_LOG pml ON ps.SERVER_ID = pml.SERVER_ID WHERE pml.CREATED_DATE > date_sub(NOW() , INTERVAL 7 DAY) GROUP BY ps.SERVER_ID;
[...]
59 rows in set (6.41 sec)
mysql> explain [thequeryabove]
+----+-------------+-------+--------+-----------------------------+---------+---------+---------------------------+---------+----------------------------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+--------+-----------------------------+---------+---------+---------------------------+---------+----------------------------------------------+
| 1 | SIMPLE | pml | ALL | SERVER_ID,SERVER_ID-ID_TYPE | NULL | NULL | NULL | 4014788 | Using where; Using temporary; Using filesort |
| 1 | SIMPLE | ps | eq_ref | PRIMARY | PRIMARY | 4 | database.pml.SERVER_ID | 1 | |
+----+-------------+-------+--------+-----------------------------+---------+---------+---------------------------+---------+----------------------------------------------+
2 rows in set (0.00 sec)
mysql> SELECT ps.SERVER_ID, ps.FULLNAME FROM PAR_SERVER ps INNER JOIN PAR_MONITORINGv2_LOG pml ON ps.SERVER_ID = pml.SERVER_ID GROUP BY ps.SERVER_ID;
[...]
59 rows in set (2.30 sec)
mysql> explain [thequeryabove]
+----+-------------+-------+--------+-----------------------------+-----------+---------+---------------------------+---------+----------------------------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+--------+-----------------------------+-----------+---------+---------------------------+---------+----------------------------------------------+
| 1 | SIMPLE | pml | index | SERVER_ID,SERVER_ID-ID_TYPE | SERVER_ID | 4 | NULL | 4015694 | Using index; Using temporary; Using filesort |
| 1 | SIMPLE | ps | eq_ref | PRIMARY | PRIMARY | 4 | database.pml.SERVER_ID | 1 | |
+----+-------------+-------+--------+-----------------------------+-----------+---------+---------------------------+---------+----------------------------------------------+
2 rows in set (0.00 sec)
mysql> SELECT pml.SERVER_ID FROM PAR_MONITORINGv2_LOG pml GROUP BY pml.SERVER_ID;
[...]
65 rows in set (0.00 sec)
mysql> explain [thequeryabove]
+----+-------------+-------+-------+---------------+-----------+---------+------+------+--------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+-------+---------------+-----------+---------+------+------+--------------------------+
| 1 | SIMPLE | pml | range | NULL | SERVER_ID | 4 | NULL | 67 | Using index for group-by |
+----+-------------+-------+-------+---------------+-----------+---------+------+------+--------------------------+
1 row in set (0.00 sec)
我能够通过定义（SERVER_ID，ID_TYPE）指数为我下面的例子查询来提高查询了很多证实：
mysql> SELECT count(*) 'count_warnings' FROM PAR_MONITORINGv2_LOG pml WHERE pml.SERVER_ID = 191 AND pml.ID_TYPE = 3 GROUP BY pml.SERVER_ID;
[...]
1 row in set (0.01 sec)
mysql> explain [thequeryabove]
+----+-------------+-------+------+-------------------------------------+-------------------+---------+-------------+-------+-------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+------+-------------------------------------+-------------------+---------+-------------+-------+-------------+
| 1 | SIMPLE | pml | ref | ID_TYPE,SERVER_ID,SERVER_ID-ID_TYPE | SERVER_ID-ID_TYPE | 8 | const,const | 10254 | Using index |
+----+-------------+-------+------+-------------------------------------+-------------------+---------+-------------+-------+-------------+
1 row in set (0.00 sec)
我现在被困在最broked下来查询的执行时间很长，为2.30秒。我不知道如何使用没有任何where子句的查询的索引。
答
您的查询一定会从PAR_MONITORINGv2_LOG（CREATED_DATE，SERVER_ID，ID_TYPE）加入综合指数受益最大。不过，我建议即使是简单的索引CREATED_DATE也会提高性能很多。
A'使用filesort'不一定是“非常糟糕”;但对于大型设备，排序操作可能会对性能产生重大影响。有时，当适当的索引可用时，MySQL可以避免排序操作。可以使用覆盖索引的访问计划（'使用索引'）通常会提高性能。 – spencer7593