我需要您帮助优化查询。一个表是一个日志表，其中有数百万个条目，我尝试将查询时间缩短到 < 1 秒。我的查询应该给出总体概述，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的查询。但是脚本能做什么，我想 mysql 也能做——至少我希望如此。也许并非所有部分都最好使用，但我陷入了一个生成临时表和文件排序的查询(我发现这非常糟糕)。在阅读周围的内容时，我发现可以使用一些整洁且位置良好的索引，但现在我陷入了一个特定的点。
让我向您展示我的最终查询及其结果:
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;
这是我得到的:
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)
这是我当前的表格设置:
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)
以下是逐步打破我的查询的时间结果。在花了这么长时间修复每个部分后，我可能会一步一步地进行。但目前只有运行时间为 2.30 秒的查询对这个问题感兴趣。
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)
通过为 (SERVER_ID, ID_TYPE) 定义索引，我能够极大地改进查询，正如我的以下示例查询所证实的那样:
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)
我现在陷入了最崩溃的查询，执行时间长达 2.30 秒。我不知道如何在没有任何 where 子句的查询中使用索引。
最佳答案
在 PAR_MONITORINGv2_LOG(CREATED_DATE, SERVER_ID,ID_TYPE) 上添加复合索引肯定会让您的查询受益匪浅。不过，我建议即使是 CREATED_DATE 上的简单索引也会大大提高性能。
关于MySQL查询优化，大表，使用临时文件排序，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/14162846/