我有一个名为 Lead_history 的表，当我从中计算平均值时，查询花费了超过一分半钟的时间。该查询正在解析大约 15k 行。我已经根据下面的查询添加了索引，但似乎仍然需要很长时间。任何帮助将不胜感激。
SELECT AVG(TIMEDIFF(tq.ts, tv.ts)) / 60 avg_time_to_quote
FROM lead_history tv
JOIN lead_history tq
ON tv.agency_id = tq.agency_id
WHERE tv.new_status = 'Verified'
AND tq.new_status = 'Quoted'
AND tv.agency_id = '$agency_id'
AND tv.ts > DATE_SUB(NOW(), INTERVAL 30 DAY)
AND tq.ts > DATE_SUB(NOW(), INTERVAL 30 DAY)
GROUP
BY tv.agency_id
, tq.agency_id
表结构
show create table lead_history;
+--------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| Table | Create Table |
+--------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| lead_history | CREATE TABLE `lead_history` (
`id` int(11) NOT NULL AUTO_INCREMENT,
`agency_id` varchar(255) NOT NULL,
`old_status` varchar(64) DEFAULT NULL,
`new_status` varchar(64) DEFAULT NULL,
`ts` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
`contact_id` varchar(255) NOT NULL DEFAULT '',
`alter_type` varchar(255) NOT NULL DEFAULT '',
`last_mod_by` varchar(64) DEFAULT NULL,
PRIMARY KEY (`id`),
KEY `avg_index` (`old_status`,`new_status`,`agency_id`,`ts`)
) ENGINE=InnoDB AUTO_INCREMENT=14041 DEFAULT CHARSET=latin1 |
+--------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
1 row in set (0.00 sec)
索引
mysql> show indexes from lead_history;
+--------------+------------+-----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
| Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment | Index_comment |
+--------------+------------+-----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
| lead_history | 0 | PRIMARY | 1 | id | A | 13922 | NULL | NULL | | BTREE | | |
| lead_history | 1 | avg_index | 1 | old_status | A | 18 | NULL | NULL | YES | BTREE | | |
| lead_history | 1 | avg_index | 2 | new_status | A | 46 | NULL | NULL | YES | BTREE | | |
| lead_history | 1 | avg_index | 3 | agency_id | A | 48 | NULL | NULL | | BTREE | | |
| lead_history | 1 | avg_index | 4 | ts | A | 1330 | NULL | NULL | | BTREE | | |
+--------------+------------+-----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+`
解释一下`
mysql> explain select avg(UNIX_TIMESTAMP(tq.ts) - UNIX_TIMESTAMP(tv.ts)) / 60 as avg_time_to_quote from lead_history tv join lead_history tq on tv.agency_id = tq.agency_id WHERE tv.old_status not like 'Verified' and tq.new_status = 'Verified' and tv.agency_id and tv.agency_id = 'XXXXXXXXXXXX35';
+----+-------------+-------+------------+-------+---------------+-----------+---------+------+-------+----------+-----------------------------------------------------------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-------+------------+-------+---------------+-----------+---------+------+-------+----------+-----------------------------------------------------------------+
| 1 | SIMPLE | tq | NULL | index | NULL | avg_index | 395 | NULL | 13922 | 1.00 | Using where; Using index |
| 1 | SIMPLE | tv | NULL | index | NULL | avg_index | 395 | NULL | 13922 | 8.00 | Using where; Using index; Using join buffer (Block Nested Loop) |
+----+-------------+-------+------------+-------+---------------+-----------+---------+------+-------+----------+-----------------------------------------------------------------+
2 rows in set, 1 warning (0.02 sec)
mysql>
`
最佳答案
由于顺序原因，您拥有的索引毫无用处 -- 添加
INDEX(agency, new_status, ts)执行
GROUP BY...可能是个好主意，但这个答案并不追求这一点。将“状态”列从庞大的
VARCHAR更改为 1 字节ENUM。
考虑一种不同的方法:两个表——一个带有审计跟踪(或交易历史记录)；另一个带有审计跟踪(或交易历史记录)。具有当前状态的一个。这样，就不需要 JOIN 来进行比较。另一方面，它需要:
INSERT到历史表以及UPDATE状态表；或- 历史表上的
TRIGGER用于更新状态表。
关于php - 即使列上有索引，TIMEDIFF 查询也会花费很长时间，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/44085739/