下面的查询都在我们的开发服务器上立即执行，因为它们最多可能需要 2 分 20 秒。
查询执行时间似乎受 LIKE 字符串的模糊性影响。如果他们与一个几乎没有匹配项的国家/地区紧密匹配，则花费的时间会更少，而如果您对德国使用“ge”之类的东西，则执行时间会更长。但这并不总是这样，有时它非常不稳定。
发送数据似乎是罪魁祸首，但这是为什么以及这意味着什么。生产内存看起来也很低(可用内存)？
制作:
英特尔四核至强 E3-1220 3.1GHz
4GB DDR3
RAID1 中的 2 个 1TB SATA
网速100Mb
Ubuntu
发展
英特尔酷睿 i3-2100，2C/4T，3.10GHz
500 GB SATA - 无 RAID
4GB DDR3
此查询不是有问题的查询，而是相关的，因此我将其发布。
SELECT
f.form_question_has_answer_id
FROM
form_question_has_answer f
INNER JOIN
project_company_has_user p ON f.form_question_has_answer_user_id = p.project_company_has_user_user_id
INNER JOIN
company c ON p.project_company_has_user_company_id = c.company_id
INNER JOIN
project p2 ON p.project_company_has_user_project_id = p2.project_id
INNER JOIN
user u ON p.project_company_has_user_user_id = u.user_id
INNER JOIN
form f2 ON p.project_company_has_user_project_id = f2.form_project_id
WHERE
(f2.form_template_name = 'custom' AND p.project_company_has_user_garbage_collection = 0 AND p.project_company_has_user_project_id = '29') AND (LCASE(c.company_country) LIKE '%ge%' OR LCASE(c.company_country) LIKE '%abcde%') AND f.form_question_has_answer_form_id = '174'
上面查询的解释计划是，在开发和生产上运行产生相同的计划。
+----+-------------+-------+--------+----------------------------------------------------------------------------------------------------------------------------------------------+----------------------------------+---------+----------------------------------------------------+------+-------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+--------+----------------------------------------------------------------------------------------------------------------------------------------------+----------------------------------+---------+----------------------------------------------------+------+-------------+
| 1 | SIMPLE | p2 | const | PRIMARY | PRIMARY | 4 | const | 1 | Using index |
| 1 | SIMPLE | f | ref | form_question_has_answer_form_id,form_question_has_answer_user_id | form_question_has_answer_form_id | 4 | const | 796 | Using where |
| 1 | SIMPLE | u | eq_ref | PRIMARY | PRIMARY | 4 | new_klarents.f.form_question_has_answer_user_id | 1 | Using index |
| 1 | SIMPLE | p | ref | project_company_has_user_unique_key,project_company_has_user_user_id,project_company_has_user_company_id,project_company_has_user_project_id | project_company_has_user_user_id | 4 | new_klarents.f.form_question_has_answer_user_id | 1 | Using where |
| 1 | SIMPLE | f2 | ref | form_project_id | form_project_id | 4 | const | 15 | Using where |
| 1 | SIMPLE | c | eq_ref | PRIMARY | PRIMARY | 4 | new_klarents.p.project_company_has_user_company_id | 1 | Using where |
+----+-------------+-------+--------+----------------------------------------------------------------------------------------------------------------------------------------------+----------------------------------+---------+----------------------------------------------------+------+-------------+
执行此查询需要 2 分钟 ~20 秒。
服务器上实际运行的查询是这个:
SELECT
COUNT(*) AS num_results
FROM (SELECT
f.form_question_has_answer_id
FROM
form_question_has_answer f
INNER JOIN
project_company_has_user p ON f.form_question_has_answer_user_id = p.project_company_has_user_user_id
INNER JOIN
company c ON p.project_company_has_user_company_id = c.company_id
INNER JOIN
project p2 ON p.project_company_has_user_project_id = p2.project_id
INNER JOIN
user u ON p.project_company_has_user_user_id = u.user_id
INNER JOIN
form f2 ON p.project_company_has_user_project_id = f2.form_project_id
WHERE
(f2.form_template_name = 'custom' AND p.project_company_has_user_garbage_collection = 0 AND p.project_company_has_user_project_id = '29') AND (LCASE(c.company_country) LIKE '%ge%' OR LCASE(c.company_country) LIKE '%abcde%') AND f.form_question_has_answer_form_id = '174'
GROUP BY
f.form_question_has_answer_id;) dctrn_count_query;
解释计划(同样在开发和生产中):
+----+-------------+-------+--------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+----------------------------------+---------+----------------------------------------------------+------+------------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+--------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+----------------------------------+---------+----------------------------------------------------+------+------------------------------+
| 1 | PRIMARY | NULL | NULL | NULL | NULL | NULL | NULL | NULL | Select tables optimized away |
| 2 | DERIVED | p2 | const | PRIMARY | PRIMARY | 4 | | 1 | Using index |
| 2 | DERIVED | f | ref | form_question_has_answer_form_id,form_question_has_answer_user_id | form_question_has_answer_form_id | 4 | | 797 | Using where |
| 2 | DERIVED | p | ref | project_company_has_user_unique_key,project_company_has_user_user_id,project_company_has_user_company_id,project_company_has_user_project_id,project_company_has_user_garbage_collection | project_company_has_user_user_id | 4 | new_klarents.f.form_question_has_answer_user_id | 1 | Using where |
| 2 | DERIVED | f2 | ref | form_project_id | form_project_id | 4 | | 15 | Using where |
| 2 | DERIVED | c | eq_ref | PRIMARY | PRIMARY | 4 | new_klarents.p.project_company_has_user_company_id | 1 | Using where |
| 2 | DERIVED | u | eq_ref | PRIMARY | PRIMARY | 4 | new_klarents.p.project_company_has_user_user_id | 1 | Using where; Using index |
+----+-------------+-------+--------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+----------------------------------+---------+----------------------------------------------------+------+------------------------------+
在生产服务器上，我的信息如下。
执行时:
+-------------+
| num_results |
+-------------+
| 3 |
+-------------+
1 row in set (2 min 14.28 sec)
显示个人资料:
+--------------------------------+------------+
| Status | Duration |
+--------------------------------+------------+
| starting | 0.000016 |
| checking query cache for query | 0.000057 |
| Opening tables | 0.004388 |
| System lock | 0.000003 |
| Table lock | 0.000036 |
| init | 0.000030 |
| optimizing | 0.000016 |
| statistics | 0.000111 |
| preparing | 0.000022 |
| executing | 0.000004 |
| Sorting result | 0.000002 |
| Sending data | 136.213836 |
| end | 0.000007 |
| query end | 0.000002 |
| freeing items | 0.004273 |
| storing result in query cache | 0.000010 |
| logging slow query | 0.000001 |
| logging slow query | 0.000002 |
| cleaning up | 0.000002 |
+--------------------------------+------------+
开发结果如下。
+-------------+
| num_results |
+-------------+
| 3 |
+-------------+
1 row in set (0.08 sec)
再次针对此查询的配置文件:
+--------------------------------+----------+
| Status | Duration |
+--------------------------------+----------+
| starting | 0.000022 |
| checking query cache for query | 0.000148 |
| Opening tables | 0.000025 |
| System lock | 0.000008 |
| Table lock | 0.000101 |
| optimizing | 0.000035 |
| statistics | 0.001019 |
| preparing | 0.000047 |
| executing | 0.000008 |
| Sorting result | 0.000005 |
| Sending data | 0.086565 |
| init | 0.000015 |
| optimizing | 0.000006 |
| executing | 0.000020 |
| end | 0.000004 |
| query end | 0.000004 |
| freeing items | 0.000028 |
| storing result in query cache | 0.000005 |
| removing tmp table | 0.000008 |
| closing tables | 0.000008 |
| logging slow query | 0.000002 |
| cleaning up | 0.000005 |
+--------------------------------+----------+
如果我删除用户和/或项目内部连接，查询将减少到 30 秒。
我得到的最后一点信息:
Mysqlserver和Apache在同一个盒子上，生产只有一个盒子。
顶部的生产输出:之前和之后。
top - 15:43:25 up 78 days, 12:11, 4 users, load average: 1.42, 0.99, 0.78
Tasks: 162 total, 2 running, 160 sleeping, 0 stopped, 0 zombie
Cpu(s): 0.1%us, 50.4%sy, 0.0%ni, 49.5%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st
Mem: 4037868k total, 3772580k used, 265288k free, 243704k buffers
Swap: 3905528k total, 265384k used, 3640144k free, 1207944k cached
top - 15:44:31 up 78 days, 12:13, 4 users, load average: 1.94, 1.23, 0.87
Tasks: 160 total, 2 running, 157 sleeping, 0 stopped, 1 zombie
Cpu(s): 0.2%us, 50.6%sy, 0.0%ni, 49.3%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st
Mem: 4037868k total, 3834300k used, 203568k free, 243736k buffers
Swap: 3905528k total, 265384k used, 3640144k free, 1207804k cached
但这并不能很好地代表生产的正常状态，所以这里是今天在执行查询之外的抓取。
top - 11:04:58 up 79 days, 7:33, 4 users, load average: 0.39, 0.58, 0.76
Tasks: 156 total, 1 running, 155 sleeping, 0 stopped, 0 zombie
Cpu(s): 3.3%us, 2.8%sy, 0.0%ni, 93.9%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st
Mem: 4037868k total, 3676136k used, 361732k free, 271480k buffers
Swap: 3905528k total, 268736k used, 3636792k free, 1063432k cached
发展:这个在期间或之后都不会改变。
top - 15:47:07 up 110 days, 22:11, 7 users, load average: 0.17, 0.07, 0.06
Tasks: 210 total, 2 running, 208 sleeping, 0 stopped, 0 zombie
Cpu(s): 0.1%us, 0.2%sy, 0.0%ni, 99.7%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st
Mem: 4111972k total, 1821100k used, 2290872k free, 238860k buffers
Swap: 4183036k total, 66472k used, 4116564k free, 921072k cached
最佳答案
如果缓慢是间歇性的，则可能是服务器负载或其他资源争用(在您的情况下，很可能是内存)。您的系统需要有足够的 RAM 来一次将所有索引存储在内存中，否则，如果所需的索引尚未加载到 RAM 中，它将不得不换出内存。
您的 TOP 结果表明可用 RAM 量很少。
使用 innodb_buffer_pool_size设置为 InnoDB 配置缓冲池的大小，以及 key_buffer_size对于 MyISAM。确保将其设置得足够高以同时在 RAM 中保存所有索引，并且您的系统有足够的 RAM 来完成此操作。
关于mysql - 相同的查询，相同的系统，不同的执行时间，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/10818068/