我需要加快这个查询。我该怎么办？
select i.resp_id as id from int_result i, response_set rs, cx_store_child cbu
where rs.survey_id IN(5550512,5550516,5550521,5550520,5590351,5590384,5679615,5679646,5691634,5699259,5699266,5699270)
and i.q_id IN(52603091,52251250,52250724,52251333,52919541,52920117,54409178,54409806,54625102,54738933,54739117,54739221)
and rs.t >= '2017-08-30 00:00:00' and rs.t <= '2017-09-30 00:00:00'
and i.response_set_id = rs.id and rs.cx_business_unit_id = cbu.child_bu_id
and cbu.business_unit_id = 30850
group by rs.cx_business_unit_id, i.a_id, extract(day from rs.t)
------------+------------+-----------------+--------------+-----------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
| Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment | Index_comment |
+------------+------------+-----------------+--------------+-----------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
| int_result | 0 | PRIMARY | 1 | id | A | 240843099 | NULL | NULL | | BTREE | | |
| int_result | 1 | q_id | 1 | q_id | A | 1442174 | NULL | NULL | | BTREE | | |
| int_result | 1 | a_id | 1 | a_id | A | 20070258 | NULL | NULL | | BTREE | | |
| int_result | 1 | resp_id | 1 | resp_id | A | 120421549 | NULL | NULL | | BTREE | | |
| int_result | 1 | response_set_id | 1 | response_set_id | A | 26760344 | NULL | NULL | | BTREE | | |
| int_result | 1 | survey_id | 1 | survey_id | A | 503855 | NULL | NULL | YES | BTREE | | |
| int_result | 1 | survey_id_2 | 1 | survey_id | A | 1459655 | NULL | NULL | YES | BTREE | | |
| int_result | 1 | survey_id_2 | 2 | q_id | A | 2736853 | NULL | NULL | | BTREE | | |
+------------+------------+-----------------+--------------+-----------------+-----------+-------------+----------+--------+------+------------+------
--+---------+---------------+
| Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment | Index_comment |
+--------------+------------+----------------------+--------------+---------------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
| response_set | 0 | PRIMARY | 1 | id | A | 14307454 | NULL | NULL | | BTREE | | |
| response_set | 1 | survey_id | 1 | survey_id | A | 223553 | NULL | NULL | | BTREE | | |
| response_set | 1 | id | 1 | id | A | 14307454 | NULL | NULL | | BTREE | | |
| response_set | 1 | external_id | 1 | external_id | A | 2921 | NULL | NULL | YES | BTREE | | |
| response_set | 1 | panel_member_id | 1 | panel_member_id | A | 357686 | NULL | NULL | YES | BTREE | | |
| response_set | 1 | email_group | 1 | email_group | A | 21259 | NULL | NULL | YES | BTREE | | |
| response_set | 1 | survey_timestamp_idx | 1 | survey_id | A | 433559 | NULL | NULL | | BTREE | | |
| response_set | 1 | survey_timestamp_idx | 2 | t | A | 14307454 | NULL | NULL | YES | BTREE | | |
| response_set | 1 | bu_id | 1 | cx_business_unit_id | A | 2246 | NULL | NULL | YES | BTREE | | |
----------------+------------+------------------+--------------+------------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
| Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment | Index_comment |
+----------------+------------+------------------+--------------+------------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
| cx_store_child | 0 | PRIMARY | 1 | id | A | 13667 | NULL | NULL | | BTREE | | |
| cx_store_child | 0 | bu_child_ref | 1 | business_unit_id | A | 13667 | NULL | NULL | YES | BTREE | | |
| cx_store_child | 0 | bu_child_ref | 2 | child_bu_id | A | 13667 | NULL | NULL | YES | BTREE | | |
| cx_store_child | 1 | cx_feedback_id | 1 | cx_feedback_id | A | 506 | NULL | NULL | YES | BTREE | | |
| cx_store_child | 1 | business_unit_id | 1 | business_unit_id | A | 13667 | NULL | NULL | YES | BTREE | | |
| cx_store_child | 1 | child_bu_id | 1 | child_bu_id | A | 13667 | NULL | NULL | YES | BTREE | | |
+----------------+------------+------------------+--------------+------------------+-----------+-------------+----------+--------+------+------------+
答案 0 :(得分：2)
您似乎在response_set(survey_id, t)上有一个索引。
尝试在
上创建所谓的compound covering indexresponse_set(t, survey_id, cx_business_unit_id)
这可能有助于使用该表优化查询部分。为什么？您的查询要求t进行范围扫描，范围扫描中使用的列必须是其复合索引中的第一个。
同样，int_result (q_id, resp_id, response_set_id)上的索引可能有助于从该表中提取所需的数据。
一些注意事项：
and rs.t >= '2017-08-30 00:00:00' and rs.t <= '2017-09-30 00:00:00'可能不正确。它可能包含一个错误的错误。您想要<代替<=吗？您所提供的内容包括时间戳记录于2017年9月30日午夜，但午夜后没有记录。int_result(survey_id, q_id)上有一个索引，int_result(survey_id)上有另一个索引。后一个索引与前者完全重复，你可以放弃它。 from int_result i
join response_set rs on i.response_set_id = rs.id
join cx_store_child cbu on rs.cx_business_unit_id = cbu.child_bu_id
阅读本文。您正在维护一个大型数据库，值得您花时间学习很多关于索引的知识。 http://use-the-index-luke.com/
答案 1 :(得分：1)
优化程序可能会尝试执行查询的方法有很多种。以下索引可以灵活地找到命中表的最佳顺序：
from bqplot import pyplot as plt
import numpy as np
fig=plt.figure()
lin=plt.plot([0,1],
[0,0])
scatt1=plt.scatter([0],[0],colors=['Red'])
scatt2=plt.scatter([1],[0],enable_move=True)
plt.xlim(-3,3)
plt.ylim(-3,3)
fig.layout.height = '500px'
fig.layout.width = '500px'
plt.show()
def call_back2(name, value):
#print(value,name)
if value['point']:
X=value['point']['x']
Y=value['point']['y']
lin.x=[scatt1.x[0],(X-scatt1.x)[0]]
lin.y=[scatt1.y[0],(Y-scatt1.y)[0]]
scatt2.on_drag_start(call_back2)
scatt2.on_drag(call_back2)
scatt2.on_drag_end(call_back2)
我安排cbu: INDEX(business_unit_id, child_bu_id)
rs: INDEX(t, cx_business_unit_id, survey_id)
rs: INDEX(survey_id, t, cx_business_unit_id)
rs: INDEX(cx_business_unit_id, survey_id, t)
i: INDEX(response_set_id, q_id)
i: INDEX(q_id, response_set_id)
和rs在所有情况下都有“覆盖”索引;这有助于一些人。
（是的，你应该像O. Jones建议的那样改为cbu。其余的建议。）
在进一步讨论之前，请提供JOIN...ON;也可能是数据类型问题。
SHOW CREATE TABLE PRIMARY KEY密钥是UNIQUE - 因此INDEX中的INDEX(id)是多余的。