最近在学习SQL嘛,所以各个地方找题目来练手,毕竟现在能离得开数据库么?
Student(S#,Sname,Sage,Ssex) 学生表
Course(C#,Cname,T#) 课程表
SC(S#,C#,score) 成绩表
Teacher(T#,Tname) 教师表
问题：
1、查询“001”课程比“002”课程成绩高的所有学生的学号；
select a.S# from (select s#,score from SC where C#=‘001’) a,(select
s#,score from SC where C#=‘002’) b where a.score>b.score and
a.s#=b.s#;
2、查询平均成绩大于60分的同学的学号和平均成绩；
select S#,avg(score) from sc group by S# having avg(score)>60;
3、查询所有同学的学号、姓名、选课数、总成绩；
select Student.S#,Student.Sname,count(SC.C#),sum(score)
from Student left Outer join SC on Student.S#=SC.S#
group by Student.S#,Sname
4、查询姓“李”的老师的个数；
select count(distinct(Tname))
from Teacher
where Tname like ‘李%’;
5、查询没学过“叶平”老师课的同学的学号、姓名；
Student.S#,Student.Sname
from Student
where S# not in (select distinct( SC.S#) from SC,Course,Teacher where SC.C#=Course.C# and Teacher.T#=Course.T# and Teacher.Tname=‘叶平’);
6、查询学过“001”并且也学过编号“002”课程的同学的学号、姓名；
select Student.S#,Student.Sname from Student,SC where Student.S#=SC.S# and SC.C#='001’and exists( Select * from SC as SC_2 where SC_2.S#=SC.S# and SC_2.C#=‘002’);
7、查询学过“叶平”老师所教的所有课的同学的学号、姓名；
select S#,Sname
from Student
where S# in (select S# from SC ,Course ,Teacher where SC.C#=Course.C# and Teacher.T#=Course.T# and Teacher.Tname=‘叶平’ group by S# having count(SC.C#)=(select count(C#) from
Course,Teacher where Teacher.T#=Course.T# and Tname=‘叶平’));
8、查询课程编号“002”的成绩比课程编号“001”课程低的所有同学的学号、姓名；
Select S#,Sname from (select Student.S#,Student.Sname,score ,(select score from SC SC_2 where SC_2.S#=Student.S# and SC_2.C#=‘002’) score2
from Student,SC where Student.S#=SC.S# and C#=‘001’) S_2 where score2 <score;
9、查询所有课程成绩小于60分的同学的学号、姓名；
select S#,Sname
from Student
where S# not in (select Student.S# from Student,SC where S.S#=SC.S# and score>60);
10、查询没有学全所有课的同学的学号、姓名；
select Student.S#,Student.Sname
from Student,SC
where Student.S#=SC.S# group by Student.S#,Student.Sname having count(C#) <(select count(C#) from Course);
11、查询至少有一门课与学号为“1001”的同学所学相同的同学的学号和姓名；
select S#,Sname from Student,SC where Student.S#=SC.S# and C# in select C# from SC where S#=‘1001’;
12、查询至少学过学号为“001”同学所有一门课的其他同学学号和姓名；
select distinct SC.S#,Sname
from Student,SC
where Student.S#=SC.S# and C# in (select C# from SC where S#=‘001’);
13、把“SC”表中“叶平”老师教的课的成绩都更改为此课程的平均成绩；
update SC set score=(select avg(SC_2.score)
from SC SC_2
where SC_2.C#=SC.C# ) from Course,Teacher where Course.C#=SC.C# and Course.T#=Teacher.T# and Teacher.Tname=‘叶平’);
14、查询和“1002”号的同学学习的课程完全相同的其他同学学号和姓名；
select S# from SC where C# in (select C# from SC where S#=‘1002’)
group by
S# having count()=(select count() from SC where S#=‘1002’);
15、删除学习“叶平”老师课的SC表记录；
Delect SC
from course ,Teacher
where Course.C#=SC.C# and Course.T#= Teacher.T# and Tname=‘叶平’;
16、向SC表中插入一些记录，这些记录要求符合以下条件：没有上过编号“003”课程的同学学号、2、
号课的平均成绩；
Insert SC select S#,‘002’,(Select avg(score)
from SC where C#=‘002’) from Student where S# not in (Select S# from SC where C#=‘002’);
17、按平均成绩从高到低显示所有学生的“数据库”、“企业管理”、“英语”三门的课程成绩，按如下形式显示： 学生ID,数据库,企业管理,英语,有效课程数,有效平均分
SELECT S# as 学生ID
,(SELECT score FROM SC WHERE SC.S#=t.S# AND C#=‘004’) AS 数据库
,(SELECT score FROM SC WHERE SC.S#=t.S# AND C#=‘001’) AS 企业管理
,(SELECT score FROM SC WHERE SC.S#=t.S# AND C#=‘006’) AS 英语
,COUNT() AS 有效课程数, AVG(t.score) AS 平均成绩
FROM SC AS t
GROUP BY S#
ORDER BY avg(t.score)
18、查询各科成绩最高和最低的分：以如下形式显示：课程ID，最高分，最低分
SELECT L.C# As 课程ID,L.score AS 最高分,R.score AS 最低分
FROM SC L ,SC AS R
WHERE L.C# = R.C# and
L.score = (SELECT MAX(IL.score)
FROM SC AS IL,Student AS IM
WHERE L.C# = IL.C# and IM.S#=IL.S#
GROUP BY IL.C#)
AND
R.Score
= (SELECT MIN(IR.score)
FROM SC AS IR
WHERE R.C# = IR.C#
GROUP BY IR.C#
);
19、按各科平均成绩从低到高和及格率的百分数从高到低顺序
SELECT t.C# AS 课程号,max(course.Cname)AS 课程名,isnull(AVG(score),0) AS 平均成绩
,100 * SUM(CASE WHEN isnull(score,0)>=60 THEN 1 ELSE 0 END)/COUNT() AS 及格百分数
FROM SC T,Course
where t.C#=course.C#
GROUP BY t.C#
ORDER BY 100 * SUM(CASE WHEN isnull(score,0)>=60 THEN 1 ELSE
0 END)/COUNT(*) DESC
20、查询如下课程平均成绩和及格率的百分数(用"1行"显示): 企业管理（001），马克思（002），OO&UML （003），数据库（004）
SELECT SUM(CASE WHEN C# =‘001’ THEN score ELSE 0 END)/SUM(CASE C# WHEN ‘001’ THEN 1 ELSE 0 END) AS 企业管理平均分
,100 * SUM(CASE WHEN C# = ‘001’ AND score >= 60 THEN 1 ELSE 0 END)/SUM(CASE WHEN C# = ‘001’ THEN 1 ELSE 0 END
) AS 企业管理及格百分数
,SUM(CASE WHEN C# = ‘002’ THEN score ELSE 0 END)/SUM(CASE C# WHEN ‘002’ THEN 1 ELSE 0 END) AS 马克思平均分
,100 * SUM(CASE WHEN C# = ‘002’ AND score >= 60 THEN 1 ELSE 0 END)/SUM(CASE WHEN C# = ‘002’ THEN 1 ELSE 0 END) AS 马克思及格百分数
,SUM(CASE WHEN C# = ‘003’ THEN score ELSE 0 END)/
SUM(CASE C# WHEN ‘003’ THEN 1 ELSE 0 END) AS UML平均分
,100 * SUM(CASE WHEN C# = ‘003’ AND score >= 60 THEN 1 ELSE 0 END)/SUM(CASE WHEN C# = ‘003’ THEN 1 ELSE 0 END) AS UML及格百分数
,SUM(CASE WHEN C# = ‘004’ THEN score ELSE 0 END)/SUM(CASE C# WHEN ‘004’ THEN 1 ELSE 0 END) AS 数据库平均分
,100
SUM(CASE WHEN C# = ‘004’ AND score >= 60 THEN 1 ELSE 0 END)/SUM(CASE WHEN C# = ‘004’ THEN 1 ELSE 0 END) AS 数据库及格百分数
FROM SC
21、查询不同老师所教不同课程平均分从高到低显示
SELECT max(Z.T#) AS 教师ID,MAX(Z.Tname) AS 教师姓名,C.C# AS 课程ＩＤ,MAX(C.Cname) AS 课程名称,AVG(Score) AS 平均成绩
FROM SC AS T,Course AS C ,Teacher AS Z
where T.C#=C.C# and C.T#=Z.T#
GROUP BY C.C#
ORDER BY AVG(Score) DESC
22、查询如下课程成绩第 3 名到第 6 名的学生成绩单：企业管理（001），马克思（002），UML （003），数据库（004）
[学生ID],[学生姓名],企业管理,马克思,UML,数据库,平均成绩
SELECT DISTINCT top 3
SC.S# As 学生学号,
Student.Sname AS 学生姓名 ,
T1.score AS 企业管理,
T2.score AS 马克思,
T3.score AS UML,
T4.score AS 数据库,
ISNULL(T1.score,0) + ISNULL(T2.score,0) + ISNULL(T3.score,0) + ISNULL(T4.score,0) as 总分
FROM Student,SC LEFT JOIN SC AS T1
ON SC.S# = T1.S# AND T1.C# = ‘001’
LEFT JOIN SC AS T2
ON SC.S# = T2.S# AND T2.C# = ‘002’
LEFT JOIN SC AS T3
ON SC.S# =T3.S# AND T3.C# = ‘003’
LEFT JOIN SC AS T4
ON SC.S# = T4.S# AND T4.C# = ‘004’
WHERE student.S#=SC.S# and
ISNULL(T1.score,0) + ISNULL(T2.score,0) + ISNULL(T3.score,0) + ISNULL(T4.score,0)
NOT IN
(SELECT
DISTINCT
TOP 15 WITH TIES
ISNULL(T1.score,0) + ISNULL(T2.score,0) + ISNULL(T3.score,0) + ISNULL(T4.score,0)
FROM sc
LEFT JOIN sc AS T1
ON sc.S# = T1.S# AND T1.C#= ‘k1’
LEFT JOIN sc AS T2
ON sc.S# = T2.S# AND T2.C# = ‘k2’
LEFT JOIN sc AS T3
ON sc.S# = T3.S# AND T3.C# = ‘k3’
LEFT JOIN sc AS T4
ON sc.S# = T4.S# AND T4.C# = ‘k4’
ORDER BY ISNULL(T1.score,0) + ISNULL(T2.score,0) + ISNULL(T3.score,0) + ISNULL(T4.score,0) DESC);
23、统计列印各科成绩,各分数段人数:课程ID,课程名称,[100-85],[85-70],[70-60],[ <60]
SELECT SC.C# as 课程ID, Cname
as 课程名称
,SUM(CASE WHEN score BETWEEN 85 AND 100 THEN 1 ELSE 0 END) AS [100 - 85]
,SUM(CASE WHEN score BETWEEN 70 AND 85 THEN 1 ELSE 0 END) AS [85 - 70]
,SUM(CASE WHEN score BETWEEN 60 AND 70 THEN 1 ELSE 0 END) AS [70 - 60]
,SUM(CASE WHEN score < 60 THEN 1 ELSE 0 END) AS [60 -]
FROM SC,Coursewhere SC.C#=Course.C#
GROUP BY SC.C#,Cname;
24、查询学生平均成绩及其名次
SELECT 1+(SELECT COUNT( distinct 平均成绩)
FROM (SELECT S#,AVG(score) AS 平均成绩
FROM SC
GROUP BY S#
) AS T1
WHERE 平均成绩 > T2.平均成绩) as 名次,
S# as 学生学号,平均成绩
FROM (SELECT S#,AVG(score) 平均成绩
FROM SC
GROUP BY S#
) AS T2
ORDER BY 平均成绩 desc;
25、查询各科成绩前三名的记录:(不考虑成绩并列情况)
SELECT t1.S# as 学生ID,t1.C# as 课程ID,Score as 分数
FROM SC t1
WHERE score IN (SELECT TOP 3 score
FROM SC
WHERE t1.C#= C# ORDER BY score DESC
)
ORDER BY t1.C#;
26、查询每门课程被选修的学生数
select c#,count(S#) from sc group by C#;
27、查询出只选修了一门课程的全部学生的学号和姓名
select SC.S#,Student.Sname,count(C#) AS 选课数
from SC ,Student
where SC.S#=Student.S# group by SC.S# ,Student.Sname having count(C#)=1;
28、查询男生、女生人数
Select count(Ssex) as 男生人数 from Student group by Ssex having Ssex=‘男’;
Select count(Ssex) as 女生人数 from Student group by Ssex having Ssex=‘女’；
29、查询姓“张”的学生名单
SELECT Sname FROM Student WHERE Sname like ‘张%’;
30、查询同名同性学生名单，并统计同名人数
select Sname,count() from Studentgroup by Sname having count()>1;;
31、1981年出生的学生名单(注：Student表中Sage列的类型是datetime)
select Sname, CONVERT(char (11),DATEPART(year,Sage)) as age
from student
where CONVERT(char(11),DATEPART(year,Sage))=‘1981’;
32、查询每门课程的平均成绩，结果按平均成绩升序排列，平均成绩相同时，按课程号降序排列
Select C#,Avg(score) from SC group by C# order by Avg(score),C# DESC ;
33、查询平均成绩大于85的所有学生的学号、姓名和平均成绩
select Sname,SC.S# ,avg(score)
from Student,SC
where Student.S#=SC.S# group by SC.S#,Sname having avg(score)>85;
34、查询课程名称为“数据库”，且分数低于60的学生姓名和分数
Select Sname,isnull(score,0)
from Student,SC,Course
where SC.S#=Student.S# and SC.C#=Course.C#and Course.Cname='数据库’and score <60;
35、查询所有学生的选课情况；
SELECT SC.S#,SC.C#,Sname,Cname
FROM SC,Student,Course
where SC.S#=Student.S# and SC.C#=Course.C# ;
36、查询任何一门课程成绩在70分以上的姓名、课程名称和分数；
SELECT distinct student.S#,student.Sname,SC.C#,SC.score
FROM student,Sc
WHERE SC.score>=70 AND SC.S#=student.S#;
37、查询不及格的课程，并按课程号从大到小排列
select c# from sc where scor e <60 order by C# ;
38、查询课程编号为003且课程成绩在80分以上的学生的学号和姓名；
select SC.S#,Student.Sname from SC,Student where SC.S#=Student.S# and Score>80 and C#=‘003’;
39、求选了课程的学生人数
select count() from sc;
40、查询选修“叶平”老师所授课程的学生中，成绩最高的学生姓名及其成绩
select Student.Sname,score
from Student,SC,Course C,Teacher
where Student.S#=SC.S# and SC.C#=C.C# and
C.T#=Teacher.T# and Teacher.Tname=‘叶平’ and SC.score=(select max(score)from SC where C#=C.C# );
41、查询各个课程及相应的选修人数
select count() from sc group by C#;
42、查询不同课程成绩相同的学生的学号、课程号、学生成绩
select distinct A.S#,B.score from SC A ,SC B where A.Score=B.Score and A.C# <>B.C# ;
43、查询每门功成绩最好的前两名
SELECT t1.S# as 学生ID,t1.C# as 课程ID,Score as 分数
FROM SC t1
WHERE score IN (SELECT TOP 2 score
FROM SC
WHERE t1.C#= C#
ORDER BY score DESC
)
ORDER BY t1.C#;
44、统计每门课程的学生选修人数（超过10人的课程才统计）。要求输出课程号和选修人数，查询结果按人数降序排列，查询结果按人数降序排列，若人数相同，按课程号升序排列
select C# as 课程号,count(*) as 人数
from sc
group by C#
order by count(*) desc,c#
1
2
3
45、检索至少选修两门课程的学生学号
select S#
from sc
group by s#
having count() > = 2
46、查询全部学生都选修的课程的课程号和课程名
select C#,Cname
from Course
where C# in (select c# from sc group by c#)
47、查询没学过“叶平”老师讲授的任一门课程的学生姓名
select Sname from Student where S# not in (select S# from Course,Teacher,SC where Course.T#=Teacher.T# and SC.C#=course.C# and Tname=‘叶平’);
48、查询两门以上不及格课程的同学的学号及其平均成绩
select S#,avg(isnull(score,0)) from SC where S# in (select S# from SC where
score <60 group by S# having count()>2)group by S#;
49、检索“004”课程分数小于60，按分数降序排列的同学学号
select S# from SC where C#='004’and score <60 order by score desc;
50、删除“002”同学的“001”课程的成绩
delete from Sc where S#='001’and C#=‘001’;
---------------------
username = username
print('创建用户...')
# 创建用户
os.system('useradd %(name)s -s /home/work/%(name)s' % {'name': username})
# 随机一个密码
password = str((random.randint(100000, 999999)))
# 设置密码
os.system('echo %(name)s:%(pwd)s |chpasswd' % {'name': username, 'pwd': password})
# 将面试题放入新创建用户路径下
os.system('cp -r /home/renligeng/exam/ /home/work/%(name)s' % {'name': username})
# 设置该路径权限
os.system('chmod 700 /home/work/%(name)s' % {'name': username})
# 设置用户权限
os.system('setfacl -m u:%(name)s:rwx /home/work/%(name)s' % {'name': username})
# 输出
os.system('echo "您好,您的账号为：" %(name)s ",密码为:" %(pwd)s' % {'name': username, 'pwd': password})
return ('您好,您的账号为：' + username + ',密码为:' + password)
index.html
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<title>Title</title>
</head>
<body>
<form method="post">
{{ form.csrf_token }}
{{ form.username.label }}{{ form.username }}<br>
{{ form.submit }}<br>
{% for message in get_flashed_messages() %}
{{message}}
{% endfor %}
<hr>
</form>
</body>
</html>mysql> select trace from information_schema.optimizer_trace\G;
*************************** 1. row ****************************
trace:
{
"steps": [
{
"join_preparation": { //优化准备阶段
"select#": 1,
"steps": [
{ //标出查询的sql
"expanded_query": "/* select#1 */ select `a`.`uin` AS `uin`,`a`.`game_centerid` AS `game_centerid`,`a`.`fbuid` AS `fbuid`,0 AS `app_version_c`,`a`.`reg_ip` AS `player_register_ip`,`b`.`last_login_ip` AS `player_last_login_ip`,`b`.`reg_time` AS `player_create_time`,`a`.`reg_time_stamp` AS `user_create_time`,`a`.`last_login_time` AS `user_last_login_time`,`a`.`fb_email` AS `fb_email`,`a`.`ticket` AS `ticket`,'' AS `androidid`,'' AS `imei`,'' AS `adid`,`a`.`last_login_time_stamp` AS `user_last_login_time_stamp`,`a`.`STATUS` AS `user_STATUS`,`a`.`country` AS `country`,`a`.`is_robot` AS `is_robot`,`a`.`platform` AS `platform`,`a`.`language` AS `language`,`a`.`model` AS `model`,`a`.`osver` AS `osver`,`a`.`session_key` AS `session_key`,`b`.`userid` AS `userid`,`b`.`serverid` AS `serverid`,`b`.`last_login_time` AS `player_last_login_time`,`b`.`STATUS` AS `player_STATUS`,`d`.`server_name` AS `server_name`,`a`.`email_state` AS `email_state` from ((`user` `a` left join `user_server` `b` on((`a`.`uin` = `b`.`uin`))) left join `server_list` `d` on((`d`.`serverid` = `b`.`serverid`))) where 1 order by `a`.`uin` desc limit 10"
},
{
"transformations_to_nested_joins":
{
"transformations":
[
"parenthesis_removal"
] ,
"expanded_query": "/* select#1 */ select `a`.`uin` AS `uin`,`a`.`game_centerid` AS `game_centerid`,`a`.`fbuid` AS `fbuid`,0 AS `app_version_c`,`a`.`reg_ip` AS `player_register_ip`,`b`.`last_login_ip` AS `player_last_login_ip`,`b`.`reg_time` AS `player_create_time`,`a`.`reg_time_stamp` AS `user_create_time`,`a`.`last_login_time` AS `user_last_login_time`,`a`.`fb_email` AS `fb_email`,`a`.`ticket` AS `ticket`,'' AS `androidid`,'' AS `imei`,'' AS `adid`,`a`.`last_login_time_stamp` AS `user_last_login_time_stamp`,`a`.`STATUS` AS `user_STATUS`,`a`.`country` AS `country`,`a`.`is_robot` AS `is_robot`,`a`.`platform` AS `platform`,`a`.`language` AS `language`,`a`.`model` AS `model`,`a`.`osver` AS `osver`,`a`.`session_key` AS `session_key`,`b`.`userid` AS `userid`,`b`.`serverid` AS `serverid`,`b`.`last_login_time` AS `player_last_login_time`,`b`.`STATUS` AS `player_STATUS`,`d`.`server_name` AS `server_name`,`a`.`email_state` AS `email_state` from `user` `a` left join `user_server` `b` on((`a`.`uin` = `b`.`uin`)) left join `server_list` `d` on((`d`.`serverid` = `b`.`serverid`)) where 1 order by `a`.`uin` desc limit 10"
}
}
]
}
},
{
"join_optimization": { //优化工作的主要阶段,包括逻辑优化和物理优化两个阶段
"select#": 1,
"steps": [
{
"condition_processing": { //逻辑优化部分
"condition": "WHERE", //先看where条件，我这边没有where条件，所以这部分就分析的比较少
"original_condition": "1",
"steps": [
{
"transformation": "equality_propagation", //逻辑优化,条件化简,等式处理
"resulting_condition": "1"
},
{
"transformation": "constant_propagation", //逻辑优化,条件化简,常量处理
"resulting_condition": "1"
},
{
"transformation": "trivial_condition_removal", //逻辑优化,条件化简,条件去除
"resulting_condition": null
}
]
}
}, //这里逻辑优化之where条件优化结束
{
"substitute_generated_columns": {
}
},
{
"table_dependencies": [ //逻辑优化, 找出表之间的相互依赖关系. 非直接可用的优化方式。我这里是三表相连，所以列出三张表
{
"table": "`user` `a`",
"row_may_be_null": false, //是否可以不存在该行。（PS：这部分我理解是因为我用的left join，所以左表的数据行不能为null，右表是可以的）
"map_bit": 0, //这行类似于排序位置，从0开始
"depends_on_map_bits": [
]
},
{
"table": "`user_server` `b`",
"row_may_be_null": true,
"map_bit": 1,
"depends_on_map_bits": [
0
]
},
{
"table": "`server_list` `d`",
"row_may_be_null": true,
"map_bit": 2,
"depends_on_map_bits": [
0,
1
]
}
]
},
{
"ref_optimizer_key_uses": [ //逻辑优化, 找出备选的索引
{
"table": "`user_server` `b`",
"field": "uin", //这个是索引字段，下面的雷同
"equals": "`a`.`uin`",
"null_rejecting": false
},
{
"table": "`server_list` `d`",
"field": "serverid",
"equals": "`b`.`serverid`",
"null_rejecting": true
}
]
},
{
"rows_estimation": [ //逻辑优化, 估算每个表的元组个数. 单表上进行全表扫描和索引扫描的代价估算. 每个索引都估算索引扫描代价(估算行数)
{
"table": "`user` `a`",
"table_scan": { //逻辑优化, 估算每个表的元组个数. 单表上进行全表扫描的代价
"rows": 5574, //行数
"cost": 97 //代价。这个值越大，代表花费的代价就越大
}
},
{
"table": "`user_server` `b`",
"table_scan": {
"rows": 82555,
"cost": 417
}
},
{
"table": "`server_list` `d`",
"table_scan": {
"rows": 2,
"cost": 1
}
}
]
},
{
"considered_execution_plans": [ //物理优化, 开始多表连接的物理优化计算。这里也是相当于对多表进行连接上的排序，因为我们用的左连接，所以这里的顺序是既定的
{
"plan_prefix": [
] ,
"table": "`user` `a`", //这里对应不同的表名，以及表的分析结果，这里为三表联合，所以下面两个表的分析和这个类似
"best_access_path": { //最优结果汇总
"considered_access_paths": [
{
"rows_to_scan": 5574,
"access_type": "scan", //代表全表扫描
"resulting_rows": 5574,
"cost": 1211.8,
"chosen": true //代表这个计算方式是可行的(PS:也就是主表采用了全表扫描，索引字段没用上，从这一步开始，就有问题了！！！)
}
]
} ,
"condition_filtering_pct": 100,
"rows_for_plan": 5574,
"cost_for_plan": 1211.8,
"rest_of_plan": [
{
"plan_prefix": [
"`user` `a`"
] ,
"table": "`user_server` `b`", //user_server表
"best_access_path": {
"considered_access_paths": [
{
"access_type": "ref", //根据下面的index，可知查询方式为使用索引
"index": "uin",
"rows": 16.416,
"cost": 109802,
"chosen": true //选用
},
{
"rows_to_scan": 82555,
"access_type": "scan", //这部分代表全表扫描没有被采用
"using_join_cache": true,
"buffers_needed": 35,
"resulting_rows": 82555,
"cost": 9.2e7,
"chosen": false
}
]
} ,
"condition_filtering_pct": 100, //这部分推测为前两个表连接需要扫描的行数和花费计划
"rows_for_plan": 91502,
"cost_for_plan": 111014,
"rest_of_plan": [
{
"plan_prefix": [
"`user` `a`",
"`user_server` `b`"
] ,
"table": "`server_list` `d`",
"best_access_path": {
"considered_access_paths": [
{
"access_type": "eq_ref",
"index": "PRIMARY", //第三个表使用主键索引即可
"rows": 1,
"cost": 109802,
"chosen": true,
"cause": "clustered_pk_chosen_by_heuristics"
},
{
"rows_to_scan": 2,
"access_type": "scan",
"using_join_cache": true,
"buffers_needed": 619,
"resulting_rows": 2,
"cost": 37220,
"chosen": true
}
]
},
"condition_filtering_pct": 100,
"rows_for_plan": 183003, //这应该算是最终的查询量，只是本人推测
"cost_for_plan": 148234,
"chosen": true
}
]
}
]
}
]
},
{
"condition_on_constant_tables": "1",
"condition_value": true
},
{
"attaching_conditions_to_tables": { //逻辑优化，尽量把条件绑定到对应的表上。此处条件为server_list表的条件
"original_condition": "1",
"attached_conditions_computation": [
{
"table": "`server_list` `d`",
"rechecking_index_usage": {
"recheck_reason": "not_first_table", //重新检查，不是第一个表
"range_analysis": {
"table_scan": {
"rows": 2,
"cost": 3.5
} ,
"potential_range_indexes": [ //逻辑优化, 列出备选的索引。此处列出的为server_list表的索引
{
"index": "PRIMARY",
"usable": true, //这个字段代表是否用到了索引
"key_parts": [
"serverid"
]
},
{
"index": "gameid",
"usable": false,
"cause": "not_applicable"
},
{
"index": "server_state",
"usable": false,
"cause": "not_applicable"
}
],
"setup_range_conditions": [
],
"group_index_range": { //分组的索引范围。因为不是单一的表，所以这里显示了false。（PS：分组这里也有问题，就是什么索引都没用到，所以才会影响速度）
"chosen": false,
"cause": "not_single_table"
},
"analyzing_range_alternatives": { //逻辑优化,开始计算每个索引做范围扫描的花费(等值比较是范围扫描的特例)
"range_scan_alternatives": [
{
"index": "PRIMARY",
"chosen": false,
"cause": "depends_on_unread_values" //取决于未读的值
}
],
"analyzing_roworder_intersect": { //分析相交的行
"usable": false,
"cause": "too_few_roworder_scans" //太少的扫描行
}
}
}
}
}
],
"attached_conditions_summary": [ //附加条件汇总，这一栏在函数最后打印上述的最终结果
{
"table": "`user` `a`",
"attached": null
},
{
"table": "`user_server` `b`",
"attached": null
},
{
"table": "`server_list` `d`",
"attached": "<if>(is_not_null_compl(d), (`d`.`serverid` = `b`.`serverid`), true)" //只有server_list表有
}
]
}
},
{
"clause_processing": { //子句处理，一般是尝试优化distinct/group by/ order by等
"clause": "ORDER BY",
"original_clause": "`a`.`uin` desc",
"items": [
{
"item": "`a`.`uin`"
}
],
"resulting_clause_is_simple": true,
"resulting_clause": "`a`.`uin` desc"
}
},
{
"refine_plan": [ //完善计划
{
"table": "`user` `a`"
},
{
"table": "`user_server` `b`"
},
{
"table": "`server_list` `d`"
}
]
}
]
}
},
{
"join_execution": { //表连接执行相关
"select#": 1,
"steps": [
{
"creating_tmp_table": { //此处创建了临时表。临时表和文件排序，都对应explain执行计划中的extra:Using temporary; Using filesort
"tmp_table_info": {
"table": "intermediate_tmp_table",
"row_length": 1915,
"key_length": 0,
"unique_constraint": false,
"location": "memory (heap)", //内存表
"row_limit_estimate": 8760 //行数限制估计
}
}
},
{
"converting_tmp_table_to_ondisk": {
"cause": "memory_table_size_exceeded",
"tmp_table_info": {
"table": "intermediate_tmp_table",
"row_length": 1915,
"key_length": 0,
"unique_constraint": false,
"location": "disk (InnoDB)", //磁盘表
"record_format": "packed"
}
}
},
{
"filesort_information": [ //文件排序相关
{
"direction": "desc",
"table": "intermediate_tmp_table",
"field": "uin" //文件排序的字段
}
],
"filesort_priority_queue_optimization": {
"limit": 10,
"rows_estimate": 352,
"row_size": 14,
"memory_available": 262144,
"chosen": true
},
"filesort_execution": [
],
"filesort_summary": { //文件排序汇总
"rows": 11,
"examined_rows": 82400,
"number_of_tmp_files": 0,
"sort_buffer_size": 248,
"sort_mode": "<sort_key, rowid>"