牛客网SQL训练4—SQL进阶挑战
发布时间：2023年12月28日
文章目录
一、增删改操作
1. 插入记录
【题目1：插入记录 (一)】
插入记录的方式汇总：
1. 普通插入（全字段）：INSERT INTO table_name VALUES (value1, value2, …)
?普通插入（限定字段）：INSERT INTO table_name (column1, column2, …) VALUES (value1, value2, …)
?多条一次性插入：INSERT INTO table_name (column1, column2, …) VALUES (value1_1, value1_2, …), (value2_1, value2_2, …), …
2. 从另一个表导入：INSERT INTO table_name SELECT * FROM table_name2 [WHERE key=value]
3. 带更新的插入：REPLACE INTO table_name VALUES (value1, value2, …) （注意这种原理是检测到主键或唯一性索引键重复就删除原记录后重新插入）
-- 因为id为自增，所以插入两条数据除自增id列以外的列
-- 提交时间可以让它自己计算
insert into exam_record(uid,exam_id,start_time,submit_time,score) values
(1001,9001,'2021-09-01 22:11:12','2021-09-01 22:11:12'+interval 50 minute,90),
(1002,9002,'2021-09-04 07:01:02',null,null)
;
【题目2：插入记录 (二)】
-- 第一列为自增主键列，不能直接复制过去
-- 只复制2021年之前的记录 & 只复制已完成了的试题作答纪录：用提交时间
insert into exam_record_before_2021(uid,exam_id,start_time,submit_time,score)
select uid,exam_id,start_time,submit_time,score from exam_record
where substr(submit_time,1,4)<='2021'
;
【题目3：插入记录 (三)】
replace into examination_info(exam_id,tag,difficulty,duration,release_time) values
(9003,'SQL','hard',90,'2021-01-01 00:00:00')
;
2. 更新记录
【题目1：更新记录 (一)】
修改记录的方式汇总：
1. 设置为新值：UPDATE table_name SET column_name=new_value [, column_name2=new_value2] [WHERE column_name3=value3]
2. 根据已有值替换：UPDATE table_name SET key1=replace(key1, ‘查找内容’, ‘替换成内容’) [WHERE column_name3=value3]
-- 方法1
update examination_info
set tag='Python'
where tag='PYTHON'
;
-- 方法2
update examination_info
set tag=replace(tag,'PYTHON','Python')
where tag='PYTHON'
;
-- 思维扩展：第二种方式不仅可用于整体替换，还能做子串替换，例如要实现将tag中所有的PYTHON替换为Python（如CPYTHON=>CPython），可写作：
update examination_info
set tag = replace(tag, "PYTHON", "Python")
where tag like "%PYTHON%";
;
【题目2：更新记录 (二)】
-- 未完成：分数为null
update exam_record
set submit_time='2099-01-01 00:00:00',score=0
where substr(start_time,1,10)<'2021-09-01' and score is null;
;
3. 删除记录
【题目1：删除记录 (一)】
删除记录的方式汇总：
1. 根据条件删除：DELETE FROM tb_name [WHERE options] [ [ ORDER BY fields ] LIMIT n ]
2. 全部删除（表清空，包含自增计数器重置）：TRUNCATE TABLE tb_name
-- 时间差：TIMESTAMPDIFF(interval, time_start, time_end)可计算time_start-time_end的时间差，单位以指定的interval为准，
-- 常用可选：SECOND 秒
-- MINUTE 分钟（返回秒数差除以60的整数部分）
-- HOUR 小时（返回秒数差除以3600的整数部分）
-- DAY 天数（返回秒数差除以3600*24的整数部分）
-- MONTH 月数
-- YEAR 年数
delete from exam_record
where timestampdiff(minute,start_time,submit_time)<5 and score<60
;
【题目2：删除记录 (二)】
delete from exam_record
where submit_time is null or timestampdiff(minute,start_time,submit_time)<5
order by start_time
limit 3
;
【题目3：删除记录 (三)】
truncate table exam_record;
二、表与索引操作
1. 表的创建、修改与删除
【题目1：创建一张新表】
表的创建、修改与删除：
1.1 直接创建表
CREATE TABLE [IF NOT EXISTS] tb_name – 不存在才创建，存在就跳过
(column_name1 data_type1 – 列名和类型必选
[ PRIMARY KEY – 可选的约束，主键
| FOREIGN KEY – 外键，引用其他表的键值
| AUTO_INCREMENT – 自增ID
| COMMENT comment – 列注释（评论）
| DEFAULT default_value – 默认值
| UNIQUE – 唯一性约束，不允许两条记录该列值相同
| NOT NULL – 该列非空
], …
) [CHARACTER SET charset] – 字符集编码
[COLLATE collate_value] – 列排序和比较时的规则（是否区分大小写等）
1.2 从另一张表复制表结构创建表：
CREATE TABLE tb_name LIKE tb_name_old
1.3 从另一张表的查询结果创建表：
CREATE TABLE tb_name AS SELECT * FROM tb_name_old WHERE options
2.1 修改表：ALTER TABLE 表名 修改选项
选项集合：
{ ADD COLUMN <列名> <类型> [first|after 字段名] – 增加列
| CHANGE COLUMN <旧列名> <新列名> <新列类型> – 修改列名
| MODIFY COLUMN <列名> <新类型> [新约束] – 修改列类型或约束
| MODIFY COLUMN <列名> <新类型> first – 将某一列放到第一列
| DROP COLUMN <列名> – 删除列
| RENAME TO <新表名> – 修改表名
| CHARACTER SET <字符集名> – 修改字符集
| COLLATE <校对规则名> } – 修改校对规则（比较和排序时用到）
3.1 删除表：DROP TABLE [IF EXISTS] 表名1 [ ,表名2]。
create table user_info_vip(
id INT(11) PRIMARY KEY AUTO_INCREMENT COMMENT '自增ID'
,uid INT(11) UNIQUE NOT NULL COMMENT '用户ID'
,nick_name VARCHAR(64) COMMENT '昵称'
,achievement INT(11) DEFAULT 0 COMMENT '成就值'
,level INT(11) COMMENT '用户等级'
,job VARCHAR(32) COMMENT '职业方向'
,register_time DATETIME DEFAULT CURRENT_TIMESTAMP COMMENT '注册时间'
) CHARACTER SET utf8 COLLATE utf8_general_ci COMMENT = '优质用户信息表'
;
【题目2：修改表】
-- 易出错的地方:当想要设置default的值为数字0时,前面必须加上<列类型>为INT,否则会报default的错误
alter table user_info add column school varchar(15) after level;
alter table user_info change job profession varchar(10);
alter table user_info modify column achievement int(11) default 0;
【题目3：删除表】
drop table if exists
exam_record_2011,
exam_record_2012,
exam_record_2013,
exam_record_2014;
2. 索引的创建、删除
【题目1：创建索引】
索引创建、删除与使用：
1.1 create方式创建索引：
CREATE
[UNIQUE – 唯一索引
| FULLTEXT – 全文索引
] INDEX index_name ON table_name – 不指定唯一或全文时默认普通索引
(column1[(length) [DESC|ASC]] [,column2,…]) – 可以对多列建立组合索引
1.2 alter方式创建索引：
ALTER TABLE tb_name ADD [UNIQUE | FULLTEXT] [INDEX] index_content(content) – 主键索引
2.1 drop方式删除索引：
DROP INDEX <索引名> ON <表名>
2.2 alter方式删除索引：
ALTER TABLE <表名> DROP INDEX <索引名>
3.1 索引的使用：
(1)索引使用时满足最左前缀匹配原则，即对于组合索引(col1, col2)，在不考虑引擎优化时，条件必须是col1在前col2在后，或者只使用col1，索引才会生效；
(2)索引不包含有NULL值的列
(3)一个查询只使用一次索引，where中如果使用了索引，order by就不会使用
(4)like做字段比较时只有前缀确定时才会使用索引
(5)在列上进行运算后不会使用索引，如year(start_time)<2020不会使用start_time上的索引
3.2 不同索引的区别：
(1)主键索引： 它是一种特殊的唯一索引，不允许有空值。一般是在建表的时候指定了主键，就会创建主键索引， CREATE INDEX不能用来创建主键索引，使用 ALTER TABLE来代替。
(2)唯一索引：与普通索引类似，不同的就是：索引列的值必须唯一，但允许有空值。如果是组合索引，则列值的组合必须一。
(3)普通索引：这是最基本的索引，它没有任何限制。
(4)全文索引：FULLTEXT索引用于全文搜索。只有InnoDB和 MyISAM存储引擎支持 FULLTEXT索引和仅适用于 CHAR， VARCHAR和 TEXT列。
CREATE INDEX idx_duration ON examination_info(duration);
CREATE UNIQUE INDEX uniq_idx_exam_id ON examination_info(exam_id);
CREATE FULLTEXT INDEX full_idx_tag ON examination_info(tag);
【题目2：删除索引】
-- 方法1：
DROP INDEX uniq_idx_exam_id ON examination_info;
DROP INDEX full_idx_tag ON examination_info;
-- 方法2：
ALTER TABLE examination_info DROP INDEX uniq_idx_exam_id;
ALTER TABLE examination_info DROP INDEX full_idx_tag;
三、聚合分组查询
1. 聚合函数
【题目1：SQL类别高难度试卷得分的截断平均值】
select
tag
,difficulty
,round((sum_score-max_score-min_score)/(score_cnt-2),1) clip_avg_score
from (
select
tag
,difficulty
,count(score) score_cnt
,sum(score) sum_score
,max(score) max_score
,min(score) min_score
from (
select
exam_id
,uid
,score
from exam_record
) a join (
select
exam_id
,tag
,difficulty
from examination_info
where tag='SQL' and difficulty='hard'
) b on a.exam_id=b.exam_id
group by tag,difficulty
) a1
;
【题目2：统计作答次数】
select
count(1) total_pv
,count(submit_time) complete_pv
,count(distinct if(submit_time is null,exam_id=null,exam_id)) complete_exam_cnt
from exam_record
;
【题目3：得分不小于平均分的最低分(这题有bug,运行不通过)】
select
min(score) min_score_over_avg
from (
select
score
,avg(score) over() avg_score
from (
select
exam_id
,score
from exam_record
) a join (
select
exam_id
,tag
from examination_info
where tag='SQL'
) b on a.exam_id=b.exam_id
) a1
where score>=avg_score
;
2. 分组查询
【题目1：平均活跃天数和月活人数】
select
month
,round(avg(day_m),2) avg_active_days
,round(count(distinct uid),2) mau
from (
select
date_format(submit_time,'%Y%m') month
,uid
,count(distinct substr(submit_time,1,10)) day_m
from exam_record
where substr(submit_time,1,4)='2021'
group by date_format(submit_time,'%Y%m'),uid
) a
group by month
;
【题目2：月总刷题数和日均刷题数】
-- 使用 WITH ROLLUP，此函数是对聚合函数进行求和，注意 with rollup是对 group by 后的第一个字段，进行分组计算。
select
ifnull(submit_month,'2021汇总') submit_month
,month_q_cnt
,round(avg_day_q_cnt,3) avg_day_q_cnt
from (
select
date_format(submit_time,'%Y%m') submit_month
,count(question_id) month_q_cnt
,count(question_id)/max(day(last_day(submit_time))) avg_day_q_cnt
from practice_record
where substr(submit_time,1,4)='2021'
group by date_format(submit_time,'%Y%m')
with rollup
) a
order by submit_month
;
【题目3：未完成试卷数大于1的有效用户】
-- 对于每条作答tag，用:连接日期和tag：concat_ws(':', date(start_time), tag)
-- 对于一个人（组内）的多条作答，用;连接去重后的作答记录：group_concat(distinct concat_ws(':', date(start_time), tag) SEPARATOR ';')
select
uid
,sum(if(submit_time is null,1,0)) incomplete_cnt
,sum(if(submit_time is not null,1,0)) complete_cnt
,group_concat(distinct concat_ws(':', date(start_time), tag) SEPARATOR ';') detail
from (
select
uid
,exam_id
,submit_time
,start_time
from exam_record
where substr(start_time,1,4)='2021'
) a left join (
select
exam_id
,tag
from examination_info
) b on a.exam_id=b.exam_id
group by uid
having sum(if(submit_time is not null,1,0))>=1
and sum(if(submit_time is null,1,0))<5
and sum(if(submit_time is null,1,0))>1
order by incomplete_cnt desc
;
四、多表查询
1. 嵌套子查询
【题目1：月均完成试卷数不小于3的用户爱作答的类别】
select
tag
,count(start_time) tag_cnt
from (
select
uid
,exam_id
,submit_time
,start_time
from exam_record
) a left join (
select
exam_id
,tag
from examination_info
) b on a.exam_id=b.exam_id
where uid in (
select
uid
from exam_record
where submit_time is not null
group by uid,substr(start_time,1,7)
having count(start_time)>=3
)
group by tag
order by tag_cnt desc
;
【题目2：试卷发布当天作答人数和平均分】
select
c.exam_id
,count(distinct b.uid) uv
,round(avg(score),1) avg_score
from(
select
uid
,level
from user_info
where level>5
) a join (
select
uid
,exam_id
,score
,substr(start_time,1,10) start_time
from exam_record
) b on a.uid=b.uid
join (
select
exam_id
,tag
,substr(release_time,1,10) release_time
from examination_info
where tag='SQL'
) c on b.exam_id=c.exam_id
where start_time=release_time
group by c.exam_id
order by uv desc,avg_score asc
;
【题目3：作答试卷得分大于过80的人的用户等级分布】
select
level
,count(distinct uid) level_cnt
from (
select
a.exam_id
,a.tag
,b.uid
,b.score
,c.level
from (
select
exam_id
,tag
from examination_info
where tag='SQL'
) a join (
select
uid
,exam_id
,score
from exam_record
where score>80
) b on a.exam_id=b.exam_id
join (
select
uid
,level
from user_info
) c on b.uid=c.uid
) a1
group by level
order by level_cnt desc,level desc
;
2. 合并查询
【题目1：每个题目和每份试卷被作答的人数和次数】
-- 先UNION后ORDER BY时，只需要在最后一个SELECT语句中包含ORDER BY；
select
exam_id tid
,count(distinct uid) uv
,count(uid) pv
from exam_record
group by exam_id
union all
select
question_id tid
,count(distinct uid) uv
,count(uid) pv
from practice_record
group by question_id
order by uv desc,pv desc
-- 先ORDER BY后UNION时，由于优先级问题，需要将子查询用括号括起来，且ORDER BY后面必须有 LIMIT`；
#-- 题目答案：
select
tid
,uv
,pv
from (
select
exam_id tid
,count(distinct uid) uv
,count(uid) pv
from exam_record
group by exam_id
order by uv desc,pv desc
) a
union all
select
tid
,uv
,pv
from (
select
question_id tid
,count(distinct uid) uv
,count(uid) pv
from practice_record
group by question_id
order by uv desc,pv desc
) b
;
【题目2：分别满足两个活动的人】
select
uid
,'activity1' activity
from exam_record
where substr(start_time,1,4)='2021'
group by uid
having min(score)>=85
union all
select
uid
,'activity2' activity
from (
select
uid
,exam_id
,start_time
,submit_time
,score
from exam_record
where substr(start_time,1,4)='2021'
and score>80
) a join (
select
exam_id
,difficulty
,duration
from examination_info
where difficulty='hard'
) b on a.exam_id=b.exam_id
where timestampdiff(second,start_time,submit_time)<=duration*30
order by uid
;
3. 连接查询
【题目1：满足条件的用户的试卷完成数和题目练习数】
select
a.uid
,ifnull(exam_cnt,0) exam_cnt
,ifnull(question_cnt,0) question_cnt
from (
-- 红名大佬2021年试卷总完成次数
select
uid
,count(submit_time) exam_cnt
from exam_record
where substr(start_time,1,4)='2021'
and uid in (
-- 高难度SQL试卷得分平均值大于80并且是7级的红名大佬
select
c.uid
from (
-- 高难度SQL试卷
select
exam_id
from examination_info
where difficulty='hard'
and tag='SQL'
) a join (
select
uid
,exam_id
,score
from exam_record
) b on a.exam_id=b.exam_id
join (
-- 7级的红名大佬
select
uid
from user_info
where level=7
) c on b.uid=c.uid
group by c.uid
having avg(score)>80
)
group by uid
) a left join (
-- 红名大佬2021年试卷总完成次数
select
uid
,count(submit_time) question_cnt
from practice_record
where substr(submit_time,1,4)='2021'
group by uid
) b on a.uid=b.uid
order by exam_cnt asc,question_cnt desc
;
【题目2：每个6/7级用户活跃情况】
-- 活跃天数考虑跨天的情况
select
a.uid -- 每个6/7级用户
,ifnull(e.active_d,0) act_month_total -- 总活跃月份数
,ifnull(d.active_d,0) act_days_2021 -- 2021年活跃天数
,ifnull(b.active_d,0) act_days_2021_exam -- 2021年试卷作答活跃天数
,ifnull(c.active_d,0) act_days_2021_question -- 2021年答题作答活跃天数
from (
-- 每个6/7级用户
select
uid
from user_info
where level in ('6','7')
) a left join (
-- 2021年试卷作答活跃天数
select
uid
,count(active_d) active_d
from (
select
uid
,substr(start_time,1,10) active_d
from exam_record
where substr(start_time,1,4)='2021'
group by uid,substr(start_time,1,10)
union
select
uid
,substr(submit_time,1,10) active_d
from exam_record
where substr(submit_time,1,4)='2021'
group by uid,substr(submit_time,1,10)
) bb
group by uid
) b on a.uid=b.uid
left join (
-- 2021年答题作答活跃天数
select
uid
,count(active_d) active_d
from (
select
uid
,substr(submit_time,1,10) active_d
from practice_record
where substr(submit_time,1,4)='2021'
group by uid,substr(submit_time,1,10)
) cc
group by uid
) c on a.uid=c.uid
left join (
-- 2021年活跃天数
select
uid
,count(active_d) active_d
from (
select
uid
,substr(start_time,1,10) active_d
from exam_record
where substr(start_time,1,4)='2021'
group by uid,substr(start_time,1,10)
union
select
uid
,substr(submit_time,1,10) active_d
from exam_record
where substr(submit_time,1,4)='2021'
group by uid,substr(submit_time,1,10)
union
select
uid
,substr(submit_time,1,10) active_d
from practice_record
where substr(submit_time,1,4)='2021'
group by uid,substr(submit_time,1,10)
) dd
group by uid
) d on a.uid=d.uid
left join (
select
uid
,count(active_d) active_d
from (
-- 2021年活跃天数
select
uid
,substr(start_time,1,7) active_d
from exam_record
group by uid,substr(start_time,1,7)
union
select
uid
,substr(submit_time,1,7) active_d
from exam_record
group by uid,substr(submit_time,1,7)
union
select
uid
,substr(submit_time,1,7) active_d
from practice_record
group by uid,substr(submit_time,1,7)
) ee
group by uid
) e on a.uid=e.uid
order by act_month_total desc,act_days_2021 desc
;
五、窗口函数
1. 专用窗口函数
【题目1：每类试卷得分前3名】
select
tag
,uid
,ranking
from (
select
tag
,uid
,max(score) max_score -- 获取各个科目每个用户得分的最大值
,min(score) min_score -- 获取各个科目每个用户得分的最小值
,row_number() over(partition by tag order by max(score) desc,min(score) desc,uid desc) ranking
from (
select
exam_id
,uid
,score
from exam_record
) a left join (
select
exam_id
,tag
from examination_info
) b on a.exam_id=b.exam_id
group by tag,uid
) a1
where ranking <=3
;
【题目2：第二快/慢用时之差大于试卷时长一半的试卷】
select distinct
exam_id
,duration
,release_time
from (
select
a.exam_id
,diff
,duration
,duration*30 duration_half
,release_time
,nth_value(diff,2) over(partition by exam_id order by diff rows between unbounded preceding and unbounded following) fast_two
,nth_value(diff,2) over(partition by exam_id order by diff desc rows between unbounded preceding and unbounded following) low_two
from (
select
exam_id
,duration
,release_time
from examination_info
) a left join (
select
exam_id
,start_time
,submit_time
,timestampdiff(second,start_time,submit_time) diff
from exam_record
) b on a.exam_id=b.exam_id
) a1
where low_two-fast_two>duration_half
order by exam_id desc
;
【题目3：连续两次作答试卷的最大时间窗】
select
uid
,days_window
,round(exam_cnt/diff_days*days_window, 2) avg_exam_cnt
from (
select
uid
,count(exam_id) exam_cnt -- 此人作答的总试卷数
,datediff(max(start_time),min(start_time))+1 diff_days -- 最早一次作答和最晚一次作答的相差天数
,max(datediff(next_start_time,start_time))+1 days_window -- 两次作答的最大时间窗
from (
select distinct
uid
,exam_id
,date(start_time) start_time
,lead(date(start_time),1) over(partition by uid order by date(start_time)) next_start_time -- 将连续的下次作答时间拼上
from exam_record
where substr(start_time,1,4)='2021'
and uid in (
-- 2021年至少有两天作答过试卷的人
select
uid
from exam_record
where substr(start_time,1,4)='2021'
group by uid
having count(distinct date(start_time))>=2
)
) a
group by uid
) a1
order by days_window desc,avg_exam_cnt desc
;
【题目4：近三个月未完成试卷数为0的用户完成情况】
select
uid
,count(submit_time) exam_complete_cnt
from (
select
uid
,start_time
,submit_time
,score
,dense_rank() over(partition by uid order by substr(start_time,1,7) desc) rn
from exam_record
) a
where rn<=3
group by uid
having count(start_time)=count(submit_time)
order by exam_complete_cnt desc,uid desc
;
【题目5：未完成率较高的50%用户近二个月答卷情况】
-- 题目解释中说“1001、1002、1003分别排在1.0、0.5、0.0的位置”，有意让我们用percent_rank，实际cume_dist更常用
select
uid
,start_month
,count(start_time) total_cnt
,count(submit_time) complete_cnt
from(
-- 有试卷作答记录的近三个月
select
a.uid
,a.start_time
,a.submit_time
,date_format(a.start_time,'%Y%m') start_month
,dense_rank() over(partition by a.uid order by date_format(a.start_time,'%Y%m') desc) dr
from (
select
uid
,start_time
,submit_time
from exam_record
) a join (
-- 6级和7级用户
select
uid
from user_info
where level in ('6','7')
) b on a.uid=b.uid
join (
-- SQL试卷上未完成率较高的50%用户
select
uid
from (
select
uid
,sum(if(submit_time is null,1,0)) incomplete_cnt -- 未完成试卷数
,count(start_time) total_cnt -- 试卷总数
,sum(if(submit_time is null,1,0))/count(start_time) incomplete_rate -- 未完成试卷率
-- ,cume_dist() over(order by sum(if(submit_time is null,1,0))/count(start_time) desc) ct
,percent_rank() over(order by sum(if(submit_time is null,1,0))/count(start_time) desc) pr -- 未完成试卷率百分比
from (
select
exam_id
from examination_info
where tag='SQL'
) a join (
select
exam_id
,uid
,start_time
,submit_time
from exam_record
) b on a.exam_id=b.exam_id
group by uid
) a1
where pr<=0.5
) c on a.uid=c.uid
) a1
where dr<=3
group by uid,start_month
order by uid,start_month
;
【题目6：试卷完成数同比2020年的增长率及排名变化】
#第三步：取出所有需要的字段，并计算排名变化（2021-2020年，无需取绝对值）
select
tag
,exam_cnt_20
,exam_cnt_21
,concat(round((exam_cnt_21/exam_cnt_20-1)*100,1),'%') growth_rate
,exam_cnt_rank_20
,exam_cnt_rank_21
-- ,exam_cnt_21-exam_cnt_20 rank_delta
,cast(exam_cnt_rank_21 as signed) - cast(exam_cnt_rank_20 as signed) rank_delta -- 将value转换成INT(有符号的整数)格式
from (
#第二步：计算growth_rate
select
tag
,max(if(year='2020',exam_cnt,null)) exam_cnt_20
,max(if(year='2021',exam_cnt,null)) exam_cnt_21
,max(if(year='2020',exam_cnt_rank,null)) exam_cnt_rank_20
,max(if(year='2021',exam_cnt_rank,null)) exam_cnt_rank_21
from (
#第一步：找到所有tag在2020，2021上半年的完成数和排名
select
tag
,substr(b.submit_time,1,4) year
,count(b.submit_time) exam_cnt
,rank() over(partition by substr(b.submit_time,1,4) order by count(b.submit_time) desc) exam_cnt_rank
from (
select
exam_id
,tag
from examination_info
) a join (
select
exam_id
,start_time
,submit_time
from exam_record
where substr(submit_time,1,10) between '2021-01-01' and '2021-06-30'
) b on a.exam_id=b.exam_id
group by tag,substr(b.submit_time,1,4)
union all
select
tag
,substr(c.submit_time,1,4) year
,count(c.submit_time) exam_cnt
,rank() over(partition by substr(c.submit_time,1,4) order by count(c.submit_time) desc) exam_cnt_rank
from (
select
exam_id
,tag
from examination_info
) a join (
select
exam_id
,start_time
,submit_time
from exam_record
where substr(submit_time,1,10) between '2020-01-01' and '2020-06-30'
) c on a.exam_id=c.exam_id
group by tag,substr(c.submit_time,1,4)
) a1
group by tag
) a2
where exam_cnt_20 is not null and exam_cnt_21 is not null # 第四步：筛选出2020和2021年均有完成记录的tag，并按题目要求排序
order by growth_rate desc,exam_cnt_rank_21 desc
;
2. 聚合窗口函数
【题目1：对试卷得分做min-max归一化】
select
uid
,exam_id
,round(avg(min_max),0) avg_new_score #归一化后分数平均值
from (
select
uid
,exam_id
,score
,if(min_score=max_score,score,(score-min_score)/(max_score-min_score)*100) min_max #归一化后缩放到[0,100]区间
from (
select
b.uid
,b.exam_id
,b.score
,min(b.score) over(partition by b.exam_id) min_score #求每类试卷的得分最小值
,max(b.score) over(partition by b.exam_id) max_score #求每类试卷的得分最大值
from (
select
exam_id
,difficulty
from examination_info
where difficulty ='hard' #难度为hard
) a join (
select
uid
,exam_id
,score
from exam_record
) b on a.exam_id=b.exam_id
where b.score is not null #得分不为null
) a1
) a2
group by uid,exam_id
order by exam_id,avg_new_score desc #按照试卷ID升序，评价分降序排序
;
【题目2：每份试卷每月作答数和截止当月的作答总数】
select
exam_id
,date_format(start_time,'%Y%m') start_month
,count(start_time) month_cnt #每份试卷每月作答数
,sum(count(start_time)) over(partition by exam_id order by date_format(start_time,'%Y%m')) cum_exam_cnt #每份试卷截止当月的作答总数
from exam_record
group by exam_id,date_format(start_time,'%Y%m')
;
【题目3：每月及截止当月的答题情况】
select
start_month
,count(distinct uid) mau #月活用户数
,sum(new_day) month_add_uv #新增用户数
,max(sum(new_day)) over(order by start_month) #截止当月的单月最大新增用户数
,sum(sum(new_day)) over(order by start_month) #截止当月的累积用户数
from(
select
uid
,exam_id
,date_format(start_time,'%Y%m') start_month
,if(new_user_day=start_time,1,0) new_day #若用户的登录时间等于首次登录时间则定义为新用户，新用户被标记为1，其他标记为0
from (
select
uid
,exam_id
,start_time
,min(start_time) over(partition by uid) new_user_day #每一个用户的首次登录日期
from exam_record
) a
) a1
group by start_month
order by start_month
;
六、其他常用操作
1. 空值处理
【题目1：统计有未完成状态的试卷的未完成数和未完成率0级用户高难度试卷的平均用时和平均得分】
select
exam_id
,sum(if(submit_time is not null,0,1)) incomplete_cnt #未完成数
, round(sum(if(submit_time is not null,0,1))/count(start_time),3) incomplete_rate #未完成率
from exam_record
group by exam_id
having sum(if(submit_time is not null,0,1))>=1
;
【题目2：0级用户高难度试卷的平均用时和平均得分】
select
uid
,round(avg(score),0) avg_score #考试平均得分
,round(avg(diff_m),1) avg_time_took #考试平均用时
from (
select
a.uid
,c.exam_id
,ifnull(timestampdiff(minute,b.start_time,b.submit_time),c.duration) diff_m #未完成的默认试卷最大考试时长
,ifnull(b.score,0) score #未完成的默认试卷0分处理
from (
select
uid
,level
from user_info
where `level`='0' #每个0级用户
) a join (
select
uid
,exam_id
,start_time
,submit_time
,score
from exam_record
) b on a.uid=b.uid
join (
select
exam_id
,difficulty
,duration
from examination_info
where difficulty='hard' #所有的高难度试卷
) c on b.exam_id=c.exam_id
) a1
group by uid
;
2. 高级条件语句
【题目1：筛选限定昵称成就值活跃日期的用户】
select
a.uid
,a.nick_name
,a.achievement
from(
select
uid
,nick_name
,achievement
from user_info
where nick_name like '牛客%号' #昵称以『牛客』开头『号』结尾、成就值在1200~2500之间
and achievement between '1200' and '2500'
) a join (
select
uid
from (
select
uid
,start_time
,max(start_time) over(partition by uid) max_time #最近一次活跃答题在2021年9月
from exam_record
) a
where substr(max_time,1,7)='2021-09'
group by uid
union
select
uid
from (
select
uid
,submit_time
,max(submit_time) over(partition by uid) max_time #最近一次活跃作答试卷在2021年9月
from practice_record
) a
where substr(max_time,1,7)='2021-09'
group by uid
) b on a.uid=b.uid
;
【题目2：筛选昵称规则和试卷规则的作答记录】
RLIKE后面可以跟正则表达式
正则表达式" ^ [0-9]+$ "的意思：
1、字符^
意义：表示匹配的字符必须在最前边。
例如：^A不匹配“an A”中的‘A’，但匹配“An A”中最前面的‘A’。
2、字符$
意义：与^类似，匹配最末的字符。
例如：t$不匹配“eater”中的‘t’，但匹配“eat”中的‘t’。
3、字符[0-9]
意义：字符列表，匹配列出中的任一个字符。你可以通过连字符-指出字符范围。
例如：[abc]跟[a-c]一样。它们匹配“brisket”中的‘b’和“ache”中的‘c’。
4、字符+
意义：匹配+号前面的字符1次及以上。等价于{1,}。
例如：a+匹配“candy”中的‘a’和“caaaaaaandy”中的所有‘a’。
select
b.uid
,b.exam_id
,round(avg(score),0) avg_score
from (
select
uid
,nick_name
from user_info
where (nick_name rlike '^牛客[0-9]+号$') or (nick_name rlike '^[0-9]+$') #昵称以"牛客"+纯数字+"号"或者纯数字组成
) a join (
select
uid
,exam_id
,score
,submit_time
from exam_record
where submit_time is not null # 已完成的试卷
) b on a.uid=b.uid
join (
select
exam_id
,tag
from examination_info
where tag rlike '^[cC]' # 字母c开头的试卷类别（如C,C++,c#等）
) c on b.exam_id=c.exam_id
group by b.uid,b.exam_id
order by b.uid,avg_score
;
【题目3：根据指定记录是否存在输出不同情况】
with t1 as(
select
a.uid
,a.level
,count(start_time) total_cnt #每个用户的答题数
,count(start_time)-count(submit_time) incomplete_cnt #每个用户的未完成数
,ifnull(round((count(start_time)-count(submit_time))/count(start_time),3),0) incomplete_rate #每个用户的未完成率
from (
select
uid
,level
from user_info
) a left join (
select
uid
,exam_id
,start_time
,submit_time
from exam_record
) b on a.uid=b.uid
group by a.uid,a.level
) #命名为t1的子查询
select
uid
,incomplete_cnt
,incomplete_rate
from t1
where exists(select uid from t1 where level='0' and incomplete_cnt>2) #出现level=0且存在incomplete_cnt>2时
and level='0' #输出level=0的用户未完成数和未完成率
union all
select
uid
,incomplete_cnt
,incomplete_rate
from t1
where not exists(select uid from t1 where level='0' and incomplete_cnt>2) #没出现level=0且存在incomplete_cnt>2时
and total_cnt>=1 #输出所有有作答记录的用户的未完成数和未完成率
order by incomplete_rate
;
【题目4：各用户等级的不同得分表现占比】
select
level
,score_grade
,round(count(score_grade)/total_cnt,3) ratio # 各得分等级占比
from (
select
a.uid
,b.exam_id
,b.submit_time
,a.level
,b.score_grade
,count(b.score_grade) over(partition by a.level) total_cnt #各等级完成试卷总数
from (
select
uid
,level
from user_info
) a join (
select
uid
,exam_id
,case when score>=90 then '优'
when score>=75 then '良'
when score>=60 then '中'
when score<60 then '差'
else null end score_grade # 优良中差四个得分等级
,submit_time
,score
from exam_record
) b on a.uid=b.uid
where submit_time is not null # 在完成过的试卷中
) a1
group by level,score_grade
order by level desc,ratio desc
;
3. 限量查询
【题目1：注册时间最早的三个人】
select
uid
,nick_name
,register_time
from (
select
uid
,nick_name
,register_time
,row_number() over(order by register_time) rn
from user_info
) a
where rn<=3
;
【题目2：注册当天就完成了试卷的名单三页】
select
uid
,level
,register_time
,max_score
from (
select
b.uid
,b.exam_id
,b.submit_time
,a.register_time
,a.level
,b.score
,d.max_score
from (
select
uid
,level
,job
, register_time
from user_info
where job='算法' #求职方向为算法工程师
) a join (
select
uid
,exam_id
,submit_time
,score
from exam_record
) b on a.uid=b.uid
join (
select
exam_id
,tag
from examination_info
where tag='算法' #算法类试卷
) c on b.exam_id=c.exam_id
join (
select
uid
,max(score) max_score #参加过的所有考试最高得分
from exam_record
group by uid
) d on a.uid=d.uid
where date(a.register_time)=date(b.submit_time) #注册当天就完成了算法类试卷
) a1
order by max_score desc
LIMIT 6,3 #展示7-9行
;
4. 文本转换函数
【题目1：修复串列了的记录】
select
exam_id
,substring_index(tag,',',1) tag
,substring_index(substring_index(tag,',',2),',',-1) difficulty
,substring_index(tag,',',-1) duration
from examination_info
where tag like '%,%'
;
【题目2：对过长的昵称截取处理】
获取字符串长度
LENTH：获取字符串的字节数量，一个中文字符通常不止占用一个字节
CHAR_LENTH：获取字符数量，不管汉字、字母、数字都算一个字符
select
uid
,if(char_length(nick_name)>13,concat(substr(nick_name,1,10),'...'),nick_name) nick_name
from user_info
where char_length(nick_name)>10
;
【题目3：大小写混乱时的筛选统计】
with t_tag_count as (
select
tag
,count(start_time) answer_cnt
from (
select
exam_id
,tag
from examination_info
) a join (
select
exam_id
,start_time
from exam_record
) b on a.exam_id=b.exam_id
group by tag
)
select
a.tag
,b.answer_cnt
from t_tag_count a
join t_tag_count b
on upper(a.tag) = b.tag and a.tag != b.tag and a.answer_cnt < 3
;
文章来源:https://blog.csdn.net/myy12456789/article/details/135071291
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本文来自互联网用户投稿，该文观点仅代表作者本人，不代表本站立场。本站仅提供信息存储空间服务，不拥有所有权，不承担相关法律责任。 如若内容造成侵权/违法违规/事实不符，请联系我的编程经验分享网邮箱：chenni525@qq.com进行投诉反馈，一经查实，立即删除！
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