SQL查询至少连续n天登录的用户
时间：2022-03-21 09:28:17 | 栏目：Mysql | 点击：次
以连续3天为例，使用工具：MySQL。
1.创建SQL表：
create table if not exists orde(id varchar(10),date datetime,orders varchar(10));
insert into orde values('1' , '2019/1/1',10 );
insert into orde values('1' , '2019/1/2',109 );
insert into orde values('1' , '2019/1/3',150 );
insert into orde values('1' , '2019/1/4',99);
insert into orde values('1' , '2019/1/5',145);
insert into orde values('1' , '2019/1/6',1455);
insert into orde values('1' , '2019/1/7',199);
insert into orde values('1' , '2019/1/8',188 );
insert into orde values('4' , '2019/1/1',10 );
insert into orde values('2' , '2019/1/2',109 );
insert into orde values('3' , '2019/1/3',150 );
insert into orde values('4' , '2019/1/4',99);
insert into orde values('5' , '2019/1/5',145);
insert into orde values('6' , '2019/1/6',1455);
insert into orde values('7' , '2019/1/7',199);
insert into orde values('8' , '2019/1/8',188 );
insert into orde values('9' , '2019/1/1',10 );
insert into orde values('9' , '2019/1/2',109 );
insert into orde values('9' , '2019/1/3',150 );
insert into orde values('9' , '2019/1/4',99);
insert into orde values('9' , '2019/1/6',145);
insert into orde values('9' , '2019/1/9',1455);
insert into orde values('9' , '2019/1/10',199);
insert into orde values('9' , '2019/1/13',188 );
查看数据表：
2.使用row_number() over() 排序函数计算每个id的排名，SQL如下：
select *,row_number() over(partition by id order by date ) 'rank' from orde where orders is not NULL;
查看数据表:
3.将date日期字段减去rank排名字段，SQL如下：
select *,DATE_SUB(a.date,interval a.rank day) 'date_sub' from( select *,row_number() over(partition by id order by date ) 'rank' from orde where orders is not NULL ) a;
查看数据：
4.根据id和date分组并计算分组后的数量(count)、计算最早登录和最晚登录的时间，SQL如下：
select b.id,min(date) 'start_time',max(date) 'end_time',count(*) 'date_count' from( select *,DATE_SUB(a.date,interval a.rank day) 'date_sub' from( select *,row_number() over(partition by id order by date ) 'rank' from orde where orders is not NULL ) a ) b group by b.date_sub,id having count(*) >= 3 ;
查看数据：
参考资料：