有日志如下，请写出代码求得所有用户和活跃用户的总数及平均年龄。（活跃用户指连续两天都有访问记录的用户）

日期    用户    年龄

2019-02-11,test_1,23

2019-02-11,test_2,19

2019-02-11,test_3,39

2019-02-11,test_1,23

2019-02-11,test_3,39

2019-02-11,test_1,23

2019-02-12,test_2,19

2019-02-13,test_1,23

2019-02-15,test_2,19

2019-02-16,test_2,19

CREATE TABLE user_age (
dt string,
user_id string, age INT )
ROW format delimited FIELDS TERMINATED BY ',';

1）按照日期以及用户分组，按照日期排序并给出排名

selectdt,user_id,min(age) age,rank() over(partition by user_id order by dt) rk
fromuser_age
group bydt,user_id;t1

2）计算日期及排名的差值

selectuser_id,age,date_sub(dt,rk) flagfromt1;t2

3）过滤出差值大于等于2的，即为连续两天活跃的用户

selectuser_id,min(age) agefromt2group byuser_id,flaghavingcount(*)>=2;t3

4）对数据进行去重处理（一个用户可以在两个不同的时间点连续登录），例如：a用户在1月10号1月11号以及1月20号和1月21号4天登录。

selectuser_id,min(age) agefromt3group byuser_id;t4

5）计算活跃用户（两天连续有访问）的人数以及平均年龄

selectcount(*) ct,cast(sum(age)/count(*) as decimal(10,2))from t4;

6）对全量数据集进行按照用户去重

selectuser_id,min(age) agefromuser_agegroup byuser_id;t5

7）计算所有用户的数量以及平均年龄

selectcount(*) user_count,cast((sum(age)/count(*)) as decimal(10,1))fromt5;

8）将第5步以及第7步两个数据集进行union all操作

select0 user_total_count,0 user_total_avg_age,count(*) twice_count,cast(sum(age)/count(*) as decimal(10,2)) twice_count_avg_agefrom(selectuser_id,min(age) agefrom(selectuser_id,min(age) agefrom(selectuser_id,age,date_sub(dt,rk) flagfrom(selectdt,user_id,min(age) age,rank() over(partition by user_id order by dt) rkfromuser_agegroup bydt,user_id)t1)t2group byuser_id,flaghavingcount(*)>=2)t3group byuser_id)t4union allselectcount(*) user_total_count,cast((sum(age)/count(*)) as decimal(10,1)),0 twice_count,0 twice_count_avg_agefrom(selectuser_id,min(age) agefromuser_agegroup byuser_id)t5;t6

9）计算最终结果

selectsum(user_total_count),sum(user_total_avg_age),sum(twice_count),sum(twice_count_avg_age)from(select0 user_total_count,0 user_total_avg_age,count(*) twice_count,cast(sum(age)/count(*) as decimal(10,2)) twice_count_avg_agefrom(selectuser_id,min(age) agefrom(selectuser_id,min(age) agefrom(selectuser_id,age,date_sub(dt,rk) flagfrom(selectdt,user_id,min(age) age,rank() over(partition by user_id order by dt) rkfromuser_agegroup bydt,user_id)t1)t2group byuser_id,flaghavingcount(*)>=2)t3group byuser_id)t4union allselectcount(*) user_total_count,cast((sum(age)/count(*)) as decimal(10,1)),0 twice_count,0 twice_count_avg_agefrom(selectuser_id,min(age) agefromuser_agegroup byuser_id)t5)t6;