一、求出場率與出廠次數

1、有如下資料：（建表語句+sql查詢）

id names

1 aa,bb,cc,dd,ee

2 aa,bb,ff,ww,qq

3 aa,cc,rr,yy

4 aa,bb,dd,oo,pp

2、求英雄的出場排名top3的出場次數及出場率

create table if not exists t_names(

id int,

names array

)

row format delimited

fields terminated by ‘\t’

collection items terminated by ‘,’

;

 
select *

from (

select name,cc,cc / (sum(cc) over()) as ccl,

rank() over(sort by cc desc) as rk

from (

select

name,

count(1) as cc

from t_names lateral view explode(names) tt as name

group by

name

) a

) aa

where aa.rk <= 3

;

二、求通話時長

1、有如下通話記錄：

Zhangsan Wangwu 01:01:01

Zhangsan Zhaoliu 
 
00:11:21

Zhangsan Yuqi 00:19:01

Zhangsan Jingba 00:21:01

Zhangsan Wuxi 01:31:17

Wangwu Zhaoliu 00:51:01

Wangwu Zhaoliu 01:11:19

Wangwu Yuqi 00:00:21

Wangwu Yuqi 00:23:01

Yuqi Zhaoliu 01:18:01

Yuqi Wuxi 00:18:00

Jingba Wangwu 00:01:01

Jingba Wangwu 00:00:06

Jingba Wangwu 00:02:04

Jingba Wangwu 00:02:54

Wangwu Yuqi 01:00:13

Wangwu Yuqi 
 
00:01:01

Wangwu Zhangsan 00:01:01

2、統計兩個人的通話總時長（使用者之間互相通話的時長）

create table relations(

fromstr string,

tostr string,

time string

)

row format delimited

fields terminated by ’ ’

;

select

fromstr,

tostr,

sum(duration) as durations

from (

Select

Case when fromstr >= tostr then fromstr else tostr end fromstr,

Case when fromstr >= tostr then tostr else fromstr end tostr,

Split(time,’:’)[0] * 60 * 60 + Split(time,’:’)[1] * 60 + Split(time,’:’)[2] duration

from relations

) a

group by fromstr,tostr

;

三、求出每個店鋪的當月銷售額和累計到當月的總銷售額

1、有如下銷售資料：（建表語句+sql查詢）

店鋪 月份 金額

a,01,150

a,01,200

b,01,1000

b,01,800

c,01,250

c,01,220

b,01,6000

a,02,2000

a,02,3000

b,02,1000

b,02,1500

c,02,350

c,02,280

a,03,350

a,03,250

2、編寫Hive的HQL語句求出每個店鋪的當月銷售額和累計到當月的總銷售額

create table t_store(

name string,

months int,

money int

)

row format delimited fields terminated by “,”;

select name,months,amoney,sum(amoney) over(distribute by name sort by months asc rows between unbounded preceding and current row) as totalmomey

from (

Select name,months,sum(money) as amoney

From t_store

Group by name,months

) a

；

四、統計amt連續3個月，環比增長>50%的user

user_id month amt
1,20170101,100
3,20170101,20
4,20170101,30
1,20170102,200
2,20170102,240
3,20170102,30
4,20170102,2
1,20170101,180
2,20170101,250
3,20170101,30
4,20170101,260
…
…

select user_id
from(
select
user_id,month,mon_amt,pre_mon_amt,
sum(case when ((mon_amt - pre_mon_amt) / pre_mon_amt * 100) > 50
and datediff(to_date(month,‘yyyymm’),to_date(pre2_month,‘yyyymm’),‘mm’) = 2
then 1
else 0 end) over(partition by user_id order by month asc rows between current row and 2 following) as flag
from (
select
user_id,
substr(month,0,6) as month,
sum(amt) as mon_amt,
lag(sum(amt),1,0.00001) over(partition by user_id order by substr(month,0,6) asc ) as pre_mon_amt,
substr(lag(substr(month,0,6),2,‘199001’) over(partition by user_id order by substr(month,0,6) asc),0,6) as pre_2_mon
from amt
group by user_id,substr(month,0,6)
) t1
) t2
where t2.flag >=3;