大數據 ODS&DWD&DIM-SQL分享

大數據 ODS&DWD&DIM-SQL分享 需求

思路一：等差數列

斷2天、3天，嵌套太多

1.1 開窗，按照 id 分組，同時按照 dt 排序，求 Rank

-- linux 中空格不能用　tab 鍵
select id,dt,rank() over(partition by id order by dt) rk from tx;

1.2 將每行日期減去RK值，如果之前是連續的日期，則相減之後為相同日期

z: 等差
(x1+z)-(y1+z)=x1-y1

select id,dt,date_sub(dt,rk) flg 
from (select id,dt,rank() over(partition by id order by dt) rk from tx) t1;

斷一天的數據，flag 變成了連續

1.3 計算絕對連續的天數

select id,flag,count(*) days
from (
  select id,dt,date_sub(dt,rk) flg
  from (select id,dt,rank() over(partition by id order by dt) rk from tx) t1;
)t2 group by id,flag;

1.4 再計算連續問題

select id,flag,days,rank() over(partition by id order by flag) newFlag
from t3;

1.5 將 flag 減去 newflag

select id,days,date_sub(flag,newFlag) flag
from t4;t5

1.6 計算每個用戶連續登錄的天數，斷一天也算

select id,sum(days)+count(1) days
from t5
group by id,flag;[t6]

1.7 計算最大連續天數

select id,max(days)
from t6
group by id;

準後再-1

思路二

2.1 將上一行數據下移

--下移預設值，一般給 1970-01-01，上移預設值一般 9999-01-01
select id,dt,lag(dt,1,'1970-01-01') over(partition by id order by dt) lagDt
from tx; t1

2.2 將當前行日期減去下移的日期

select id,dt,datediff(dt,lagDt) dtDiff
from t1; t2

執行

select id,dt,datediff(dt,lagDt) dtDiff
from (
select id,dt,lag(dt,1,'1970-01-01') over(partition by id order by dt) lagDt
from tx) t1;

每碰到一個 >2 的就分組 + 1

2.3 分組

select id,dt,sum(if(dtDiff>2,1,0)) over(partition by id order by dt) flag
from t2; t3

select id,dt,sum(if(dtDiff>2,1,0)) over(partition by id order by dt) flag
from (
select id,dt,datediff(dt,lagDt) dtDiff
from (
select id,dt,lag(dt,1,'1970-01-01') over(partition by id order by dt) lagDt
from tx) t1
) t2;

select id,flag,datediff(max(dt),min(dt))+1
from t3
group by id,flag;

帶入執行

--斷3天把2改成3，斷4天把2改成4
select id,flag,datediff(max(dt),min(dt))+1
from (
select id,dt,sum(if(dtDiff>2,1,0)) over(partition by id order by dt) flag
from (
select id,dt,datediff(dt,lagDt) dtDiff
from (
select id,dt,lag(dt,1,'1970-01-01') over(partition by id order by dt) lagDt
from tx) t1
) t2
)t3
group by id,flag;

2.3 求分組後的最大值

HiveOnSpark: 有個BUG， datediff over 子查詢 => null point
解決方案：

1. 換MR引擎
2. 將時間欄位由 String 類型改成 Date 類型

https://www.bilibili.com/video/BV1Ju411o7f8/?p=69