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I have the data set as below: 

EMP_NAME   MGRNAME    STATUS    MODIFIED_DATE 
---------------------------------------------------
Amy        John       ACTIVE    01/15/2012 00:00:00 
Amy        Ken        INSERVICE 06/08/2000 00:00:00 
Amy        Tom        INACTIVE  04/02/2010 00:00:00 
Ron        David      ACTIVE    01/15/2008 00:00:00 
Keith      Jack       INACTIVE  08/10/2005 00:00:00 
Keith      Cat        INACTIVE  04/30/2008 00:00:00 
Keith      Ken        INACTIVE  02/04/2010 00:00:00
Mary       Stephen    INACTIVE  10/18/2010 00:00:00

Now, i should identify the duplicate rows based on the below conditions:

  • If an Emp has 1 Mgr tagged, then we should not consider the same. Ex:- Ron, Mary
  • If an Emp has been tagged to multiple Managers, then we need to check if he is tagged to any of the manager as ACTIVE , then we should not consider the same. Fetch those records whose status is <> ACTIVE for that Emp. Ex:- For Amy, we should exclude the record with ACTIVE status. We should fetch the records with INSERVICE and INACTIVE
  • If an Emp has been tagged to multiple Managers, but he is in INACTIVE status with all of them, then leave the max(MODIFIED_DATE) record and fetch the remaining records Ex:- For Keith, as both the Mgr records Status is INACTIVE, fetch the (MODIFIED_DATE) records which are 08/10/2005 00:00:00 and 04/30/2008 00:00:00

The final output should look like below: 

EMP_NAME   MGRNAME     STATUS      MODIFIED_DATE 
------------------------------------------------------
Amy        Ken         INSERVICE   06/08/2000 00:00:00 
Amy        Tom         INACTIVE    04/02/2010 00:00:00 
Keith      Jack        INACTIVE    08/10/2005 00:00:00 
Keith      Cat         INACTIVE    04/30/2008 00:00:00
4

1 回答 1

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尝试这个：

SELECT EMP_NAME ,  MGRNAME ,   STATUS  ,  MODIFIED_DATE
FROM (
SELECT your_table.*,
rank() over (partition BY EMP_NAME ORDER BY decode(STATUS,'ACTIVE', to_date('31129999', 'ddmmyyyy'), MODIFIED_DATE) DESC ) r FROM your_table
) t
WHERE r > 1

这是一个小提琴

于 2012-07-01T06:06:25.570 回答