I have Assignment Table like this
EMPLID | RCD | COMPANY | EFFDT | SALARY
---------------------------------------------------
100 | 0 | xyz | 1/1/2000 | 1000
100 | 0 | xyz | 1/15/2000 | 1100
100 | 0 | xyz | 1/31/2000 | 1200
100 | 0 | ggg | 2/15/2000 | 1500
100 | 1 | abc | 3/1/2000 | 2000
100 | 1 | abc | 4/1/2000 | 2100
I need a counter which should increase whenever RCD or Company combination changes and it should be order by effdt.
EMPLID | RCD | COMPANY | EFFDT | SALARY | COUNTER
-------|-----|---------|---------------|-------------|----------
100 | 0 | xyz | 1/1/2000 | 1000 | 1
100 | 0 | xyz | 1/15/2000 | 1100 | 1
100 | 0 | xyz | 1/31/2000 | 1200 | 1
100 | 0 | ggg | 2/15/2000 | 1500 | 2
100 | 1 | abc | 3/1/2000 | 2000 | 3
100 | 1 | abc | 4/1/2000 | 2100 | 3
I tried Dense_Rank function with order by EMPLID , RCD , COMPANY , It provides me Counter but its not in order by effdt.
SELECT EMPLID,RCD,COMPANY,EFFDT,
DENSE_RANK() over (order by EMPLID , RCD , COMPANY) AS COUNTER
FROM ASSIGNMENT ;
Order by EFFDT , Gives incremental counter 1 ... 6
SELECT EMPLID,RCD,COMPANY,EFFDT,
DENSE_RANK() over (order by EFFDT) AS COUNTER
FROM ASSIGNMENT;
Kindly help me to find out what I am missing.
This should work - with the clarification that a combination of rcd and company should keep the same "counter" even if it appears in non-consecutive periods. I added to more rows to the test data to make sure I get the correct result.
Like Serg's solutions (which answer a different question), the solution does one pass over the base data, and then a second pass over the results of the first pass (all in memory, so it should be relatively fast). There's no way around that - this requires two different analytic functions where one depends on the results of the other, and nested analytic functions are not allowed. (This part of the answer addresses a comment by the OP to the Answer by Serg.)
with
test_data ( emplid, rcd, company, effdt, salary ) as (
select 100, 0, 'xyz', to_date('1/1/2000' , 'mm/dd/yyyy'), 1000 from dual union all
select 100, 0, 'xyz', to_date('1/15/2000', 'mm/dd/yyyy'), 1100 from dual union all
select 100, 0, 'xyz', to_date('1/31/2000', 'mm/dd/yyyy'), 1200 from dual union all
select 100, 0, 'ggg', to_date('2/15/2000', 'mm/dd/yyyy'), 1500 from dual union all
select 100, 1, 'abc', to_date('3/1/2000' , 'mm/dd/yyyy'), 2000 from dual union all
select 100, 1, 'abc', to_date('4/1/2000' , 'mm/dd/yyyy'), 2100 from dual union all
select 100, 0, 'xyz', to_date('5/1/2000' , 'mm/dd/yyyy'), 2200 from dual union all
select 100, 1, 'ggg', to_date('8/15/2000', 'mm/dd/yyyy'), 2300 from dual
)
-- end of test data; the actual solution (SQL query) begins below this line
select emplid, rcd, company, effdt, salary,
dense_rank() over (partition by emplid order by min_dt) as counter
from ( select emplid, rcd, company, effdt, salary,
min(effdt) over (partition by emplid, rcd, company) as min_dt
from test_data )
order by effdt -- ORDER BY is optional
;
EMPLID RCD COM EFFDT SALARY COUNTER
---------- ---------- --- ------------------- ---------- ----------
100 0 xyz 2000-01-01 00:00:00 1000 1
100 0 xyz 2000-01-15 00:00:00 1100 1
100 0 xyz 2000-01-31 00:00:00 1200 1
100 0 ggg 2000-02-15 00:00:00 1500 2
100 1 abc 2000-03-01 00:00:00 2000 3
100 1 abc 2000-04-01 00:00:00 2100 3
100 0 xyz 2000-05-01 00:00:00 2200 1
100 1 ggg 2000-08-15 00:00:00 2300 4
8 rows selected