I am struggling with a SQL query and while I have looked at many similar answers none of them quite fit my situation. I have a dataset as below:
Date1 Amount 1 Index Date2 Type Supplier
31/03/2018 410000.00 17 16/04/2018 06:27 102 A
31/03/2018 410000.00 17 16/04/2018 06:31 102 B
31/03/2018 400000.00 2 16/04/2018 06:37 102 A
31/03/2018 400000.00 2 16/04/2018 06:38 102 B
30/06/2018 0 20 04/07/2018 08:23 202 A
30/06/2018 0 20 04/07/2018 08:23 202 B
30/06/2018 412000.00 20 06/07/2018 12:46 102 A
30/06/2018 412000.00 20 06/07/2018 12:47 102 B
30/06/2018 442000.00 100 16/07/2018 06:27 102 A
30/06/2018 442000.00 100 16/07/2018 06:31 102 B
For each Date1 where there are multiple rows with the same Type, I only want the rows where the index matches the index of the maximum Date2 so I want this output:
Date1 Amount 1 Index Date2 Type Supplier
31/03/2018 400000.00 2 16/04/2018 06:37 102 A
31/03/2018 400000.00 2 16/04/2018 06:38 102 B
30/06/2018 0 20 04/07/2018 08:23 202 A
30/06/2018 0 20 04/07/2018 08:23 202 B
30/06/2018 442000.00 100 16/07/2018 06:27 102 A
30/06/2018 442000.00 100 16/07/2018 06:31 102 B
I feel it should be possible with some form of conditional MAX() OVER (PARTITION BY) but for the life of me I can't work out how to do it.
Use LAST_VALUE (Transact-SQL) analytic function together with a subquery.
The below working example is for Oracle (I prefer Oracle because I always have a problem with converting dates on SQLServer), but the idea of the query is the same, the syntax also is the same:
Demo: http://www.sqlfiddle.com/#!4/004ce7/19
SELECT * FROM (
SELECT t.* ,
last_value( "INDEX" ) OVER
( partition by date1, "TYPE" order by date2
ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING) xx
FROM table1 t
) x
WHERE xx = "INDEX"
ORDER BY date1;
| DATE1 | AMOUNT1 | INDEX | DATE2 | TYPE | SUPPLIER | XX |
|----------------------|---------|-------|-----------------------|------|----------|-----|
| 2018-03-31T00:00:00Z | 400000 | 2 | 2018-04-16 06:37:00.0 | 102 | A | 2 |
| 2018-03-31T00:00:00Z | 400000 | 2 | 2018-04-16 06:38:00.0 | 102 | B | 2 |
| 2018-06-30T00:00:00Z | 442000 | 100 | 2018-07-16 06:27:00.0 | 102 | A | 100 |
| 2018-06-30T00:00:00Z | 442000 | 100 | 2018-07-16 06:31:00.0 | 102 | B | 100 |
| 2018-06-30T00:00:00Z | 0 | 20 | 2018-07-04 08:23:00.0 | 202 | B | 20 |
| 2018-06-30T00:00:00Z | 0 | 20 | 2018-07-04 08:23:00.0 | 202 | A | 20 |
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