nop77svk - 1 year ago 155

SQL Question

A question here, on SO, asked for resolving a rather common use case of filling in "missing" (based on defined criteria of being missing) values with non-"missing" values from "previous" (based on defined criteria of ordering) rows.

My usual approach to this problem is to

- remap (/
`decode`

) the "missing" values to NULLs,`case`

- use the analytic function on the non-"missing"-value, with
`last_value()`

and the window of all preceding rows up to the current row in the defined ordering.`ignore nulls`

I.e., given a (taken from the original post) input set of rows

`my_table`

`ORD COL1 COL2 COL3 COL4`

--- ---- ---- ---- ----

1 A 0 1 5

2 B 0 4 0

3 C 2 0 0

4 D 0 0 0

5 E 3 5 0

6 F 0 3 0

7 G 0 3 1

8 A 0 1 5

9 E 3 5 0

..., an ordering of

`order by ord asc`

`case when colX <= 0 then null else colX end`

`X`

`select X.ord, X.col1,`

nvl(last_value(case when col2 > 0 then col2 end) ignore nulls over (order by ord), col2) as col2,

nvl(last_value(case when col3 > 0 then col3 end) ignore nulls over (order by ord), col3) as col3,

nvl(last_value(case when col4 > 0 then col4 end) ignore nulls over (order by ord), col4) as col4

from my_table X

order by ord;

... would yield the desired result of ...

`ORD COL1 COL2 COL3 COL4`

--- ---- ---- ---- ----

1 A 0 1 5

2 B 0 4 5

3 C 2 4 5

4 D 2 4 5

5 E 3 5 5

6 F 3 3 5

7 G 3 3 1

8 A 3 1 5

9 E 3 5 5

Lukas Eder proposed a beautiful alternative solution with the

`model`

`model`

`SQL MODEL ORDERED`

`n`

`n+1`

One of Lukas's comments also mentioned the possibility of using the

`match_recognize`

I'm offering a small bounty to the most elegant

`match_recognize`

`with`

`pivot`

`unpivot`

`model`

`match_recognize`

`my_table`

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Answer Source

I don't think you can accomplish the result using pure `MATCH_RECOGNIZE`

clause. Simply because the values `col2`

, `col3`

, `col4`

are independent on each other but the pattern is evaluated per entire row. So if multiple symbols can be matched (multiple columns have zero or non-zero values in your case) only the first one is matched as classifier and the others are ignored.

For single column there is simple solution:

```
SELECT
ORD, COL1, COL2R COL2
FROM
my_table
MATCH_RECOGNIZE (
ORDER BY ORD
MEASURES
NVL(LAST(V2.COL2), 0) AS COL2R
ALL ROWS PER MATCH
PATTERN ((V20*V2+V20*)+)
DEFINE
V2 AS V2.COL2 > 0,
V20 AS V20.COL2 = 0
)
```

Anyway, analytic functions are definitely the best option in your case. Both `MODEL`

and `MATCH_RECOGNIZE`

clauses are meant to solve different problems where analytic functions will not help and although there are well optimized both are more heavy weight than analytic functions.

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