Group data into separate partitions based on identified NULL values [closed] - sql

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I'm looking to break a partition based on a NULL value as seen below in the 'GroupNumber' column. The purpose is that within window function statements, there isn't another identifier within my dataset that could break the groups apart (e.g. seen below to derive the "GroupNumber" column). The point is the create this "GroupNumber" column. Is there a way to break/reset the partition when a NULL value exists (ordered by date DESC)? Note: There can be multiple NULL instances for each partition. Any help is appreciated.
METHODOLOGY:
Create bit flag column to represent NULL values.
Use rolling sum (sorted by date DESC) to create these groups. This is a great method because at each observed NULL value, the "GROUP" field would increment dynamically. This would allow for aggregate calculations using this new field as a partition.
EXAMPLE SETUP:
IF OBJECT_ID('tempdb..#GroupNULL', 'U') IS NOT NULL
DROP TABLE #GroupNULL
CREATE TABLE #GroupNULL
([ID] INT NOT NULL,
[Date] date NULL,
[Number] INT NULL)
INSERT INTO #GroupNULL (ID, Date, Number) VALUES (1001, '8/12/2018', 35)
INSERT INTO #GroupNULL (ID, Date, Number) VALUES (1001, '8/11/2018', 27)
INSERT INTO #GroupNULL (ID, Date, Number) VALUES (1001, '8/10/2018', 7)
INSERT INTO #GroupNULL (ID, Date, Number) VALUES (1001, '8/9/2018', 18)
INSERT INTO #GroupNULL (ID, Date, Number) VALUES (1001, '8/8/2018', NULL)
INSERT INTO #GroupNULL (ID, Date, Number) VALUES (1001, '8/7/2018', 3)
INSERT INTO #GroupNULL (ID, Date, Number) VALUES (1001, '8/6/2018', 42)
INSERT INTO #GroupNULL (ID, Date, Number) VALUES (1001, '8/5/2018', 16)
INSERT INTO #GroupNULL (ID, Date, Number) VALUES (1001, '8/4/2018', 9)
INSERT INTO #GroupNULL (ID, Date, Number) VALUES (1001, '8/3/2018', NULL)
FURTHER CONTEXT: I would like to partition this dataset into 2 groups, with the first NULL value (ordered by date DESC) to be the first value of the group.

Answer 1

Here's an example that should get you pretty close. It uses windowing aggregates to add up the number of NULLs you have seen in a given order of the table as returned in a query. This works on recent versions of SQL Server/SQL Azure (SQL Server 2012+ I believe)
drop table t1
create table t1 (col1 int, col2 int)
insert into t1(col1, col2) values (1, 1)
insert into t1(col1, col2) values (1, 10)
insert into t1(col1, col2) values (2, NULL)
insert into t1(col1, col2) values (2, 10)
insert into t1(col1, col2) values (3, 2)
insert into t1(col1, col2) values (3, NULL)
SELECT
col1,
col2,
IsBoundary,
SUM(IsBoundary) OVER(ORDER BY col1, col2 ROWS UNBOUNDED PRECEDING) + 1 as GroupNumber
FROM
(
SELECT
col1,
col2,
CASE WHEN col2 is NULL then 1 ELSE 0 END as IsBoundary
FROM
t1
) A
ORDER BY col1, col2
col1 col2 IsBoundary GroupNumber
----------- ----------- ----------- -----------
1 1 0 1
1 10 0 1
2 NULL 1 2
2 10 0 2
3 NULL 1 3
3 2 0 3

Answer 2

SETUP
IF OBJECT_ID('tempdb..#GroupNULL', 'U') IS NOT NULL
DROP TABLE #GroupNULL
CREATE TABLE #GroupNULL
([ID] INT NOT NULL,
[Date] date NULL,
[Number] INT NULL)
INSERT INTO #GroupNULL (ID, Date, Number) VALUES (1001, '8/12/2018', 35)
INSERT INTO #GroupNULL (ID, Date, Number) VALUES (1001, '8/11/2018', 27)
INSERT INTO #GroupNULL (ID, Date, Number) VALUES (1001, '8/10/2018', 7)
INSERT INTO #GroupNULL (ID, Date, Number) VALUES (1001, '8/9/2018', 18)
INSERT INTO #GroupNULL (ID, Date, Number) VALUES (1001, '8/8/2018', NULL)
INSERT INTO #GroupNULL (ID, Date, Number) VALUES (1001, '8/7/2018', 3)
INSERT INTO #GroupNULL (ID, Date, Number) VALUES (1001, '8/6/2018', 42)
INSERT INTO #GroupNULL (ID, Date, Number) VALUES (1001, '8/5/2018', 16)
INSERT INTO #GroupNULL (ID, Date, Number) VALUES (1001, '8/4/2018', 9)
INSERT INTO #GroupNULL (ID, Date, Number) VALUES (1001, '8/3/2018', NULL)
SOLUTION
SELECT x.*,
SUM(Flagged) OVER(ORDER BY ID, Date DESC ROWS UNBOUNDED PRECEDING) AS [GroupNumber]
FROM
(SELECT *,
CASE WHEN LAG(Number) OVER(PARTITION BY ID ORDER BY Date DESC) IS NULL
THEN 1
ELSE 0
END AS [Flagged]
FROM #GroupNULL) x
ID Date Number Flagged GroupNumber
----------- ---------- ----------- ----------- -----------
1001 2018-08-12 35 1 1
1001 2018-08-11 27 0 1
1001 2018-08-10 7 0 1
1001 2018-08-09 18 0 1
1001 2018-08-08 NULL 0 1
1001 2018-08-07 3 1 2
1001 2018-08-06 42 0 2
1001 2018-08-05 16 0 2
1001 2018-08-04 9 0 2
1001 2018-08-03 NULL 0 2