SQL rotate rows to columns...dynamic number of rows [duplicate] - sql

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SQL Server dynamic PIVOT query?
I have a dataset that has the below structure.
CREATE TABLE #TempTable
(
Measure_ID INT,
measurement DECIMAL(18, 4)
)
INSERT INTO #TempTable
VALUES
(1,2.3)
,(1,3.4)
,(1,3.3)
,(2,3)
,(2,2.3)
,(2,4.0)
,(2,4.5)
I need to produce output that will look like this.
1,2.3,3.4,3.3
2,3,2.3,4.0,4.5
Basically its a pivot on Measure_ID. Unfortunately, there can be an unlimited number of measure_id's. So Pivot is out.
I'm hoping to avoid CURSORS, but will if that turns out to be the best approach.

Answer 1

If you have an unknown number of values, then you can use a PIVOT with dynamic SQL:
DECLARE #cols AS NVARCHAR(MAX),
#query AS NVARCHAR(MAX)
select #cols = STUFF((SELECT distinct ','
+ QUOTENAME('Measurement_' + cast(rn as varchar(10)))
from temptable
cross apply
(
select row_number() over(partition by measure_id order by measurement) rn
from temptable
) x
FOR XML PATH(''), TYPE
).value('.', 'NVARCHAR(MAX)')
,1,1,'')
set #query = 'SELECT measure_id, ' + #cols + ' from
(
select measure_id, measurement,
''Measurement_''
+ cast(row_number() over(partition by measure_id order by measurement) as varchar(10)) val
from temptable
) x
pivot
(
max(measurement)
for val in (' + #cols + ')
) p '
execute(#query)
See SQL Fiddle With Demo
If you have a known number of values, then you can hard-code the values, similar to this:
SELECT measure_id, [Measurement_1], [Measurement_2],
[Measurement_3], [Measurement_4]
from
(
select measure_id, measurement,
'Measurement_'
+ cast(row_number() over(partition by measure_id order by measurement) as varchar(10)) val
from temptable
) x
pivot
(
max(measurement)
for val in ([Measurement_1], [Measurement_2],
[Measurement_3], [Measurement_4])
) p
See SQL Fiddle With Demo
Both queries will produce the same results:
MEASURE_ID | MEASUREMENT_1 | MEASUREMENT_2 | MEASUREMENT_3 | MEASUREMENT_4
==========================================================================
1 | 2.3 | 3.3 | 3.4 | (null)
2 | 2.3 | 3 | 4 | 4.5