February 28, 2013 at 2:23 am
Hi Please help me out in this scenario.
Table
IDNAME
1a
1b
1c
1d
2e
2f
3g
3h
3i
4j
5K
5L
5m
5N
5O
5P
required output
id name1name 2name3name4name 5name6
1abc
2ef
3ghi
4j
5klmnop
i need a query which gives the out put
February 28, 2013 at 3:58 am
Using this sample data: -
IF object_id('tempdb..#testEnvironment') IS NOT NULL
BEGIN
DROP TABLE #testEnvironment;
END;
SELECT ID, NAME
INTO #testEnvironment
FROM (VALUES(1,'a'),(1,'b'),(1,'c'),(1,'d'),(2,'e'),(2,'f'),
(3,'g'),(3,'h'),(3,'i'),(4,'j'),(5,'K'),(5,'L'),
(5,'m'),(5,'N'),(5,'O'),(5,'P')
)a(ID, NAME);
Then something like this: -
DECLARE @sql NVARCHAR(MAX);
SELECT @sql='SELECT ID,'+CHAR(13)+CHAR(10)+
STUFF((SELECT ','+CHAR(13)+CHAR(10)+'NULLIF(MAX(CASE WHEN POS = '+CAST(POS AS VARCHAR(3))+' THEN NAME ELSE '+CHAR(39)+CHAR(39)+' END),'+CHAR(39)+CHAR(39)+
') AS '+QUOTENAME('NAME'+CAST(POS AS VARCHAR(3)))
FROM (SELECT DISTINCT ROW_NUMBER() OVER(PARTITION BY ID ORDER BY NAME)
FROM #testEnvironment
)a(POS)
FOR XML PATH(''), TYPE).value('.','VARCHAR(MAX)'),1,3,'')+CHAR(13)+CHAR(10)+'FROM (SELECT ID, NAME, ROW_NUMBER() OVER(PARTITION BY ID ORDER BY NAME)'+CHAR(13)+CHAR(10)+
SPACE(6)+'FROM #testEnvironment'+CHAR(13)+CHAR(10)+SPACE(6)+')a(ID,NAME,POS)'+CHAR(13)+CHAR(10)+'GROUP BY ID;';
EXECUTE sp_executesql @sql;
Which returns: -
ID NAME1 NAME2 NAME3 NAME4 NAME5 NAME6
----------- ----- ----- ----- ----- ----- -----
1 a b c d NULL NULL
2 e f NULL NULL NULL NULL
3 g h i NULL NULL NULL
4 j NULL NULL NULL NULL NULL
5 K L m N O P
February 28, 2013 at 6:53 am
Using the above sample from Cadavre to load the data here is an alternative. Admittedly you will need to prejudge the possible number of options and pad out the sql but this code can be used in views as it isnt dynamic:
Select ID
,[Name1] = [1]
,[Name2] = [2]
,[Name3] = [3]
,[Name4] = [4]
,[Name5] = [5]
,[Name6] = [6]
,[Name7] = [7]
,[Name8] = [8]
from (
select distinct
ID
,Name
,RID = Dense_Rank() OVER(PARTITION BY ID ORDER BY NAME)
from #testEnvironment
) as XX
pivot ( min(Name) for RID in ( [1],[2],[3],[4],[5],[6],[7],[8] )
) as pvt
order by ID
February 28, 2013 at 7:00 am
Steve JP (2/28/2013)
Using the above sample from Cadavre to load the data here is an alternative. Admittedly you will need to prejudge the possible number of options and pad out the sql but this code can be used in views as it isnt dynamic:
Select ID
,[Name1] = [1]
,[Name2] = [2]
,[Name3] = [3]
,[Name4] = [4]
,[Name5] = [5]
,[Name6] = [6]
,[Name7] = [7]
,[Name8] = [8]
from (
select distinct
ID
,Name
,RID = Dense_Rank() OVER(PARTITION BY ID ORDER BY NAME)
from #testEnvironment
) as XX
pivot ( min(Name) for RID in ( [1],[2],[3],[4],[5],[6],[7],[8] )
) as pvt
order by ID
The OP said for an "unknown" number, which means that realistically, dynamic is the only way to go.
If it was for a known number, then I find that the PIVOT operator is generally slower than using CASE statements then aggregating, e.g.
SELECT ID,
NULLIF(MAX(CASE WHEN POS = 1 THEN NAME ELSE '' END),'') AS [NAME1],
NULLIF(MAX(CASE WHEN POS = 2 THEN NAME ELSE '' END),'') AS [NAME2],
NULLIF(MAX(CASE WHEN POS = 3 THEN NAME ELSE '' END),'') AS [NAME3],
NULLIF(MAX(CASE WHEN POS = 4 THEN NAME ELSE '' END),'') AS [NAME4],
NULLIF(MAX(CASE WHEN POS = 5 THEN NAME ELSE '' END),'') AS [NAME5],
NULLIF(MAX(CASE WHEN POS = 6 THEN NAME ELSE '' END),'') AS [NAME6]
FROM (SELECT ID, NAME, ROW_NUMBER() OVER(PARTITION BY ID ORDER BY NAME)
FROM #testEnvironment
)a(ID,NAME,POS)
GROUP BY ID;
February 28, 2013 at 9:53 am
Throwing the 2 versions of the code through a test rig shows that the methods are reasonable similar on speed. Its how the methods get used is probable more important than the milliseconds difference in its perfromance.
For each sceniaro there was 50 interations which had a random number of values for the each row and the time taken to run each statement was recorded. For my code I padded the code out to hold a potential of 15 columns [Name1].....[Name15] just to make the testing easier & trouble freee 🙂 I havent tested the width of the values that populate the columns and at a guess this will have an effect.
The first run had a random number of columns upto 5 values for each row.
RowsCadavre Steve_JP
10125
10032
500137
1000159
25002018
50003029
75004144
100004549
50000210242
100000370442
The second run had a random number of columns upto 10 values for each row.
RowsCadavre Steve_JP
10103
10051
500157
10002313
25003825
50007050
750010075
1000012697
50000649487
1000001170864
Hopefully this helpful. At least both methods avoid RBAR
February 28, 2013 at 10:31 am
Another version with use of dynamic SQL produces required output:
SET NOCOUNT ON;
-- setup sample table
SELECT ID, NAME
INTO #testEnvironment
FROM (VALUES(1,'a'),(1,'b'),(1,'c'),(1,'d'),(2,'e'),(2,'f'),
(3,'g'),(3,'h'),(3,'i'),(4,'j'),(5,'K'),(5,'L'),
(5,'m'),(5,'N'),(5,'O'),(5,'P')
)a(ID, NAME);
-- Get required output
DECLARE @sql NVARCHAR(4000) = 'SELECT ID';
,MAX(CASE N WHEN ' + N + ' THEN NAME ELSE '''' END) as Name' + N
FROM (SELECT DISTINCT CAST(ROW_NUMBER() OVER (PARTITION BY ID ORDER BY NAME) AS VARCHAR) N
FROM #testEnvironment) Q;
FROM (SELECT *, ROW_NUMBER() OVER (PARTITION BY ID ORDER BY NAME) N
FROM #testEnvironment) Q
GROUP BY ID';
EXEC (@SQL);
DROP TABLE #testEnvironment;
March 1, 2013 at 2:26 am
Steve JP (2/28/2013)
Throwing the 2 versions of the code through a test rig shows that the methods are reasonable similar on speed. Its how the methods get used is probable more important than the milliseconds difference in its perfromance.
Interesting, can you provide the code you used in your test rig? I find that the CASE versions are generally much quicker than PIVOT, so I'd like to see why we have a different result here.
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