SQL- pad results with extra rows - sql

Question

I have a group of records that have a "Store" column. I need to basically split the result sets into groups of 13 records, creating blank rows to pad out each store to have 13 rows.
For simplicity, lets say I need groups of 4 records.
Example, given the below table:
-----------------
Store Name
-----------------
A John
A Bill
B Sam
C James
C Tim
C Chris
D Simon
D Phil
I need the results to look like:
-----------------
Store Name
-----------------
A John
A Bill
A
B Sam
B
B
C James
C Tim
C Chris
D Simon
D Phil
D
Is this at all possible with pure SQL? There are never going to be more than 3 rows for each store.
SQL Fiddle

Answer 1

Try this one -
DDL:
SET STATISTICS IO ON;
IF OBJECT_ID (N'tempdb.dbo.#temp') IS NOT NULL
DROP TABLE #temp
CREATE TABLE #temp
(
Store CHAR(1)
, Name VARCHAR(10)
)
INSERT INTO #temp (Store, Name)
VALUES
('A', 'John'), ('A', 'Bill'),
('B', 'Sam'), ('C', 'James'),
('C', 'Tim'), ('C', 'Chris'),
('D', 'Simon'), ('D', 'Phil')
Queries:
DevArt #1:
;WITH cte AS
(
SELECT
Store
, Name
, rn = ROW_NUMBER() OVER (PARTITION BY Store ORDER BY (SELECT 1))
FROM #temp
)
SELECT t.Store, Name = ISNULL(t3.Name, '')
FROM (
SELECT DISTINCT Store
FROM cte
) t
CROSS JOIN (SELECT rn = 1 UNION ALL SELECT 2 UNION ALL SELECT 3) t2
LEFT JOIN cte t3 ON t2.rn = t3.rn AND t.Store = t3.Store
DevArt #2:
SELECT t2.Store, Name = ISNULL(t3.Name, '')
FROM (
SELECT *
FROM (
SELECT Store, r = COUNT(1)
FROM #temp
GROUP BY Store
) t
CROSS APPLY (
VALUES (r), (r+1), (r+2)
) t2 (x)
) t2
LEFT JOIN #temp t3 ON t2.Store = t3.Store AND t2.x = t2.r
WHERE t2.x < 4
Alexander Fedorenko:
;WITH cte AS
(
SELECT DISTINCT Store
FROM #temp
)
SELECT o.Store, o.name
FROM cte s
CROSS APPLY (
SELECT TOP 3 x.Store, x.name
FROM (
SELECT s2.Store, s2.name
FROM #temp s2
WHERE s.Store = s2.Store
UNION ALL
SELECT s.Store, ''
UNION ALL
SELECT s.Store, ''
) x
) o
ErikE:
SELECT Store, Name
FROM (
SELECT
x.Store
, x.Name
, s = ROW_NUMBER() OVER (PARTITION BY x.Store ORDER BY x.s)
FROM #temp t
CROSS APPLY (
VALUES
(Store, Name, 0),
(Store, '', 1),
(Store, '', 1)
) x (Store, Name, S)
) z
WHERE s <= 3
ORDER BY Store
AmitSingh:
SELECT t.Store, Name = COALESCE(
(
SELECT name
FROM (
SELECT
row1 = ROW_NUMBER() OVER (PARTITION BY Store ORDER BY Store)
, *
FROM #temp
) c
WHERE t.[row] = c.row1
AND t.Store = c.Store
)
, '')
FROM
(
SELECT
[Row] = ROW_NUMBER() OVER (PARTITION BY a.Store ORDER BY a.Store)
, a.Store
FROM (
SELECT Store
FROM #temp
GROUP BY Store
) a
, (
SELECT TOP 3 Store
FROM #temp
) b
) t
Andriy M #1:
;WITH ranked AS
(
SELECT
Store
, Name
, rnk = ROW_NUMBER() OVER (PARTITION BY Store ORDER BY 1/0)
FROM #temp
)
, pivoted AS
(
SELECT
Store
, [1] = ISNULL([1], '')
, [2] = ISNULL([2], '')
, [3] = ISNULL([3], '')
FROM ranked
PIVOT (
MAX(Name)
FOR rnk IN ([1], [2], [3])
) p
)
, unpivoted AS
(
SELECT
Store
, Name
FROM pivoted
UNPIVOT (
Name FOR rnk IN ([1], [2], [3])
) u
)
SELECT *
FROM unpivoted
Andriy M #2:
;WITH ranked AS
(
SELECT
Store
, Name
, rnk = ROW_NUMBER() OVER (PARTITION BY Store ORDER BY 1/0)
FROM #temp
)
, padded AS
(
SELECT
Store
, Name
FROM ranked
PIVOT (
MAX(Name)
FOR rnk IN ([1], [2], [3])
) p
CROSS APPLY (
VALUES
(ISNULL([1], '')),
(ISNULL([2], '')),
(ISNULL([3], ''))
) x (Name)
)
SELECT *
FROM padded
Output:
Store Name
----- ----------
A John
A Bill
A
B Sam
B
B
C James
C Tim
C Chris
D Simon
D Phil
D
Statistics:
Query Presenter Scans Logical Reads
------------------- ----- -------------
DevArt #1 3 41
DevArt #2 2 9
Alexander Fedorenko 4 5
ErikE 1 1
AmitSingh 22 25
Andriy M #1 1 1
Andriy M #2 1 1
Query cost:
Extended statistics:
Execution statistics:
Query plan (from dbForge Studio for MS SQL):

Answer 2

Select t.store_id,Coalesce((Select Name from (
Select row_Number() Over(Partition by store_id order by store_id) as row1, * from stores)c
where t.row=c.row1 and t.store_id=c.store_id),'') as cfgg
from
(Select row_Number() Over(Partition by a.store_id order by a.store_id) as row,
a.store_id from
(Select store_id from stores group by store_id) a ,(Select top 3 store_id from stores)b
) t
SQL Fiddle Demo

Answer 3

One more option with APPLY operator
;WITH cte AS
(
SELECT store_id
FROM stores
GROUP BY store_id
)
SELECT o.store_id, o.name
FROM cte s CROSS APPLY (
SELECT TOP 3 x.store_id, x.name
FROM (
SELECT s2.store_id, s2.name
FROM stores s2
WHERE s.store_id = s2.store_id
UNION ALL
SELECT s.store_id, ''
UNION ALL
SELECT s.store_id, ''
) x
) o
Demo on SQLFiddle

Answer 4

Here's a query that works (SQL Server 2008 and up, can be fixed to work in 2005):
SELECT Store, Name
FROM (
SELECT
X.Store, X.Name, R = Row_Number() OVER (PARTITION BY X.Store ORDER BY X.S)
FROM
#temp T
CROSS APPLY (VALUES
(Store, Name, 0), (Store, '', 1), (Store, '', 1)
) X (Store, Name, S)
) Z
WHERE R <= 3
ORDER BY Store
;
According to SET STATISTICS IO ON;, here are performance statistics (all have negligible CPU at this low number of rows, perhaps more rows would help determine the best performer):
Query Presenter Scans Logical Reads
------------------- ----- -------------
ErikE 1 1
Alexander Fedorenko 4 5
Devart 3 41
AmitSingh 22 25
My query does not preserve the "original" ordering of the names for each store, however that is not a flaw because there is no concept of ordering in a relational database table. You must supply a column to order by if you want to preserve a particular sequence.

Answer 5

Yet another option, this time using PIVOT and UNPIVOT:
WITH ranked AS (
SELECT
store_id,
name,
rnk = ROW_NUMBER() OVER (PARTITION BY store_id ORDER BY 1/0)
FROM stores
),
pivoted AS (
SELECT
store_id,
[1] = ISNULL([1], ''),
[2] = ISNULL([2], ''),
[3] = ISNULL([3], '')
FROM ranked
PIVOT (
MAX(name) FOR rnk IN ([1], [2], [3])
) p
),
unpivoted AS (
SELECT
store_id,
name
FROM pivoted
UNPIVOT (
name FOR rnk IN ([1], [2], [3])
) u
)
SELECT *
FROM unpivoted
;
A SQL Fiddle demo to play with: http://sqlfiddle.com/#!3/354df/39.
Note that the UNPIVOT step in the above query has to be done in a separate SELECT from the PIVOT action. That is because UNPIVOT does not generate rows where columns listed in the IN column list contain NULLs. However, you could replace UNPIVOT with an equivalent technique (like CROSS APPLY) and thus move the unpivoting to the same subquery that does the pivoting:
WITH ranked AS (
SELECT
store_id,
name,
rnk = ROW_NUMBER() OVER (PARTITION BY store_id ORDER BY 1/0)
FROM stores
),
padded AS (
SELECT
store_id,
name
FROM ranked
PIVOT (
MAX(name) FOR rnk IN ([1], [2], [3])
) p
CROSS APPLY (
VALUES
(ISNULL([1], '')),
(ISNULL([2], '')),
(ISNULL([3], ''))
) x (name)
)
SELECT *
FROM padded
;
A SQL Fiddle demo for the modified version: http://sqlfiddle.com/#!3/354df/40.