Split column value to rows.

• sql_learner29

  SSCrazy Eights

  Points: 9107

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  June 1, 2017 at 1:53 pm

  #323832

  Hi All,
  I was looking for code to split column value into separate rows..
  Any help on this..
  like for the example below , for ID =1 ,it should give 4 rows..like this
  ID Category
  1  5
  1  H
  1  W
  1  6

  create table TEST

  (
ID char(10),
CATEGORY VARCHAR(10)
)

  INSERT INTO TEST values(1,'5HW6')
INSERT INTO TEST values(2,'256')
INSERT INTO TEST values(3,'57')
INSERT INTO TEST values(4,'3')
INSERT INTO TEST values(5,'4578')
INSERT INTO TEST values(6,'256HW')SELECT * from TEST

  [font="Comic Sans MS"]
  ---------------------------------------------------

  Thanks [/font]

• Joe Torre

  SSChampion

  Points: 10248

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  June 1, 2017 at 2:33 pm

  #1944968

  Try:
  
DECLARE @test-2 table (ID int IDENTITY,CATEGORY VARCHAR(10));
INSERT @test-2 (CATEGORY)
VALUES ('5HW6')
      ,('256')
      ,('57')
      ,('3')
      ,('4578')
      ,('256HW');
SELECT ID
     , CATEGORY
FROM @test-2;
SELECT ID
     , n Position
     , Substring(t.CATEGORY, n, 1) Letter
FROM @test-2 t
CROSS APPLY (SELECT n FROM (VALUES (1),(2),(3),(4),(5)) nums (n)) nums
WHERE n<=Len(t.CATEGORY)

  

• Ed Wagner

  SSC Guru

  Points: 287026

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  June 1, 2017 at 4:04 pm

  #1944979

  Joe Torre - Thursday, June 1, 2017 2:33 PM

  Try:
  
DECLARE @test-2 table (ID int IDENTITY,CATEGORY VARCHAR(10));
INSERT @test-2 (CATEGORY)
VALUES ('5HW6')
      ,('256')
      ,('57')
      ,('3')
      ,('4578')
      ,('256HW');
SELECT ID
     , CATEGORY
FROM @test-2;
SELECT ID
     , n Position
     , Substring(t.CATEGORY, n, 1) Letter
FROM @test-2 t
CROSS APPLY (SELECT n FROM (VALUES (1),(2),(3),(4),(5)) nums (n)) nums
WHERE n<=Len(t.CATEGORY)

  

  Nice job, Joe.  Other than the placement of the commas, it's about what I would have done. 😛

  Mr. Learner, I don't think you're going to get much more efficient of an approach than this.  I ran a test over 1.7M rows and it split them out in 29.2 seconds.
  I was able to get it down to 22.7 seconds using  Itzik's Tally function, called TallyN below.
  Without actually returning the values (using a bit bucket instead) the times were 8166 ms vs. 7826 ms.

  I tried a couple of slightly different approaches and the results were largely the same.

  Here's the test harness I put together for it.

  
--This table variable is only used to track the start and end time of each task as executed. Thanks for the approach, EE!
DECLARE @times TABLE (
  task Varchar(32),
  d Datetime);

  --Bit bucket variables to receive the values
DECLARE @id Integer,
       @n Integer,
       @char Varchar(1);

  --Approach #1
INSERT INTO @times(task, d) VALUES('Split', GETDATE());

  SELECT @id = ID, @n = n, @char = Substring(t.CATEGORY, n, 1)
FROM #TEST t
    CROSS APPLY (SELECT n FROM (VALUES (1),(2),(3),(4),(5)) nums (n)) nums
WHERE n <= Len(t.CATEGORY);

  INSERT INTO @times(task, d) VALUES('Split', GETDATE());

  --Approach #2
INSERT INTO @times(task, d) VALUES('TallyN', GETDATE());

  SELECT @id = ID, @n = t.N, @char = SUBSTRING(d.Category, t.N, 1)
  FROM #test d
    CROSS APPLY dbo.TallyN(5) t
WHERE t.N < LEN(d.Category);

  INSERT INTO @times(task, d) VALUES('TallyN', GETDATE());

  --The time each approach took is the difference of the min and max for each task name
SELECT task, DATEDIFF(ms, MIN(d), MAX(d))
FROM @times
GROUP BY task;


  I hope I didn't go overboard, but I really enjoy this type of thing. 😉  There may, of course, be faster ways to do the same thing, but I think this is pretty good.
  

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• Jacob Wilkins

  One Orange Chip

  Points: 27976

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  June 1, 2017 at 4:44 pm

  #1944985

  I'm not sure there's actually a substantial performance difference between the two methods.

  Note that the TallyN query as written will always avoid doing the last letter of each category, because it's doing WHERE t.N < LEN(d.Category) instead of WHERE t.N <= LEN(d.Category)

  I'd wager most of the performance improvement comes from avoiding that extra letter of work for each ID 🙂

  EDIT: 

  As a followup, here's another method that seems to shave a bit of time off by only generating the rows we need in the CROSS APPLY, instead of potentially generating all 5 and rejecting some of them with the WHERE clause (I'm still playing around with this in my head and might test a couple other ideas, hence labeling it 'Jacob #1')

  I've also noticed this one tends to go parallel, so you might want to throw in a MAXDOP 1 hint so the elapsed time metric isn't misleading. Even forcing them all serial this one consistently is measurably faster, though.

  INSERT INTO @times(task, d) VALUES('Jacob #1', GETDATE());

  SELECT @id = ID,
       @n = t.N,
       @char = SUBSTRING(d.Category, t.N, 1)
FROM   #TEST d
       CROSS APPLY
       (
       SELECT TOP (LEN(Category)) n
       FROM (VALUES(1),(2),(3),(4),(5))n(n)
       ORDER BY n ASC
       )t(n);

  INSERT INTO @times(task,d) VALUES ('Jacob #1', GETDATE());

  Cheers!

• Ed Wagner

  SSC Guru

  Points: 287026

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  June 1, 2017 at 5:25 pm

  #1944986

  Jacob Wilkins - Thursday, June 1, 2017 4:44 PM

  Note that the TallyN query as written will always avoid doing the last letter of each category, because it's doing WHERE t.N < LEN(d.Category) instead of WHERE t.N <= LEN(d.Category)

  I'd wager most of the performance improvement comes from avoiding that extra letter of work for each ID 🙂

  DOH!  Well, that's embarrassing.  Thank you for the good catch, Jacob.  It really did make a difference in performance.

  Jacob Wilkins - Thursday, June 1, 2017 4:44 PM

  As a followup, here's another method that seems to shave a bit of time off by only generating the rows we need in the CROSS APPLY, instead of potentially generating all 5 and rejecting some of them with the WHERE clause (I'm still playing around with this in my head and might test a couple other ideas, hence labeling it 'Jacob #1')

  INSERT INTO @times(task, d) VALUES('Jacob #1', GETDATE());

  SELECT @id = ID,
       @n = t.N,
       @char = SUBSTRING(d.Category, t.N, 1)
FROM   #TEST d
       CROSS APPLY
       (
       SELECT TOP (LEN(Category)) n
       FROM (VALUES(1),(2),(3),(4),(5))n(n)
       ORDER BY n ASC
       )t(n);

  INSERT INTO @times(task,d) VALUES ('Jacob #1', GETDATE());


  Nice work.  That does indeed take it down significantly.  With the fix to the TallyN in place, here's where it stands now.

  Jacob #1: 3630
  Split: 7470
  TallyN: 8060

  I'm seeing some variability in trials of up to 500 ms or so.

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• Jeff Moden

  SSC Guru

  Points: 1004312

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  June 1, 2017 at 5:39 pm

  #1944987

  I see a claim of working against 1.7 million rows.  What does the data actually look like and what is the structure of the table that you're using for the test?

  --Jeff Moden

  ---

  RBAR is pronounced "ree-bar" and is a "Modenism" for Row-By-Agonizing-Row.
  First step towards the paradigm shift of writing Set Based code:
  ________Stop thinking about what you want to do to a ROW... think, instead, of what you want to do to a COLUMN.

  Change is inevitable... Change for the better is not.
  

  ---

  Helpful Links:
  How to post code problems
  How to Post Performance Problems
  Create a Tally Function (fnTally)
  

• Ed Wagner

  SSC Guru

  Points: 287026

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  June 1, 2017 at 6:59 pm

  #1944992

  Jeff Moden - Thursday, June 1, 2017 5:39 PM

  I see a claim of working against 1.7 million rows.  What does the data actually look like and what is the structure of the table that you're using for the test?

  Hi Jeff.  I made a test table and used 1.7M rows.  I did some lower-volume testing, but kept adding to it over several rounds and ended up at 1.7M.  I didn't start out with that number as a goal, but rather ended up there.  It's on my laptop and I used tempdb.

  Here's the table:

  IF OBJECT_ID('tempdb.dbo.#test', 'u') IS NOT NULL DROP TABLE #test;
CREATE TABLE #test (
ID integer IDENTITY,
CATEGORY Varchar(10));

  And here's the mechanism to create the test data.  I know I don't have to explain it to you, as it should look very familiar. 😉

  INSERT INTO #test(Category)
SELECT SUBSTRING(CONVERT(CHAR(36),NEWID()),
                  ABS(CHECKSUM(NEWID()) % 16) + 1,
                  ABS(CHECKSUM(NEWID()) % 5) + 1)
FROM dbo.TallyN(100000);


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• Ed Wagner

  SSC Guru

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  June 1, 2017 at 7:28 pm

  #1944995

  I see I forgot to define dbo.TallyN.  It's Itzik's zero-read tally ITVF.  I use it so much I sometimes think it's a part of SQL Server.  It isn't, but it should be.

  ALTER FUNCTION dbo.TallyN(@N Bigint) RETURNS TABLE WITH SCHEMABINDING
AS
--Credit: This function was written by Itzik Ben-Gan at http://sqlmag.com/sql-server/virtual-auxiliary-table-numbers
RETURN WITH level0 AS (
SELECT 0 AS g UNION ALL SELECT 0),           --2
level1 AS (SELECT 0 AS g FROM level0 AS a CROSS JOIN level0 AS b), --2^2 = 4
level2 AS (SELECT 0 AS g FROM level1 AS a CROSS JOIN level1 AS b), --4^2 = 16
level3 AS (SELECT 0 AS g FROM level2 AS a CROSS JOIN level2 AS b), --16^2 = 256
level4 AS (SELECT 0 AS g FROM level3 AS a CROSS JOIN level3 AS b), --256^2 = 65536
level5 AS (SELECT 0 AS g FROM level4 AS a CROSS JOIN level4 AS b), --65536^2 = 4294967296
Tally AS (SELECT ROW_NUMBER() OVER (ORDER BY (SELECT NULL)) AS n FROM level5)
SELECT TOP (@N) N
FROM Tally
ORDER BY N;


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• Eirikur Eiriksson

  SSC Guru

  Points: 182911

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  June 2, 2017 at 2:22 am

  #1945031

  Jacob Wilkins - Thursday, June 1, 2017 4:44 PM

  I'm not sure there's actually a substantial performance difference between the two methods.

  Note that the TallyN query as written will always avoid doing the last letter of each category, because it's doing WHERE t.N < LEN(d.Category) instead of WHERE t.N <= LEN(d.Category)

  I'd wager most of the performance improvement comes from avoiding that extra letter of work for each ID 🙂

  EDIT: 

  As a followup, here's another method that seems to shave a bit of time off by only generating the rows we need in the CROSS APPLY, instead of potentially generating all 5 and rejecting some of them with the WHERE clause (I'm still playing around with this in my head and might test a couple other ideas, hence labeling it 'Jacob #1')

  I've also noticed this one tends to go parallel, so you might want to throw in a MAXDOP 1 hint so the elapsed time metric isn't misleading. Even forcing them all serial this one consistently is measurably faster, though.

  INSERT INTO @times(task, d) VALUES('Jacob #1', GETDATE());

  SELECT @id = ID,
       @n = t.N,
       @char = SUBSTRING(d.Category, t.N, 1)
FROM   #TEST d
       CROSS APPLY
       (
       SELECT TOP (LEN(Category)) n
       FROM (VALUES(1),(2),(3),(4),(5))n(n)
       ORDER BY n ASC
       )t(n);

  INSERT INTO @times(task,d) VALUES ('Jacob #1', GETDATE());

  Cheers!

  Be careful with that order by clause, it will significantly slow down the query!
  😎

• Eirikur Eiriksson

  SSC Guru

  Points: 182911

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  June 2, 2017 at 2:40 am

  #1945038

  Here is a simple test harness and the result set from my old i5 laptop
  😎

  USE TEEST;
GO
SET NOCOUNT ON;

  DECLARE @SAMPLE_SIZE  INT   = 2000000;
DECLARE @MAX_CHARS  INT   = 5;
DECLARE @INT_BUCKET  INT   = 0;
DECLARE @CHAR_BUCKET  VARCHAR(10) = '';
DECLARE @timer TABLE (T_TXT VARCHAR(20) NOT NULL, T_TS DATETIME NOT NULL DEFAULT (GETDATE()));

  /*
IF OBJECT_ID(N'dbo.TBL_SAMPLE_SPLIT_CHARS') IS NOT NULL DROP TABLE dbo.TBL_SAMPLE_SPLIT_CHARS;

  CREATE TABLE dbo.TBL_SAMPLE_SPLIT_CHARS
(
  SSC_ID  INT   NOT NULL CONSTRAINT PK_DBO_TBL_SAMPLE_SPLIT_CHARS_SSC_ID PRIMARY KEY CLUSTERED
 ,CATEGORY  VARCHAR(10) NOT NULL
);

  ;WITH T(N) AS (SELECT X.N FROM (VALUES (0),(0),(0),(0),(0),(0),(0),(0),(0),(0)) X(N))
, NUMS(N) AS (SELECT TOP(@SAMPLE_SIZE) ROW_NUMBER() OVER (ORDER BY @@VERSION) AS N
     FROM T T1,T T2,T T3,T T4,T T5,T T6,T T7,T T8,T T9)
INSERT INTO dbo.TBL_SAMPLE_SPLIT_CHARS(SSC_ID,CATEGORY)
SELECT
  NM.N
 ,SUBSTRING(REPLACE(CONVERT(VARCHAR(36),NEWID(),0),CHAR(45),CHAR(65)),1,(ABS(CHECKSUM(NEWID())) % @MAX_CHARS) + 1)
FROM  NUMS  NM;
-- */

  INSERT INTO @timer(T_TXT) VALUES('DRY RUN');
SELECT
  @INT_BUCKET = SSC.SSC_ID
 ,@CHAR_BUCKET = SSC.CATEGORY
FROM  dbo.TBL_SAMPLE_SPLIT_CHARS SSC
OPTION (MAXDOP 1);
INSERT INTO @timer(T_TXT) VALUES('DRY RUN');

  INSERT INTO @timer(T_TXT) VALUES('EE CROSS APPLY');
SELECT
 @INT_BUCKET = SSC.SSC_ID
,@INT_BUCKET = NM.N
,@CHAR_BUCKET = SUBSTRING(SSC.CATEGORY,NM.N,1)
FROM  dbo.TBL_SAMPLE_SPLIT_CHARS SSC
CROSS APPLY (SELECT TOP(LEN(SSC.CATEGORY)) X.N FROM (VALUES (1),(2),(3),(4),(5)) X(N)) AS NM
OPTION (MAXDOP 1);
INSERT INTO @timer(T_TXT) VALUES('EE CROSS APPLY');

  INSERT INTO @timer(T_TXT) VALUES('EE OUTER APPLY');
SELECT
 @INT_BUCKET = SSC.SSC_ID
,@INT_BUCKET = NM.N
,@CHAR_BUCKET = SUBSTRING(SSC.CATEGORY,NM.N,1)
FROM  dbo.TBL_SAMPLE_SPLIT_CHARS SSC
OUTER APPLY (SELECT TOP(LEN(SSC.CATEGORY)) X.N FROM (VALUES (1),(2),(3),(4),(5)) X(N)) AS NM
OPTION (MAXDOP 1);
INSERT INTO @timer(T_TXT) VALUES('EE OUTER APPLY');

  INSERT INTO @timer(T_TXT) VALUES('Jacob #1');
SELECT @INT_BUCKET = SSC.SSC_ID,
   @INT_BUCKET = t.n,
   @CHAR_BUCKET = SUBSTRING(SSC.CATEGORY, t.N, 1)
FROM dbo.TBL_SAMPLE_SPLIT_CHARS SSC
   CROSS APPLY
   (
   SELECT TOP (LEN(Category)) n
   FROM (VALUES(1),(2),(3),(4),(5))n(n)
   ORDER BY n ASC
   )t(n)
OPTION (MAXDOP 1);
INSERT INTO @timer(T_TXT) VALUES('Jacob #1');

  INSERT INTO @timer(T_TXT) VALUES('Jacob #2');
SELECT @INT_BUCKET = SSC.SSC_ID,
   @INT_BUCKET = t.n,
   @CHAR_BUCKET = SUBSTRING(SSC.CATEGORY, t.N, 1)
FROM dbo.TBL_SAMPLE_SPLIT_CHARS SSC
   CROSS APPLY
   (
   SELECT TOP (LEN(Category)) n
   FROM (VALUES(1),(2),(3),(4),(5))n(n)
   )t(n)
OPTION (MAXDOP 1);
INSERT INTO @timer(T_TXT) VALUES('Jacob #2');

  SELECT
  T.T_TXT
 ,DATEDIFF(MICROSECOND,MIN(T.T_TS),MAX(T.T_TS)) AS DURATION
FROM  @timer T
GROUP BY T.T_TXT
ORDER BY DURATION ASC;

  Results
  T_TXT                DURATION
-------------------- -----------
DRY RUN                433334
EE OUTER APPLY        1663333
Jacob #2              1740000
EE CROSS APPLY        1750000
Jacob #1             21433333

  

• Eirikur Eiriksson

  SSC Guru

  Points: 182911

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  June 2, 2017 at 3:23 am

  #1945049

  Ed Wagner - Thursday, June 1, 2017 4:04 PM

  Joe Torre - Thursday, June 1, 2017 2:33 PM

  Try:
  
DECLARE @test-2 table (ID int IDENTITY,CATEGORY VARCHAR(10));
INSERT @test-2 (CATEGORY)
VALUES ('5HW6')
      ,('256')
      ,('57')
      ,('3')
      ,('4578')
      ,('256HW');
SELECT ID
     , CATEGORY
FROM @test-2;
SELECT ID
     , n Position
     , Substring(t.CATEGORY, n, 1) Letter
FROM @test-2 t
CROSS APPLY (SELECT n FROM (VALUES (1),(2),(3),(4),(5)) nums (n)) nums
WHERE n<=Len(t.CATEGORY)

  

  Nice job, Joe.  Other than the placement of the commas, it's about what I would have done. 😛

  Mr. Learner, I don't think you're going to get much more efficient of an approach than this.  I ran a test over 1.7M rows and it split them out in 29.2 seconds.
  I was able to get it down to 22.7 seconds using  Itzik's Tally function, called TallyN below.
  Without actually returning the values (using a bit bucket instead) the times were 8166 ms vs. 7826 ms.

  I tried a couple of slightly different approaches and the results were largely the same.

  Here's the test harness I put together for it.

  
--This table variable is only used to track the start and end time of each task as executed. Thanks for the approach, EE!
DECLARE @times TABLE (
  task Varchar(32),
  d Datetime);

  --Bit bucket variables to receive the values
DECLARE @id Integer,
       @n Integer,
       @char Varchar(1);

  --Approach #1
INSERT INTO @times(task, d) VALUES('Split', GETDATE());

  SELECT @id = ID, @n = n, @char = Substring(t.CATEGORY, n, 1)
FROM #TEST t
    CROSS APPLY (SELECT n FROM (VALUES (1),(2),(3),(4),(5)) nums (n)) nums
WHERE n <= Len(t.CATEGORY);

  INSERT INTO @times(task, d) VALUES('Split', GETDATE());

  --Approach #2
INSERT INTO @times(task, d) VALUES('TallyN', GETDATE());

  SELECT @id = ID, @n = t.N, @char = SUBSTRING(d.Category, t.N, 1)
  FROM #test d
    CROSS APPLY dbo.TallyN(5) t
WHERE t.N < LEN(d.Category);

  INSERT INTO @times(task, d) VALUES('TallyN', GETDATE());

  --The time each approach took is the difference of the min and max for each task name
SELECT task, DATEDIFF(ms, MIN(d), MAX(d))
FROM @times
GROUP BY task;


  I hope I didn't go overboard, but I really enjoy this type of thing. 😉  There may, of course, be faster ways to do the same thing, but I think this is pretty good.
  

  Using the LEN function in the WHERE clause is a killer here, slows the query down several times, much more efficient to use the TOP operator within the numbers CTE. The reason for this is that when using the former, the server will generate the full output of the CTE and then filter is applied afterwards whilst the TOP operator will limit the number generated.
  😎

  Demonstration
  USE TEEST;
GO
SET NOCOUNT ON;

  DECLARE @SAMPLE_SIZE  INT   = 2000000;
DECLARE @MAX_CHARS  INT   = 5;
DECLARE @INT_BUCKET  INT   = 0;
DECLARE @CHAR_BUCKET  VARCHAR(10) = '';
DECLARE @timer TABLE (T_TXT VARCHAR(20) NOT NULL, T_TS DATETIME NOT NULL DEFAULT (GETDATE()));

  /*
IF OBJECT_ID(N'dbo.TBL_SAMPLE_SPLIT_CHARS') IS NOT NULL DROP TABLE dbo.TBL_SAMPLE_SPLIT_CHARS;

  CREATE TABLE dbo.TBL_SAMPLE_SPLIT_CHARS
(
  SSC_ID  INT   NOT NULL CONSTRAINT PK_DBO_TBL_SAMPLE_SPLIT_CHARS_SSC_ID PRIMARY KEY CLUSTERED
 ,CATEGORY  VARCHAR(10) NOT NULL
);

  ;WITH T(N) AS (SELECT X.N FROM (VALUES (0),(0),(0),(0),(0),(0),(0),(0),(0),(0)) X(N))
, NUMS(N) AS (SELECT TOP(@SAMPLE_SIZE) ROW_NUMBER() OVER (ORDER BY @@VERSION) AS N
     FROM T T1,T T2,T T3,T T4,T T5,T T6,T T7,T T8,T T9)
INSERT INTO dbo.TBL_SAMPLE_SPLIT_CHARS(SSC_ID,CATEGORY)
SELECT
  NM.N
 ,SUBSTRING(REPLACE(CONVERT(VARCHAR(36),NEWID(),0),CHAR(45),CHAR(65)),1,(ABS(CHECKSUM(NEWID())) % @MAX_CHARS) + 1)
FROM  NUMS  NM;
-- */

  INSERT INTO @timer(T_TXT) VALUES('DRY RUN');
SELECT
  @INT_BUCKET = SSC.SSC_ID
 ,@CHAR_BUCKET = SSC.CATEGORY
FROM  dbo.TBL_SAMPLE_SPLIT_CHARS SSC
OPTION (MAXDOP 1);
INSERT INTO @timer(T_TXT) VALUES('DRY RUN');

  INSERT INTO @timer(T_TXT) VALUES('EE CROSS APPLY TOP');
SELECT
 @INT_BUCKET = SSC.SSC_ID
,@INT_BUCKET = NM.N
,@CHAR_BUCKET = SUBSTRING(SSC.CATEGORY,NM.N,1)
FROM  dbo.TBL_SAMPLE_SPLIT_CHARS SSC
CROSS APPLY (SELECT TOP(LEN(SSC.CATEGORY)) X.N FROM (VALUES (1),(2),(3),(4),(5)) X(N)) AS NM
OPTION (MAXDOP 1);
INSERT INTO @timer(T_TXT) VALUES('EE CROSS APPLY TOP');

  INSERT INTO @timer(T_TXT) VALUES('EE OUTER APPLY TOP');
SELECT
 @INT_BUCKET = SSC.SSC_ID
,@INT_BUCKET = NM.N
,@CHAR_BUCKET = SUBSTRING(SSC.CATEGORY,NM.N,1)
FROM  dbo.TBL_SAMPLE_SPLIT_CHARS SSC
OUTER APPLY (SELECT TOP(LEN(SSC.CATEGORY)) X.N FROM (VALUES (1),(2),(3),(4),(5)) X(N)) AS NM
OPTION (MAXDOP 1);
INSERT INTO @timer(T_TXT) VALUES('EE OUTER APPLY TOP');

  INSERT INTO @timer(T_TXT) VALUES('EE CROSS APPLY WHERE');
SELECT
 @INT_BUCKET = SSC.SSC_ID
,@INT_BUCKET = NM.N
,@CHAR_BUCKET = SUBSTRING(SSC.CATEGORY,NM.N,1)
FROM  dbo.TBL_SAMPLE_SPLIT_CHARS SSC
CROSS APPLY (SELECT X.N FROM (VALUES (1),(2),(3),(4),(5)) X(N)) AS NM
WHERE NM.N <= LEN(SSC.CATEGORY)
OPTION (MAXDOP 1);
INSERT INTO @timer(T_TXT) VALUES('EE CROSS APPLY WHERE');

  INSERT INTO @timer(T_TXT) VALUES('EE OUTER APPLY WHERE');
SELECT
 @INT_BUCKET = SSC.SSC_ID
,@INT_BUCKET = NM.N
,@CHAR_BUCKET = SUBSTRING(SSC.CATEGORY,NM.N,1)
FROM  dbo.TBL_SAMPLE_SPLIT_CHARS SSC
OUTER APPLY (SELECT X.N FROM (VALUES (1),(2),(3),(4),(5)) X(N)) AS NM
WHERE NM.N <= LEN(SSC.CATEGORY)
OPTION (MAXDOP 1);
INSERT INTO @timer(T_TXT) VALUES('EE OUTER APPLY WHERE');

  INSERT INTO @timer(T_TXT) VALUES('Jacob #1');
SELECT @INT_BUCKET = SSC.SSC_ID,
   @INT_BUCKET = t.n,
   @CHAR_BUCKET = SUBSTRING(SSC.CATEGORY, t.N, 1)
FROM dbo.TBL_SAMPLE_SPLIT_CHARS SSC
   CROSS APPLY
   (
   SELECT TOP (LEN(Category)) n
   FROM (VALUES(1),(2),(3),(4),(5))n(n)
   ORDER BY n ASC
   )t(n)
OPTION (MAXDOP 1);
INSERT INTO @timer(T_TXT) VALUES('Jacob #1');

  INSERT INTO @timer(T_TXT) VALUES('Jacob #2');
SELECT @INT_BUCKET = SSC.SSC_ID,
   @INT_BUCKET = t.n,
   @CHAR_BUCKET = SUBSTRING(SSC.CATEGORY, t.N, 1)
FROM dbo.TBL_SAMPLE_SPLIT_CHARS SSC
   CROSS APPLY
   (
   SELECT TOP (LEN(Category)) n
   FROM (VALUES(1),(2),(3),(4),(5))n(n)
   )t(n)
OPTION (MAXDOP 1);
INSERT INTO @timer(T_TXT) VALUES('Jacob #2');

  SELECT
  T.T_TXT
 ,DATEDIFF(MICROSECOND,MIN(T.T_TS),MAX(T.T_TS)) AS DURATION
FROM  @timer T
GROUP BY T.T_TXT
ORDER BY DURATION ASC;

  Results
  
T_TXT                DURATION
-------------------- ---------
DRY RUN                470000
EE OUTER APPLY TOP    1640000
Jacob #2              1770000
EE CROSS APPLY TOP    1783333
EE OUTER APPLY WHERE 10510000
Jacob #1             16463333
EE CROSS APPLY WHERE 18526667


• Eirikur Eiriksson

  SSC Guru

  Points: 182911

  More actions

  June 2, 2017 at 6:38 am

  #1945082

  Ed Wagner - Thursday, June 1, 2017 4:04 PM

  I hope I didn't go overboard, but I really enjoy this type of thing. 😉  There may, of course, be faster ways to do the same thing, but I think this is pretty good.
  

  No such thing as going overboard when doing fun stuff mate😉
  😎

• Ed Wagner

  SSC Guru

  Points: 287026

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  June 2, 2017 at 6:41 am

  #1945083

  Eirikur Eiriksson - Friday, June 2, 2017 6:38 AM

  Ed Wagner - Thursday, June 1, 2017 4:04 PM

  I hope I didn't go overboard, but I really enjoy this type of thing. 😉  There may, of course, be faster ways to do the same thing, but I think this is pretty good.
  

  No such thing as going overboard when doing fun stuff mate😉
  😎

  Heh - I agree.  I was working through a slightly different idea, but won't be working on it until I get home tonight.

  Tally Tables - Performance Personified
  String Splitting with True Performance
  Best practices on how to ask questions

• Jacob Wilkins

  One Orange Chip

  Points: 27976

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  June 2, 2017 at 8:18 am

  #1945112

  Eirikur Eiriksson - Friday, June 2, 2017 2:22 AM

  Be careful with that order by clause, it will significantly slow down the query!
  😎

  Indeed.

  I kept it included because very strictly speaking there is no guarantee of correctness of the query without it.

  To guarantee the query is correct, you have to know that the N returned for a string of length 3 will be 1,2, and 3.

  Anything else would yield incorrect results.

  As you did, I noticed that I seemed to get correct results every time without it, but without the ORDER BY, there's just no guarantee you'll get the right N from the APPLY.

  Perhaps the engine will actually return them in the desired order under every possible circumstance, but I'm a paranoid DBA,so I couldn't bring myself to make that assumption 🙂

• Eirikur Eiriksson

  SSC Guru

  Points: 182911

  More actions

  June 2, 2017 at 8:38 am

  #1945119

  Jacob Wilkins - Friday, June 2, 2017 8:18 AM

  Eirikur Eiriksson - Friday, June 2, 2017 2:22 AM

  Be careful with that order by clause, it will significantly slow down the query!
  😎

  Indeed.

  I kept it included because very strictly speaking there is no guarantee of correctness of the query without it.

  To guarantee the query is correct, you have to know that the N returned for a string of length 3 will be 1,2, and 3.

  Anything else would yield incorrect results.

  As you did, I noticed that I seemed to get correct results every time without it, but without the ORDER BY, there's just no guarantee you'll get the right N from the APPLY.

  Perhaps the engine will actually return them in the desired order under every possible circumstance, but I'm a paranoid DBA,so I couldn't bring myself to make that assumption 🙂

  From a set based perspective, the order of appearance is irrelevant, the result set will be correct with or without the order by clause as the N will always correspond correctly to the position of the character returned. In fact, when using MAXDOP 1, the output is always appearing in the correct order although as you said, there is no guarantee that will always be so.
  😎

  A greater culprit is not using the TOP operator, especially when handling greater variety of input length, the constant scan operator will feed the join operator maximum number of rows for every iteration.