Transforming string to rows (HEEELP!)

Please help. The required code is beyond me. :slight_smile:

I need to transform data from a string into rows as below.

@MyTable1 is how the data looks now and @MyTable2 is how I would like it to look. I am using SQL2012.

-- Raw Data
DECLARE @MyTable1 TABLE (CustomerId INT, InvoiceData VARCHAR(1000))

SELECT 1, '2022/01/31;INV001;125.50;2022/02/28;INV002;86.25'
SELECT 2, '2022/01/20;INV023;726.26;2022/02/14;INV043;200.50;2022/03/17;INV067;453.85'


-- Transformed
DECLARE @MyTable2 TABLE (CustomerId INT, InvoiceDate DATETIME, InvoiceNo VARCHAR(20), InvoiceAmount MONEY)

SELECT 1, '2022/01/31', 'INV001', 125.50
SELECT 1, '2022/02/28', 'INV002', 86.25
SELECT 2, '2022/01/20', 'INV023', 726.26
SELECT 2, '2022/02/14', 'INV043', 200.50
SELECT 2, '2022/03/17', 'INV067', 453.85


;WITH cte AS (SELECT *, CAST(CONCAT('<a><z>',REPLACE(invoicedata,';','</z><z>'),'</z></a>') AS xml) x FROM @MyTable1 t)
	,cte2 AS (SELECT CustomerId
			, q.value('(.)[1]','varchar(128)') val
	FROM cte
	CROSS APPLY x.nodes('/a/z') q(q))
, CAST([0] AS datetime) InvoiceDate, cast([1] AS varchar(64)) InvoiceNo, cast([2] AS money) InvoiceAmount
	SELECT CustomerId, val, (rn)/3 as invID, rn % 3 as item
	FROM cte2) a
PIVOT(MAX(val) FOR item in ([0],[1],[2])) b

This is a bit complex but I'll break it down:

  1. First statement (cte) replaces ; with XML tags, then encloses invoicedata in opening and closing XML tags to make it pure XML

  2. Second statement (cte2) splits that XML into multiple nodes, split on the z element, which represents each column of the invoice. It also numbers each node in sequence as it appears in invoicedata.

  3. The subquery just above PIVOT does some division and modulo arithmetic to identify each separate invoice, then categorize each element by a column number (0, 1 or 2), based on the sequence number generated in cte2.

  4. The PIVOT extracts the parsed value (val) from the invoicedata, then rotates it based on column position into a separate column. It includes the CustomerID, and is additionally grouped by each invoicedata value.

  5. The SELECT statement that CASTs each column to its appropriate data type also aliases the columns to the desired names.

This isn't the only way to parse this data, might not be the best way, but string parsing in SQL is a very wide and deep topic. As you've probably figured out, it's better and easier to combine multiple columns and rows into a string than to do the opposite.

I have two articles that cover this. One is on "CrossTabs and Pivots", which demonstrates what a CrossTab is and how it's faster and a bit more flexible than a Pivot.

I have another article on a nasty fast string splitter that I built for the pre-2022 days long before it was a gleam in anyone's eye. It also compares many other "splitter" methods and why you should probably avoid them when it comes to performance

Don't use that function (the article is a real fun read, though)... a good friend of mine made a mod to it in 2012 that made it even faster, thanks to the use of LEAD. Here's the function with that mod.

 CREATE FUNCTION [dbo].[DelimitedSplit8K]
 Split a given string at a given delimiter and return a list of the split elements (items).

 1.  Leading and trailing delimiters are treated as if an empty string element were present.
 2.  Consecutive delimiters are treated as if an empty string element were present between them.
 3.  Except when spaces are used as a delimiter, all spaces present in each element are preserved.

 iTVF containing the following:
 ItemNumber = Element position of Item as a BIGINT (not converted to INT to eliminate a CAST)
 Item       = Element value as a VARCHAR(8000)

 Note that this function uses a binary collation and is, therefore, case sensitive.

 The original article for the concept of this splitter may be found at the following URL.  You can also find
 performance tests at this link although they are now a bit out of date. This function is much faster as of Rev 09,
 which was built specifically for use in SQL Server 2012 and above andd is about twice as fast as the version
 document in the article.

 CROSS APPLY Usage Examples and Tests:
-- TEST 1:
-- This tests for various possible conditions in a string using a comma as the delimiter.  The expected results are
-- laid out in the comments
--===== Conditionally drop the test tables to make reruns easier for testing.
     -- (this is NOT a part of the solution)
--===== Create and populate a test table on the fly (this is NOT a part of the solution).
     -- In the following comments, "b" is a blank and "E" is an element in the left to right order.
     -- Double Quotes are used to encapsulate the output of "Item" so that you can see that all blanks
     -- are preserved no matter where they may appear.
   INTO #JBMTest
   FROM (                                               --# of returns & type of Return Row(s)
         SELECT  0, NULL                      UNION ALL --1 NULL
         SELECT  1, SPACE(0)                  UNION ALL --1 b (Empty String)
         SELECT  2, SPACE(1)                  UNION ALL --1 b (1 space)
         SELECT  3, SPACE(5)                  UNION ALL --1 b (5 spaces)
         SELECT  4, ','                       UNION ALL --2 b b (both are empty strings)
         SELECT  5, '55555'                   UNION ALL --1 E
         SELECT  6, ',55555'                  UNION ALL --2 b E
         SELECT  7, ',55555,'                 UNION ALL --3 b E b
         SELECT  8, '55555,'                  UNION ALL --2 b B
         SELECT  9, '55555,1'                 UNION ALL --2 E E
         SELECT 10, '1,55555'                 UNION ALL --2 E E
         SELECT 11, '55555,4444,333,22,1'     UNION ALL --5 E E E E E 
         SELECT 12, '55555,4444,,333,22,1'    UNION ALL --6 E E b E E E
         SELECT 13, ',55555,4444,,333,22,1,'  UNION ALL --8 b E E b E E E b
         SELECT 14, ',55555,4444,,,333,22,1,' UNION ALL --9 b E E b b E E E b
         SELECT 15, ' 4444,55555 '            UNION ALL --2 E (w/Leading Space) E (w/Trailing Space)
         SELECT 16, 'This,is,a,test.'         UNION ALL --4 E E E E
         SELECT 17, ',,,,,,'                            --7 (All Empty Strings)
        ) d (SomeID, SomeValue)
--===== Split the CSV column for the whole table using CROSS APPLY (this is the solution)
 SELECT test.SomeID, test.SomeValue, split.ItemNumber, Item = QUOTENAME(split.Item,'"')
   FROM #JBMTest test
  CROSS APPLY dbo.DelimitedSplit8K(test.SomeValue,',') split
-- TEST 2:
-- This tests for various "alpha" splits and COLLATION using all ASCII characters from 0 to 255 as a delimiter against
-- a given string.  Note that not all of the delimiters will be visible and some will show up as tiny squares because
-- they are "control" characters.  More specifically, this test will show you what happens to various non-accented 
-- letters for your given collation depending on the delimiter you chose.
cteBuildAllCharacters (String,Delimiter) AS 
   FROM master.sys.all_columns
 SELECT ASCII_Value = ASCII(c.Delimiter), c.Delimiter, split.ItemNumber, Item = QUOTENAME(split.Item,'"')
   FROM cteBuildAllCharacters c
  CROSS APPLY dbo.DelimitedSplit8K(c.String,c.Delimiter) split
  ORDER BY ASCII_Value, split.ItemNumber

 Other Notes:
 1. Optimized for VARCHAR(8000) or less.  No testing or error reporting for truncation at 8000 characters is done.
 2. Optimized for single character delimiter.  Multi-character delimiters should be resolved externally from this 
 3. Optimized for use with CROSS APPLY.
 4. Does not "trim" elements just in case leading or trailing blanks are intended.
 5. If you don't know how a Tally table can be used to replace loops, please see the following...
 6. Changing this function to use a MAX datatype will cause it to run twice as slow.  It's just the nature of 
    MAX datatypes whether it fits in-row or not.

 This code is the product of many people's efforts including but not limited to the folks listed in the Revision
 History below:

 I also thank whoever wrote the first article I ever saw on "numbers tables" which is located at the following URL
 and to Adam Machanic for leading me to it many years ago.  The link below no long works but has been preserved herer
 for posterity sake.

 The original article can be seen at then following special site, as least as of 29 Sep 2019.

 Revision History:
 Rev 00 - 20 Jan 2010 - Concept for inline cteTally: Itzik-Ben Gan, Lynn Pettis and others.
                        Redaction/Implementation: Jeff Moden 
        - Base 10 redaction and reduction for CTE.  (Total rewrite)

 Rev 01 - 13 Mar 2010 - Jeff Moden
        - Removed one additional concatenation and one subtraction from the SUBSTRING in the SELECT List for that tiny
          bit of extra speed.

 Rev 02 - 14 Apr 2010 - Jeff Moden
        - No code changes.  Added CROSS APPLY usage example to the header, some additional credits, and extra 

 Rev 03 - 18 Apr 2010 - Jeff Moden
        - No code changes.  Added notes 7, 8, and 9 about certain "optimizations" that don't actually work for this
          type of function.

 Rev 04 - 29 Jun 2010 - Jeff Moden
        - Added WITH SCHEMABINDING thanks to a note by Paul White.  This prevents an unnecessary "Table Spool" when the
          function is used in an UPDATE statement even though the function makes no external references.

 Rev 05 - 02 Apr 2011 - Jeff Moden
        - Rewritten for extreme performance improvement especially for larger strings approaching the 8K boundary and
          for strings that have wider elements.  The redaction of this code involved removing ALL concatenation of 
          delimiters, optimization of the maximum "N" value by using TOP instead of including it in the WHERE clause,
          and the reduction of all previous calculations (thanks to the switch to a "zero based" cteTally) to just one 
          instance of one add and one instance of a subtract. The length calculation for the final element (not 
          followed by a delimiter) in the string to be split has been greatly simplified by using the ISNULL/NULLIF 
          combination to determine when the CHARINDEX returned a 0 which indicates there are no more delimiters to be
          had or to start with. Depending on the width of the elements, this code is between 4 and 8 times faster on a
          single CPU box than the original code especially near the 8K boundary.
        - Modified comments to include more sanity checks on the usage example, etc.
        - Removed "other" notes 8 and 9 as they were no longer applicable.

 Rev 06 - 12 Apr 2011 - Jeff Moden
        - Based on a suggestion by Ron "Bitbucket" McCullough, additional test rows were added to the sample code and
          the code was changed to encapsulate the output in pipes so that spaces and empty strings could be perceived 
          in the output.  The first "Notes" section was added.  Finally, an extra test was added to the comments above.

 Rev 07 - 06 May 2011 - Peter de Heer
        - A further 15-20% performance enhancement has been discovered and incorporated into this code which also 
          eliminated the need for a "zero" position in the cteTally table.

 Rev 08 - 24 Mar 2014 - Eirikur Eiriksson
        - Further performance modification (twice as fast) For SQL Server 2012 and greater by using LEAD to find the
          next delimiter for the current element, which eliminates the need for CHARINDEX, which eliminates the need
          for a second scan of the string being split.

 Rev 09 - 29 Sep 2019 - Jeff Moden
        - Combine the improvements by Peter de Heer and Eirikur Eiriksson for use on SQL Server 2012 and above.
        - Add Test 17 to the test code above.
        - Modernize the generation of the embedded "Tally" generation available as of 2012. There's no significant
          performance increase but it makes the code much shorter and easier to understand.
        - Check/change all URLs in the notes abobe to ensure that they're still viable. 
        - Add a binary collation for a bit more of an edge on performance.
        - Removed "Other Note" #7 above as UNPIVOT is no longern applicable (never was for performance).
--=========== Define I/O parameters
              (@pString VARCHAR(8000), @pDelimiter CHAR(1)) 
--=========== "Inline" CTE Driven "Tally Table” produces values from 0 up to 10,000, enough to cover VARCHAR(8000).
   WITH E1(N) AS (SELECT N FROM (VALUES (1),(1),(1),(1),(1),(1),(1),(1),(1),(1))E0(N))
       ,E4(N) AS (SELECT 1 FROM E1 a, E1 b, E1 c, E1 d)
 ,cteTally(N) AS (--==== This provides the "base" CTE and limits the number of rows right up front
                      -- for both a performance gain and prevention of accidental "overruns"
,cteStart(N1) AS (--==== This returns N+1 (starting position of each "element" just once for each delimiter)
                 SELECT 1 UNION ALL
                 SELECT t.N+1 FROM cteTally t WHERE SUBSTRING(@pString COLLATE Latin1_General_BIN,t.N,1) 
                                                  = @pDelimiter COLLATE Latin1_General_BIN
--=========== Do the actual split. 
           -- The ISNULL/NULLIF combo handles the length for the final element when no delimiter is found.
       SELECT ItemNumber = ROW_NUMBER() OVER (ORDER BY s.N1)
            , Item       = SUBSTRING(@pString,s.N1,ISNULL(NULLIF((LEAD(s.N1,1,1) OVER (ORDER BY s.N1)-1),0)-s.N1,8000))
         FROM cteStart s

If you don't have SQL Server 2022 or above (thinking of the future), then install the above function in your database.

Once that's done, things like your described problem become both easy and fast for strings up to VARCHAR(8000).

First, here's the test data you were kind enough to post but rewritten as a TEMP Table, just to make testing easier.

--===== This creates the test data as a TEMP Table to make testing easier.
 CREATE TABLE #MyTable1 (CustomerId INT, InvoiceData VARCHAR(1000));
        (CustomerID, InvoiceData)
 VALUES  (1, '2022/01/31;INV001;125.50;2022/02/28;INV002;86.25')
        ,(2, '2022/01/20;INV023;726.26;2022/02/14;INV043;200.50;2022/03/17;INV067;453.85')

Here's the pre-2022 code to solve the issue. It uses the function above and is nasty fast for all the reasons previously identified in the cited articles.

 SELECT t.CustomerID
        ,Row  = (split.ItemNumber-1)/3
        ,Col  = (split.ItemNumber-1)%3
        ,Item = split.Item
   FROM #MyTable1 t
  CROSS APPLY dbo.DelimitedSplit8k(InvoiceData,';')split
 SELECT  CustomerID
        ,InvoiceDate   = TRY_CONVERT(DATETIME   ,MAX(IIF(Col = 0,Item,NULL)))
        ,InvoiceNo     = TRY_CONVERT(VARCHAR(20),MAX(IIF(Col = 1,Item,NULL)))
        ,InvoiceAmount = TRY_CONVERT(MONEY      ,MAX(IIF(Col = 2,Item,NULL)))
   FROM cteEAV
  GROUP BY CustomerID,Row
  ORDER BY CustomerID,InvoiceDate

Here are the results from that code.


If you DO have 2022 (or better in the future), then you don't need to use the function above because they finally fixed the STRING_SPLIT() function to optionally include returning the original position of each string. All you need is the code below.

 SELECT t.CustomerID
        ,Row  = (split.ordinal-1)/3
        ,Col  = (split.ordinal-1)%3
        ,Item = split.value
   FROM #MyTable1 t
  CROSS APPLY STRING_SPLIT(InvoiceData,';',1)split
 SELECT  CustomerID
        ,InvoiceDate   = TRY_CONVERT(DATETIME   ,MAX(IIF(Col = 0,Item,NULL)))
        ,InvoiceNo     = TRY_CONVERT(VARCHAR(20),MAX(IIF(Col = 1,Item,NULL)))
        ,InvoiceAmount = TRY_CONVERT(MONEY      ,MAX(IIF(Col = 2,Item,NULL)))
   FROM cteEAV
  GROUP BY CustomerID,Row
  ORDER BY CustomerID,InvoiceDate

Here are the results from that nearly identical code.

Yes, the XML splitter that Robert used will work but you run into "entitization", the fix for which will make it twice as slow and it also uses concatenation, which slows things down a lot for larger strings.

1 Like

Hi Robert. This is genius. I don't 100% understand the code, although I will try and get my head around it at some point. I have slotted in my actual tables/field and it works a treat.

Thanks so much for taking the time to provide an answer.


Thank you. Make sure to read @JeffModen 's post and the accompanying links too, they're amazingly good.


Thank you for the very kind words.

And, thank you VERY much for the write-up you did to explain your code. I'm not very good when it comes to XML so it helped me and it's going to help a lot of other folks. Well done, good Sir!