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SSC Veteran
      
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SSChampion
        
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Not only is it important to name columns (as opposed to using '*') - it is important to name them and return them in the same order!
Nothing in the 'MAV' query guarantees the order of column names returned. Use FOR XML PATH with an explicit ORDER BY clause instead (it's faster and entirely documented):
SELECT STUFF( ( SELECT N',' + sc.name FROM sys.columns sc WHERE sc.[object_id] = OBJECT_ID(N'dbo.Widget', N'U') ORDER BY sc.column_id ASC FOR XML PATH(''), TYPE ).value(N'.[1]', 'NVARCHAR(MAX)'), 1, 1, '');
Paul White SQL Server MVP SQLblog.com @SQL_Kiwi
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Say Hey Kid
      
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A quick note on that trailing comma. Instead of
select @col_list = @col_list + col + ', ' which leaves the trailing comma that must be taken off, you might try
set @col_list = null -- though defaults to null when defined... select @col_list = nullif(@col_list + ',', '') + col
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Mr or Mrs. 500
      
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I can see where this could come in handly during ETL processes.
In regards to creating a delimited list see the example here on MSDN http://msdn2.microsoft.com/en-us/library/ms131056.aspx. Using a CLR it will create a comma delimited list. Since it's an Aggregate Function you can use it just like any other aggregate which makes it really handy.
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Grasshopper
      
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Hi Stephen, I was wondering if there's a reason you use information_schema rather than the new sys.columns? Backwards compatibility? I believe in 2005 onwards information_schema is just a wrapper for the new object views (sys.columns, sys.objects, etc.)...
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Grasshopper
      
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Thanks for the article, I use this "feature" quite a bit. One of mine is similar to yours, I have a script that creates insert statements using column names in order to reduce the size of our production database for testing purposes. We copy over only the records we want from the production db into an empty db, the process is much faster than deleting and resizing the db.
I realize that your article is just for explanation purposes, but when I compare the contents of two tables that have the same structure, I use the CheckSum_Agg() and CheckSum() functions. You can start by comparing the entire tables with just one checksum value. If the values don't match, you can show the rows that differ by comparing each row's checksum with the checksum of the corresponding tables row (using primary keys to match rows).
Syntax is:
SELECT CheckSum_Agg(CheckSum(*)) FROM TableName SELECT Checksum(*) FROM TableName WHERE PrimaryKey=1
Paul
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SSC Journeyman
      
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Nice article. A minor nit-pick. You need to initialize the @col variable to an empty string befory running the MAV query. Otherwise, your result will be NULL.
I've also used this for quick and dirty CSV list generation. For long lists, though, say over 500 elements, a FOR XML query, like Paul White's above, is much faster.
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Old Hand
      
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Now, in a previous post of mine discussing comparing tables using EXCEPT <reference>, I noted that it is best practice to explicitly name your columns in any query using EXCEPT.
I saw this in your previous article, but didn't respond to it there...I think you're wrong, and that this is one of the rare instances where it's best NOT to explicitly name your columns. If the column order is different between the two tables, then there may be other differences as well. Of course there can be other differences without the column order being different or the column order could be the only difference, but since it's simpler to use * and the failure provides you with useful information (that the structure of the two tables has branched at some point), that's what I'd use. Of course you may need to do the comparision in any case, in which case todays script can come in handy.
Speaking of todays script, using @col_list = IsNull(@col_list +',' , '') + col
prevents having to delete a trailing comma.
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Forum Newbie
      
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If the purpose of this script is to detect whether two tables with identical structure have different data, it might be nice to check the row counts before jumping into a potentially expensive comparison.
Just a thought.
Carl Anderson Data Architect, Northwestern University
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SSChampion
        
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@viacoboni: a construction using COALESCE is normally used, but in any case I can see no reason to prefer any variation of the method over the FOR XML solution (documented, supported, and faster...)
@Bradley Deem: True - and I am a great fan of appropriate CLR usage; however, FOR XML still performs faster than even a CLR UDA - so a call-out to the hosted CLR seems unnecessary...unless you have special requirements of course!
@yaadman: Absoutely - and I was going to include a quote from BOL to make the point that system views are preferred over INFORMATION_SCHEMA...but I didn't want to pile on too much I agree that it is rarely better to use anything other than the system views like sys.columns in this case.
@pbarbin: Yes - there are many better approaches to this sort of problem - and carl.anderson mentions another worthwhile optimization in a later post (checking row counts). HashBytes, CHECKSUM, the TableDiff utility...it is a long list.
@Steve McNamee: Are you saying that the technique used in the article is faster than FOR XML PATH for fewer than 500 elements? Not nit-picking; I just want to be clear on it. For me, the greater problem is that using variables in this way lacks an ORDER guarantee. Incorrect results, even when produced fractionally more quickly, are rarely to be desired 
Good discussion
Paul White SQL Server MVP SQLblog.com @SQL_Kiwi
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