Category Archives: T-SQL

dba_runCHECKDB v2(012)


If you are one among the many that downloaded my consistency check stored procedure called “dba_RunCHECKDB”, you may have noticed a “small” glitch… it doesn’t work on SQL Server 2012!

This is due to the resultset definition of DBCC CHECKDB, which has changed again in SQL Server 2012. Trying to pipe the results of that command in the table definition for SQL Server 2008 produces a column mismatch and it obviously fails.

Fixing the code is very easy indeed, but I could never find the time to post the corrected version until today.

Also, I had to discover the new table definition for DBCC CHECKDB, and it was not just as easy as it used to be in SQL Server 2008. In fact, a couple of days ago I posted a way to discover the new resultset definition working around the cumbersome metadata discovery feature introduced in SQL Server 2012.

Basically, the new output of DBCC CHECKDB now includes 6 new columns:

    CREATE TABLE ##DBCC_OUTPUT(
        Error int NULL,
        [Level] int NULL,
        State int NULL,
        MessageText nvarchar(2048) NULL,
        RepairLevel nvarchar(22) NULL,
        Status int NULL,
        DbId int NULL, -- was smallint in SQL2005
        DbFragId int NULL,      -- new in SQL2012
        ObjectId int NULL,
        IndexId int NULL,
        PartitionId bigint NULL,
        AllocUnitId bigint NULL,
        RidDbId smallint NULL,  -- new in SQL2012
        RidPruId smallint NULL, -- new in SQL2012
        [File] smallint NULL,
        Page int NULL,
        Slot int NULL,
        RefDbId smallint NULL,  -- new in SQL2012
        RefPruId smallint NULL, -- new in SQL2012
        RefFile smallint NULL,  -- new in SQL2012
        RefPage int NULL,
        RefSlot int NULL,
        Allocation smallint NULL
    )

If you Google the name of one of these new columns, you will probably find a lot of blog posts (no official documentation, unfortunately) that describes the new output of DBCC CHECKDB, but none of them is strictly correct: all of them indicate the smallint columns as int.

Not a big deal, actually, but still incorrect.

I will refrain from posting the whole procedure here: I updated the code in the original post, that you can find clicking here. You can also download the code from the Code Repository.

As usual, suggestions and comments are welcome.

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Discovering resultset definition of DBCC commands in SQL Server 2012


Back in 2011 I showed a method to discover the resultset definition of DBCC undocumented commands.

At the time, SQL Server 2012 had not been released yet and nothing suggested that the linked server trick could stop working on the new major version. Surprisingly enough it did.

If you try to run the same code showed in that old post on a 2012 instance, you will get a quite explicit error message:

DECLARE @srv nvarchar(4000);
SET @srv = @@SERVERNAME; -- gather this server name

-- Create the linked server
EXEC master.dbo.sp_addlinkedserver
    @server     = N'LOOPBACK',
    @srvproduct = N'SQLServ', -- it’s not a typo: it can’t be “SQLServer”
    @provider   = N'SQLNCLI', -- change to SQLOLEDB for SQLServer 2000
    @datasrc    = @srv;

-- Set the authentication to "current security context"
EXEC master.dbo.sp_addlinkedsrvlogin
    @rmtsrvname  = N'LOOPBACK',
    @useself     = N'True',
    @locallogin  = NULL,
    @rmtuser     = NULL,
    @rmtpassword = NULL;

USE tempdb;
GO

CREATE PROCEDURE loginfo
AS
BEGIN
    SET NOCOUNT ON;

    DBCC LOGINFO();
END
GO

SELECT *
INTO tempdb.dbo.loginfo_output
FROM OPENQUERY(LOOPBACK, 'SET FMTONLY OFF; EXEC tempdb.dbo.loginfo');

DROP PROCEDURE loginfo;
GO
Msg 11528, Level 16, State 1, Procedure sp_describe_first_result_set, Line 1
The metadata could not be determined because statement 'DBCC LOGINFO();' in procedure 'loginfo' does not support metadata discovery.

This behaviour has to do with the way SQL Server 2012 tries to discover metadata at parse/bind time, when the resultset is not available yet for DBCC commands.

Fortunately, there is still a way to discover metadata when you have a SQL Server instance of a previous version available.

On my laptop I have a 2008R2 instance I can use to query the 2012 instance with a linked server:

-- run this on the 2008R2 instance
USE [master]
GO

EXEC master.dbo.sp_addlinkedserver
     @server = N'LOCALHOST\SQL2012'
    ,@srvproduct = N'SQL Server'

EXEC master.dbo.sp_addlinkedsrvlogin
     @rmtsrvname = N'LOCALHOST\SQL2012'
    ,@useself = N'True'
    ,@locallogin = NULL
    ,@rmtuser = NULL
    ,@rmtpassword = NULL
GO

SELECT *
INTO tempdb.dbo.loginfo_output
FROM OPENQUERY([LOCALHOST\SQL2012], 'SET FMTONLY OFF; EXEC tempdb.dbo.loginfo');
GO

This code pipes the results of the DBCC command into a table in the tempdb database in my 2008R2 instance. The table can now be scripted using SSMS:

Using the 2008R2 instance as a “Trojan Horse” for the metadata discovery, you can see that the resultset definition of DBCC LOGINFO() has changed again in SQL Server 2012:

CREATE TABLE [dbo].[loginfo_output](
	[RecoveryUnitId] [int] NULL,  -- new in SQL2012
	[FileId] [int] NULL,
	[FileSize] [bigint] NULL,
	[StartOffset] [bigint] NULL,
	[FSeqNo] [int] NULL,
	[Status] [int] NULL,
	[Parity] [tinyint] NULL,
	[CreateLSN] [numeric](25, 0) NULL
)

This trick will be particularly useful for an upcoming (and long overdue) post, so… stay tuned!

Using QUERYTRACEON in plan guides


Yesterday the CSS team made the QUERYTRACEON hint publicly documented.

This means that now it’s officially supported and you can use it in production code.

After reading the post on the CSS blog, I started to wonder whether there is some actual use in production for this query hint, given that it requires the same privileges as DBCC TRACEON, which means you have to be a member of the sysadmin role.

In fact, if you try to use that hint when connected as a low privileged user, you get a very precise error message, that leaves no room for interpretation:

SELECT *
FROM [AdventureWorks2012].[Person].[Person]
OPTION (QUERYTRACEON 4199)

Msg 2571, Level 14, State 3, Line 1
User ‘guest’ does not have permission to run DBCC TRACEON.

How can a query hint available to sysadmins only be possibly useful for production?

I posted my doubt on Twitter using the #sqlhelp hashtag and got interesting replies from Paul Randal, Paul White and Robert Davis.

My concerns were not about the usefulness of the hint per se, but about the usefulness in production code. Often 140 chars are not enough when you want to express your thoughts clearly, in fact I decided to write this blog post to clarify what I mean.

As we have seen, the QUERYTRACEON query hint cannot be used directly by users not in the sysadmin role, but it can be used in stored procedures with “EXECUTE AS owner” and in plan guides.

While it’s completely clear what happens when the hint is used in procedures executed in the context of the owner, what happens in plan guides is not so obvious (at least, not to me). In fact, given that the secuirty context is not changed when the plan guide is matched and applied, I would have expected it to fail miserably when executed by a low privileged user, but it’s not the case.

Let’s try and see what happens:

First of all we need a query “complex enough” to let the optimizer take plan guides into account. A straight “SELECT * FROM table” and anything else that results in a trivial plan won’t be enough.

SELECT *
FROM [Person].[Person] AS P
INNER JOIN [Person].[PersonPhone] AS H
    ON P.BusinessEntityID = H.BusinessEntityID
INNER JOIN [Person].[BusinessEntity] AS BE
    ON P.BusinessEntityID = BE.BusinessEntityID
INNER JOIN [Person].[BusinessEntityAddress] AS BEA
    ON BE.BusinessEntityID = BEA.BusinessEntityID
WHERE BEA.ModifiedDate > '20080101'

Then we need a plan guide to apply the QUERYTRACEON hint:

EXEC sp_create_plan_guide @name = N'[querytraceon]', @stmt = N'SELECT *
FROM [Person].[Person] AS P
INNER JOIN [Person].[PersonPhone] AS H
	ON P.BusinessEntityID = H.BusinessEntityID
INNER JOIN [Person].[BusinessEntity] AS BE
	ON P.BusinessEntityID = BE.BusinessEntityID
INNER JOIN [Person].[BusinessEntityAddress] AS BEA
	ON BE.BusinessEntityID = BEA.BusinessEntityID
WHERE BEA.ModifiedDate > ''20080101''', @type = N'SQL', @hints = N'OPTION (QUERYTRACEON 4199)'

If we enable the plan guide and try to issue this query in the context of a low privileged user, we can see no errors thrown any more:

CREATE LOGIN testlogin WITH PASSWORD = 'testlogin123';
GO
USE AdventureWorks2012;
GO
CREATE USER testlogin FOR LOGIN testlogin;
GO
GRANT SELECT TO testlogin;
GO
EXECUTE AS USER = 'testlogin';
GO
SELECT *
FROM [Person].[Person] AS P
INNER JOIN [Person].[PersonPhone] AS H
    ON P.BusinessEntityID = H.BusinessEntityID
INNER JOIN [Person].[BusinessEntity] AS BE
    ON P.BusinessEntityID = BE.BusinessEntityID
INNER JOIN [Person].[BusinessEntityAddress] AS BEA
    ON BE.BusinessEntityID = BEA.BusinessEntityID
WHERE BEA.ModifiedDate > '20080101';
GO
REVERT;
GO

If we open a profiler trace and capture the “Plan Guide Successful” and “Plan Guide Unsuccessful” events, we can see that the optimizer matches the plan guide and enforces the use of the query hint.

Lesson learned: even if  users are not allowed to issue that particular query hint directly, adding it to a plan guide is a way to let anyone use it indirectly.

Bottom line is OPTION QUERYTRACEON can indeed be very useful when we identify some queries that obtain a decent query plan only when a specific trace flag is active and we don’t want to enable it for the whole instance. In those cases, a plan guide or a stored procedure in the owner’s context can be the answer.

Replaying Workloads with Distributed Replay


A couple of weeks ago I posted a method to convert trace files from the SQL Server 2012 format to the SQL Server 2008 format.

The trick works quite well and the trace file can be opened with Profiler or with ReadTrace from RML Utilities. What doesn’t seem to work just as well is the trace replay with Ostress (another great tool bundled in the RML Utilities).

For some reason, OStress refuses to replay the whole trace file and starts throwing lots of errors.

Some errors are due to the workload I was replaying (it contains CREATE TABLE statements and that can obviuosly work just the first time it is issued), but some others seem to be due to parsing errors, probably because of differences in the trace format between version 11 and 10.

11/20/12 12:30:39.008 [0x00001040] File C:\RML\SQL00063.rml: Parser Error: [Error: 60500][State: 1][Abs Char: 1068][Seq: 0] Syntax error [parse error, expecting `tok_RML_END_RPC'] encountered near
0x0000042C: 6C000D00 0A005700 48004500 52004500 l.....W.H.E.R.E.
0x0000043C: 20005500 6E006900 74005000 72006900  .U.n.i.t.P.r.i.
0x0000044C: 63006500 20002600 6C007400 3B002000 c.e. .&.l.t.;. .
0x0000045C: 24003500 2E003000 30000D00 0A004F00 $.5...0.0.....O.
0x0000046C: 52004400 45005200 20004200 59002000 R.D.E.R. .B.Y. .
0x0000047C: 50007200 6F006400 75006300 74004900 P.r.o.d.u.c.t.I.
0x0000048C: 44002C00 20004C00 69006E00 65005400 D.,. .L.i.n.e.T.
0x0000049C: 6F007400 61006C00 3B000D00 0A003C00 o.t.a.l.;.....<. 0x000004AC: 2F004300 4D004400 3E000D00 0A003C00 /.C.M.D.>.....<. 0x000004BC: 2F004C00 41004E00 47003E00 0D000A00 /.L.A.N.G.>.....
0x000004CC:

11/20/12 12:30:39.010 [0x00001040] File C:\RML\SQL00063.rml: Parser Error: [Error: 110010][State: 100][Abs Char: 1068][Seq: 0] SYNTAX ERROR: Parser is unable to safely recover. Correct the errors and try again.

The error suggests that the two formats are indeed more different than I supposed, thus making the replay with Ostress a bit unrealiable.

Are there other options?

Sure there are! Profiler is another tool that allows replaying the workload, even if some limitations apply. For instance, Profiler cannot be scripted, which is a huge limitation if you are using Ostress in benchmarking script and want to replace it with something else.

That “something else” could actually be the Distributed Replay feature introduced in SQL Server 2012.

Basically, Distributed Replay does the same things that Ostress does and even more, with the nice addition of the possibility to start the replay on multiple machines, thus simulating a workload that resembles more the one found in production.

An introduction to Distributed Replay can be found on Jonathan Kehayias’ blog and I will refrain from going into deep details here: those posts are outstanding and there’s very little I could add to that.

Installing the Distributed Replay feature

The first step for the installation is adding a new user for the distributed replay services. You could actually use separate accounts for the Controller and Client services, but for a quick demo a single user is enough.

The Distributed Replay Controller and Client features must be selected from the Feature Selection dialog of SQLServer setup:

In the next steps of the setup you will also be asked the service accounts to use for the services and on the Replay Client page you will have to enter the controller name and the working directories.

Once the setup is over, you will find two new services in the Server Manager:

After starting the services (first the Controller, then the Client), you can go to the log directories and check in the log files if everything is working.

The two files to check are in the following folders:

  • C:\Program Files (x86)\Microsoft SQL Server\110\Tools\DReplayController\Log
  • C:\Program Files (x86)\Microsoft SQL Server\110\Tools\DReplayClient\Log

Just to prove one more time that “if something can wrong, it will”, the client log will probably contain an obnoxious error message.

DCOM gotchas

Setting up the distributed replay services can get tricky because of some permissions needed to let the client connect to the controller. Unsurprisingly, the client/controller communication is provided by DCOM, which must be configured correctly.

Without granting the appropriate permissions, in the distributed replay client log file you may find the following message:

2012-11-03 00:43:04:062 CRITICAL     [Client Service]      [0xC8100005 (6)] Failed to connect controller with error code 0x80070005.

In practical terms, the service account that executes the distributed replay controller service must be granted permissions to use the DCOM class locally and through the network:

  1. Run dcomcnfg.exe
  2. Navigate the tree to Console Root, Component Services, Computers, My Computer, DCOM Config, DReplayController
  3. Right click DReplayController and choose “properties” from the context menu.
  4. Click the Security tab
  5. Click the “Launch and Activation Permissions” edit button and grant  “Local Activation” and “Remote Activation” permissions to the service account
  6. Click the “Access Permissions” edit button and grant “Local Access” and “Remote Access” permissions to the service account
  7. Add the service user account to the “Distributed COM Users” group
  8. Restart the distributed replay controller and client services

After restarting the services, you will find that the message in the log file has changed:

2012-11-20 14:01:10:783 OPERATIONAL  [Client Service]      Registered with controller "WIN2012_SQL2012".

Using the Replay feature

Once the services are successfully started, we can now start using the Distributed Replay feature.

The trace file has to meet the same requirements for replay found in Profiler, thus making the “Replay” trace template suitable for the job.

But there’s one more step needed before we can replay the trace file, which cannot be replayed directly. In fact, distributed replay needs to work on a trace stub, obtained preprocessing the original trace file.

The syntax to obtain the stub is the following:

"C:\Program Files (x86)\Microsoft SQL Server\110\Tools\Binn\dreplay.exe" preprocess -i "C:\SomePath\replay_trace.trc" -d "C:\SomePath\preprocessDir"

Now that the trace stub is ready, we can start the replay admin tool from the command line, using the following syntax:

"C:\Program Files (x86)\Microsoft SQL Server\110\Tools\Binn\dreplay.exe" replay -s "targetServerName" -d "C:\SomePath\preprocessDir" -w "list,of,allowed,client,names"

A final word

A comparison of the features found in the different replay tools can be found in the following table:

Profiler Ostress Distributed Replay
Multithreading YES YES YES
Debugging YES NO NO
Synchronization mode NO YES YES
Stress mode YES YES YES
Distributed mode NO NO YES
Scriptable NO YES YES
Input format Trace Trace/RML/SQL Trace

The Distributed Replay Controller can act as  a replacement for Ostress, except for the ability to replay SQL and RML files.

Will we be using RML Utilities again in the future? Maybe: it  depends on what Microsoft decides to do with this tool. It’s not unlikely that the Distributed Replay feature will replace the RML Utilities entirely. The tracing feature itself  has an unceartain future ahead, with the deprecation in SQL Server 2012. Probably this new feature will disappear in the next versions of SQLServer, or it will be ported to the Extended Events instrastructure, who knows?

One thing is sure: today we have three tools that support replaying trace files and seeing this possibilty disappear in the future would be very disappointing. I’m sure SQL Server will never disappoint us. 🙂

Convert a Trace File from SQLServer 2012 to SQLServer 2008R2


Recently I started using RML utilities quite a lot.

ReadTrace and Ostress are awesome tools for benchmarking and baselining and many of the features found there have not been fully implemented in SQLServer 2012, though Distributed Replay was a nice addition.

However, as you may have noticed, ReadTrace is just unable to read trace files from SQLServer 2012, so you may get stuck with a trace file you wont’ abe able to process.

When I first hit this issue, I immediately thought I could use a trace table to store the data and then use Profiler again to write back to a trace file.

The idea wasn’t bad, but turns out that Profiler 2012 will always write trace files in the new format, with no way to specify the old one. On the other hand, Profiler2008R2 can’t read trace data from a table written by Profiler2012, throwing an ugly exception:

Interesting! So, looks like Profiler stores version information and other metadata somewhere in the trace table, but where exactly?

It might sound funny, but I had to trace Profiler with Profiler in order to know! Looking at the profiler trace, the first thing that Profiler does when trying to open a trace table is this:

declare @p1 int
set @p1=180150003
declare @p3 int
set @p3=2
declare @p4 int
set @p4=4
declare @p5 int
set @p5=-1
exec sp_cursoropen @p1 output,N'select BinaryData from [dbo].[trace_test] where RowNumber=0',@p3 output,@p4 output,@p5 output
select @p1, @p3, @p4, @p5

So, looks like Profiler stores its metadata in the first row (RowNumber = 0), in binary format.

That was the clue I was looking for!

I loaded a trace file in the old format into another trace table and I started to compare the data to find similarities and differences.

I decided to break the binary headers into Dwords and paste the results in WinMerge to hunt the differences:

-- Break the header row in the trace table into DWords
-- in order to compare easily in WinMerge
SELECT SUBSTRING(data, 8 * (n - 1) + 3, 8) AS dword
	,n AS dwordnum
FROM (
	SELECT CONVERT(VARCHAR(max), CAST(binarydata AS VARBINARY(max)), 1) AS data
	FROM tracetable
	WHERE rownumber = 0
	) AS src
INNER JOIN (
	SELECT DISTINCT ROW_NUMBER() OVER (
			ORDER BY (SELECT NULL)
		) / 8 AS n
	FROM sys.all_columns AS ac
	) AS v
	ON n > 0 AND (n - 1) * 8 <= LEN(data) - 3
ORDER BY 2

If you copy/paste the output in WinMerge you can easily spot the difference around the 100th dword:

Hmmmm, seems promising. Can those “11” and “10” possibly represent the trace version? Let’s try and see.
Now we should just update that section of the header to let the magic happen:

-- Use a table variable to cast the trace
-- header from image to varbinary(max)
DECLARE @header TABLE (
	header varbinary(max)
)

-- insert the trace header into the table
INSERT INTO @header
SELECT binarydata
FROM tracetable
WHERE RowNumber = 0

-- update the byte at offset 390 with version 10 (SQLServer 2008)
-- instead of version 11 (SQLServer 2012)
UPDATE @header
SET header .WRITE(0x0A,390,1)

-- write the header back to the trace table
UPDATE tracetable
SET binarydata = (SELECT header FROM @header)
WHERE RowNumber = 0

The trace table can now be opened with Profiler2008R2 and written back to a trace file. Hooray!
Yes, I know, using a trace table can take a whole lot of time and consume a lot of disk space when the file is huge (and typically RML traces are), but this is the best I could come up with.
I tried to look into the trace file itself, but I could not find a way to diff the binary contents in an editor. You may be smarter than me a give it a try: in that case, please, post a comment here.

Using this trick, ReadTrace can happily process the trace file and let you perform your benchmarks, at least until Microsoft decides to update RML Utilities to 2012.

UPDATE 11/08/2012: The use of a trace table is not necessary: the trace file can be updated in place, using the script found here.

Replay a T-SQL batch against all databases


It’s been quite a lot since I last posted on this blog and I apologize with my readers, both of them :-).

Today I would like to share with you a handy script I coded recently during a SQL Server health check. One of the tools I find immensely valuable for conducting a SQL Server assessment is Glenn Berry’s SQL Server Diagnostic Information Queries. The script contains several queries that can help you collect and analyze a whole lot of information about a SQL Server instance and I use it quite a lot.

The script comes with a blank results spreadsheet, that can be used to save the information gathered by the individual queries. Basically, the spreadsheet is organized in tabs, one for each query and has no preformatted column names, so that you can run the query, select the whole results grid, copy with headers and paste everything to the appropriate tab.

When working with multiple instances, SSMS can help automating this task with multiserver queries. Depending on your SSMS settings, the results of a multiserver query can be merged into a single grid, with an additional column holding the server name.

This feature is very handy, because it lets you run a statement against multiple servers without changing the statement itself.

This works very well for the queries in the first part of Glenn Berry’s script, which is dedicated to instance-level checks. The second part of the script is database-specific and you have to repeat the run+copy+paste process for each database in your instance.

It would be great if there was a feature in SSMS that allowed you to obtain the same results as the multiserver queries, scaled down to the database level. Unfortunately, SSMS has no such feature and  the only possible solution is to code it yourself… or borrow my script!

Before rushing to the code, let’s describe briefly the idea behind and the challenges involved.

It would be quite easy to take a single statement and use it with sp_MsForEachDB, but this solution has several shortcomings:

  • The results would display as individual grids
  • There would be no easy way to determine which results grid belongs to which database
  • The statement would have to be surrounded with quotes and existing quotes would have to be doubled, with an increased and unwanted complexity

The ideal tool for this task should simply take a statement and run it against all [user] databases without modifying the statement at all, merge the results in a single result set and add an additional column to hold the database name. Apparently, sp_MSForEachDB, besides being undocumented and potentially nasty, is not the right tool for the job.

That said, the only option left is to capture the statement from its query window, combining a trace, a loopback linked server and various other tricks.

Here’s the code:


-- =============================================
-- Author:      Gianluca Sartori - @spaghettidba
-- Create date: 2012-06-26
-- Description: Records statements to replay
--              against all databases.
-- =============================================
CREATE PROCEDURE replay_statements_on_each_db
    @action varchar(10) = 'RECORD',
    @start_statement_id int = NULL,
    @end_statement_id   int = NULL
AS
BEGIN

    SET NOCOUNT ON;

    DECLARE @TraceFile nvarchar(256);
    DECLARE @TraceFileNoExt nvarchar(256);
    DECLARE @LastPathSeparator int;
    DECLARE @TracePath nvarchar(256);
    DECLARE @TraceID int;
    DECLARE @fs bigint = 5;
    DECLARE @r int;
    DECLARE @spiid int = @@SPID;
    DECLARE @srv nvarchar(4000);
    DECLARE @ErrorMessage nvarchar(4000);
    DECLARE @ErrorSeverity int;
    DECLARE @ErrorState int;
    DECLARE @sql nvarchar(max);
    DECLARE @statement nvarchar(max);
    DECLARE @column_list nvarchar(max);

    IF @action NOT IN ('RECORD','STOPRECORD','SHOWQUERY','REPLAY')
        RAISERROR('A valid @action (RECORD,STOPRECORD,SHOWQUERY,REPLAY) must be specified.',16,1)

    -- *********************************************** --
    -- *                 RECORD                      * --
    -- *********************************************** --
    IF @action = 'RECORD'
    BEGIN

        BEGIN TRY

            -- Identify the path of the default trace
            SELECT @TraceFile = path
            FROM master.sys.traces
            WHERE id = 1

            -- Split the directory / filename parts of the path
            SELECT @LastPathSeparator = MAX(number)
            FROM master.dbo.spt_values
            WHERE type = 'P'
                  AND number BETWEEN 1 AND LEN(@tracefile)
                  AND CHARINDEX('\', @TraceFile, number) = number
            --' fix WordPress's sql parser quirks'

            SELECT @TraceFile =
                  SUBSTRING(
                         @TraceFile
                        ,1
                        ,@LastPathSeparator
                  )
                  + 'REPLAY_'
                  + CONVERT(char(8),GETDATE(),112)
                  + REPLACE(CONVERT(varchar(8),GETDATE(),108),':','')
                  + '.trc'

            SET @TraceFileNoExt = REPLACE(@TraceFile,N'.trc',N'')

            -- create trace
            EXEC sp_trace_create @TraceID OUTPUT, 0, @TraceFileNoExt, @fs, NULL;

            --add filters and events
            EXEC sp_trace_setevent @TraceID, 41, 1, 1;
            EXEC sp_trace_setevent @TraceID, 41, 12, 1;
            EXEC sp_trace_setevent @TraceID, 41, 13, 1;

            EXEC sp_trace_setfilter @TraceID, 1, 0, 7, N'%fn_trace_gettable%'
            EXEC sp_trace_setfilter @TraceID, 1, 0, 7, N'%replay_statements_on_each_db%'
            EXEC sp_trace_setfilter @TraceID, 12, 0, 0, @spiid

            --start the trace
            EXEC sp_trace_setstatus @TraceID, 1

            --create a global temporary table to store the statements
            IF OBJECT_ID('tempdb..##replay_info') IS NOT NULL
                DROP TABLE ##replay_info;

            CREATE TABLE ##replay_info (
                trace_id int,
                statement_id int,
                statement_text nvarchar(max)
            );

            --save the trace id in the global temp table
            INSERT INTO ##replay_info (trace_id) VALUES(@TraceID);

        END TRY
        BEGIN CATCH

            --cleanup the trace
            IF EXISTS( SELECT 1 FROM sys.traces WHERE id = @TraceId AND status = 1 ) EXEC sp_trace_setstatus @TraceID, 0;
            IF EXISTS( SELECT 1 FROM sys.traces WHERE id = @TraceId AND status = 0 ) EXEC sp_trace_setstatus @TraceID, 2;

            IF OBJECT_ID('tempdb..##replay_info') IS NOT NULL
                DROP TABLE ##replay_info;

            SELECT @ErrorMessage  = ERROR_MESSAGE(),
                   @ErrorSeverity = ERROR_SEVERITY(),
                   @ErrorState    = ERROR_STATE();

            RAISERROR(@ErrorMessage, @ErrorSeverity, @ErrorState);

        END CATCH

    END

    -- *********************************************** --
    -- *              STOP RECORDING                 * --
    -- *********************************************** --
    IF @action = 'STOPRECORD'
    BEGIN

        BEGIN TRY

            -- gather the trace id
            SELECT @TraceID = trace_id
            FROM ##replay_info;

            IF @TraceId IS NULL
                RAISERROR('No data has been recorded!',16,1)

            DELETE FROM ##replay_info;

            -- identify the trace file
            SELECT TOP(1) @TraceFile = path
            FROM sys.traces
            WHERE path like '%REPLAY[_]______________.trc'
            ORDER BY id DESC

            -- populate the global temporary table with
            -- the statements recorded in the
            INSERT INTO ##replay_info
            SELECT @TraceID,
                ROW_NUMBER() OVER(ORDER BY (SELECT NULL)),
                TextData
            FROM fn_trace_gettable(@traceFile, DEFAULT)
            WHERE TextData IS NOT NULL;

            --stop and deltete the trace
            IF EXISTS( SELECT 1 FROM sys.traces WHERE id = @TraceId AND status = 1 ) EXEC sp_trace_setstatus @TraceID, 0;
            IF EXISTS( SELECT 1 FROM sys.traces WHERE id = @TraceId AND status = 0 ) EXEC sp_trace_setstatus @TraceID, 2;

        END TRY
        BEGIN CATCH

            --stop and deltete the trace
            IF EXISTS( SELECT 1 FROM sys.traces WHERE id = @TraceId AND status = 1 ) EXEC sp_trace_setstatus @TraceID, 0;
            IF EXISTS( SELECT 1 FROM sys.traces WHERE id = @TraceId AND status = 0 ) EXEC sp_trace_setstatus @TraceID, 2;

            SELECT @ErrorMessage  = ERROR_MESSAGE(),
                   @ErrorSeverity = ERROR_SEVERITY(),
                   @ErrorState    = ERROR_STATE();

            RAISERROR(@ErrorMessage, @ErrorSeverity, @ErrorState);

        END CATCH

    END

    -- *********************************************** --
    -- *           SHOW COLLECTED QUERIES            * --
    -- *********************************************** --
    IF @action = 'SHOWQUERY'
    BEGIN
        BEGIN TRY

            IF OBJECT_ID('tempdb..##replay_info') IS NULL
                RAISERROR('No data has been recorded yet',16,1);

            SET @sql = 'SELECT statement_id, statement_text FROM ##replay_info ';

            IF @start_statement_id IS NOT NULL AND @end_statement_id IS NULL
                SET @sql = @sql + ' WHERE statement_id = @start_statement_id ';

            IF @start_statement_id IS NOT NULL AND @end_statement_id IS NOT NULL
                SET @sql = @sql + ' WHERE statement_id
                                    BETWEEN @start_statement_id AND @end_statement_id';

            EXEC sp_executesql
                 @sql
                ,N'@start_statement_id int, @end_statement_id int'
                ,@start_statement_id
                ,@end_statement_id;

        END TRY
        BEGIN CATCH
            SELECT @ErrorMessage  = ERROR_MESSAGE(),
                   @ErrorSeverity = ERROR_SEVERITY(),
                   @ErrorState    = ERROR_STATE();

            RAISERROR(@ErrorMessage, @ErrorSeverity, @ErrorState);
        END CATCH
    END

    -- *********************************************** --
    -- *                 REPLAY                      * --
    -- *********************************************** --
    IF @action = 'REPLAY'
    BEGIN

        BEGIN TRY

            --load the selected statement(s)
            SET @statement = '
                SET @sql = ''''
                SELECT @sql += statement_text + '' ''
                FROM ##replay_info
            ';

            IF @start_statement_id IS NOT NULL AND @end_statement_id IS NULL
                SET @statement =
                    @statement
                    + ' WHERE statement_id = @start_statement_id ';

            IF @start_statement_id IS NOT NULL AND @end_statement_id IS NOT NULL
                SET @statement =
                    @statement
                    + ' WHERE statement_id
                        BETWEEN @start_statement_id AND @end_statement_id';

            EXEC sp_executesql
                 @statement
                ,N'@start_statement_id int, @end_statement_id int, @sql nvarchar(max) OUTPUT'
                ,@start_statement_id
                ,@end_statement_id
                ,@sql OUTPUT;

            IF NULLIF(LTRIM(@sql),'') IS NULL
                RAISERROR('Unable to locate the statement(s) specified.',16,1)

            SET @srv = @@SERVERNAME; -- gather this server name

            IF EXISTS (SELECT * FROM sys.servers WHERE name = 'TMPLOOPBACK')
                EXEC sp_dropserver 'TMPLOOPBACK';

            -- Create a loopback linked server
            EXEC master.dbo.sp_addlinkedserver
                @server     = N'TMPLOOPBACK',
                @srvproduct = N'SQLServ', -- it’s not a typo: it can’t be “SQLServer”
                @provider   = N'SQLNCLI', -- change to SQLOLEDB for SQLServer 2000
                @datasrc    = @srv;

            -- Set the authentication to "current security context"
            EXEC master.dbo.sp_addlinkedsrvlogin
                @rmtsrvname  = N'TMPLOOPBACK',
                @useself     = N'True',
                @locallogin  = NULL,
                @rmtuser     = NULL,
                @rmtpassword = NULL;

            -- Use a permanent table in Tempdb to store the output
            IF OBJECT_ID('tempdb..___outputTable') IS NOT NULL
                DROP TABLE tempdb..___outputTable;

            -- Execute the statement in Tempdb to discover the column definition
            SET @statement = '
                SELECT TOP(0) *
                INTO tempdb..___outputTable
                FROM OPENQUERY(TMPLOOPBACK,''
                    SET FMTONLY OFF; EXEC tempdb.sys.sp_executesql N''''' + REPLACE(@sql,'''','''''''''') + '''''
                '')
            ';

            EXEC(@statement);

            SET @statement = @sql;

            -- Build the column list of the output table
            SET @column_list = STUFF((
                SELECT ',' + QUOTENAME(C.name)
                FROM tempdb.sys.columns AS C
                INNER JOIN tempdb.sys.tables AS T
                    ON C.object_id = T.object_id
                WHERE T.name = '___outputTable'
                FOR XML PATH('')
            ),1,1,SPACE(0));

            -- Add a "Database Name" column
            ALTER TABLE tempdb..___outputTable ADD Database__Name sysname;

            -- Build a sql statement to execute
            -- the recorded statement against all databases
            SET @sql =
                'N''INSERT tempdb..___outputTable(' + @column_list + ') EXEC(@statement); UPDATE tempdb..___outputTable SET Database__Name = DB_NAME() WHERE Database__Name IS NULL;''';

            -- Build a statement to execute on each database context
            ;WITH dbs AS (
                SELECT *,
                    system_db = CASE WHEN name IN ('master','model','msdb','tempdb') THEN 1 ELSE 0 END
                FROM sys.databases
                WHERE   DATABASEPROPERTY(name, 'IsSingleUser') = 0
                    AND HAS_DBACCESS(name) = 1
                    AND state_desc = 'ONLINE'
            )
            SELECT @sql = (
                SELECT
                    'EXEC ' + QUOTENAME(name) + '.sys.sp_executesql ' +
                        @sql + ',' +
                        'N''@statement nvarchar(max)'',' +
                        '@statement;' + char(10) AS [text()]
                FROM dbs
                ORDER BY name
                FOR XML PATH('')
            );

            -- Execute multi-db sql and pass in the actual statement
            EXEC sp_executeSQL @sql, N'@statement nvarchar(max)', @statement

            --
            SET @sql = '
                SELECT Database__Name AS [Database  Name], ' + @column_list + '
                FROM tempdb..___outputTable
                ORDER BY 1;
            '

            EXEC sp_executesql @sql;

            EXEC tempdb.sys.sp_executesql N'DROP TABLE ___outputTable';

        END TRY
        BEGIN CATCH
            SELECT @ErrorMessage  = ERROR_MESSAGE(),
                   @ErrorSeverity = ERROR_SEVERITY(),
                   @ErrorState    = ERROR_STATE();

            RAISERROR(@ErrorMessage, @ErrorSeverity, @ErrorState);
        END CATCH

    END

END

As you can see, the code creates a stored procedure that accepts a parameter named @action, which is used to determine what the procedure should do. Specialized sections of the procedure handle every possible value for the parameter, with the following logic:

First of all you start recording, then you execute the statements to repeat on each database, then you stop recording. From that moment on, you can enumerate the statements captured and execute them, passing a specific statement id or a range of ids.

The typical use of the procedure could look like this:


-- start recording
EXECUTE replay_statements_on_each_db
    @action = 'RECORD'

-- run the statements you want to replay
SELECT DATABASEPROPERTYEX(DB_NAME(),'Recovery') AS RecoveryModel

-- stop recording
EXECUTE replay_statements_on_each_db
    @action = 'STOPRECORD'

-- display captured statements
EXECUTE replay_statements_on_each_db
    @action = 'SHOWQUERY'

-- execute the first statement
EXECUTE replay_statements_on_each_db
    @action             = 'REPLAY',
    @start_statement_id = 1,
    @end_statement_id   = 1

You can see the results of the script execution here:

Obviuosly this approach is totally overkill for just selecting the database recovery model, but it can become very handy when the statement’s complexity raises.

This seems a perfect fit for Glen Berry’s diagnostic queries, which is where we started from. You can go back to that script and add the record instructions just before the database specific queries start:

At the end of the script you can add the instructions to stop recording and show the queries captured by the procedure.

Once the statements are recorded, you can run any of the statements against all databases. For instance, I decided to run the top active writes index query (query 51).

As expected, the procedure adds the database name column to the result set and then displays the merged results.

You may have noticed that I skipped the first statement in the database-specific section of the script, which is a DBCC command. Unfortunately, not all kind of statement can be captured with this procedure, because some limitations apply. Besides the inability to capture some DBCC commands, please note that the column names must be explicitly set.

I think that a CLR procedure could overcome these limitations, or at least some of them. I hope I will find the time to try the CLR method soon and I promise I will blog the results.

SQL Server and Custom Date Formats


Today SQL Server Central is featuring my article Dealing with custom date formats in T-SQL.

There’s a lot of code on that page and I thought that making it available for download would make it easier to play with.

You can download the code from this page or from the Code Repository.

I was also asked to include a performance chart for the different methods included in the article. Here’s a quick’n’dirty Excel bar chart (I didn’t include the recursive iTVF for the sake of readability).
 

I hope you enjoy reading the article as much as I enjoyed writing it.

How to Eat a SQL Elephant in 10 Bites


One byte at a time, obviously!

No elephants were harmed during photoshopping.

Sometimes, when you have to optimize a poor performing query, you may find yourself staring at a huge statement, wondering where to start.

Some developers think that a single elephant statement is better than multiple small statements, but this is not always the case.

Let’s try to look from the perspective of software quality:

  • Efficiency
    The optimizer will likely come up with a suboptimal plan, giving up early on optimizations and transformations.
  • Reliability
    Any slight change in statistics could lead the optimizer to produce a different and less efficient plan.
  • Maintainability
    A single huge statement is less readable and maintainable than multiple small statements.

With those points in mind, the only sensible thing to do is cut the elephant into smaller pieces and eat them one at a time.

What should I do with this query??

This is how I do it:

  1. Lay out the original code and read the statement carefully
  2. Decide whether a full rewrite is more convenient
  3. Set up a test environment
  4. Identify the query parts
    • Identify the main tables
    • Identify non correlated subqueries and UNIONs
    • Identify correlated subqueries
  5. Write a query outline
  6. Break the statement into parts with CTEs, views, functions and temporary tables
  7. Merge redundant subqueries
  8. Put it all together
  9. Verify the output based on multiple different input values
  10. Comment your work thoroughly
The queries you will find in the pictures are (in very small part) a MySQL stored procedure I had to rewrite recently, so don’t try to run them in SQL Server. The syntax may be different, but the method still stands.

1.     Lay out the original code and read the statement carefully

Use one of the many SQL formatters you can find online. My favorite one is Tao Klerk’s Poor Man’s T-SQL Formatter: it’s very easy to use and configure and it comes with a handy SSMS add-in and plugins for Notepad++ and WinMerge. Moreover, it’s free and open source. A must-have.

Looks much better now.

Once your code is readable, don’t rush to the keyboard: take your time and read it carefully.

  • Do you understand (more or less) what it is supposed to do?
  • Do you think you could have coded it yourself?
  • Do you know all the T-SQL constructs it contains?

If you answered “yes” to all the above, you’re ready to go to the next step.

2.     Decide whether a full rewrite is more convenient

OK, that code sucks and you have to do something. It’s time to make a decision:

  1. Take the business rules behind the statement and rewrite it from scratch
    When the statement is too complicated and unreadable, it might be less time-consuming to throw the old statement away and write your own version.
    Usually it is quite easy when you know exactly what the code is supposed to do. Just make sure you’re not making wrong assumptions and be prepared to compare your query with the original one many times.
  2. Refactor the statement
    When the business rules are unclear (or unknown) starting from scratch is not an option. No, don’t laugh! The business logic may have been buried in the sands of time or simply you may be working on a query without any will to understand the business processes behind it.
    Bring a big knife: you’re going to cut the elephant in pieces.
  3. Leave the statement unchanged
    Sometimes the statement is too big or too complicated to bother taking the time to rewrite it. For instance, this query would take months to rewrite manually.
    It works? Great: leave it alone.

3.     Set up a test environment

It doesn’t matter how you decide to do it: at the end of the day you will have to compare the results of your rewritten query with the results of the “elephant” and make sure you did not introduce errors in your code.

The best way to do this is to prepare a script that compares the results of the original query with the results of your rewritten version. This is the script I am using (you will find it in the code repository, as usual).

-- =============================================
-- Author:      Gianluca Sartori - spaghettidba
-- Create date: 2012-03-14
-- Description: Runs two T-SQL statements and 
--              compares the results
-- =============================================

-- Drop temporary tables
IF OBJECT_ID('tempdb..#original') IS NOT NULL 
    DROP TABLE #original;

IF OBJECT_ID('tempdb..#rewritten') IS NOT NULL 
    DROP TABLE #rewritten;

-- Store the results of the original 
-- query into a temporary table
WITH original AS (
    <original, text, >
)
SELECT *
INTO #original
FROM original;

-- Add a sort column
ALTER TABLE #original ADD [______sortcolumn] int identity(1,1);



-- Store the results of the rewritten 
-- query into a temporary table
WITH rewritten AS (
    <rewritten, text, >
)
SELECT *
INTO #rewritten
FROM rewritten;

-- Add a sort column
ALTER TABLE #rewritten ADD [______sortcolumn] int identity(1,1);


-- Compare the results
SELECT 'original' AS source, *
FROM (
    SELECT * 
    FROM #original 
    
    EXCEPT 
    
    SELECT * 
    FROM #rewritten
) AS A

UNION ALL

SELECT 'rewritten' AS source, *
FROM (
    SELECT * 
    FROM #rewritten 
    
    EXCEPT 
    
    SELECT * 
    FROM #original
) AS B;

The script is a SSMS query template that takes the results of the original and the rewritten query and compares the resultsets, returning all the missing or different rows. The script uses two CTEs to wrap the two queries: this means that the ORDER BY predicate (if any) will have to be moved outside the CTE.

Also, the results of the two queries are piped to temporary tables, which means that you can’t have duplicate column names in the result set.

Another thing worth noting is that the statements to compare cannot be stored procedures. One simple way to overcome this limitation is to use the technique I described in this post.

The queries inside the CTEs should then be rewritten as:

SELECT *
FROM OPENQUERY(LOOPBACK,'<original, text,>')

Obviously, all the quotes must be doubled, which is the reason why I didn’t set up the script this way in the first place. It’s annoying, but it’s the only way I know of to pipe the output of a stored procedure into a temporary table without knowing the resultset definition in advance. If you can do better, suggestions are always welcome.

4.     Identify the query parts

OK, now you have everything ready and you can start eating the elephant. The first thing to do is to identify all the autonomous blocks in the query and give them a name. You can do this at any granularity and repeat the task as many times as you like: the important thing is that at the end of this process you have a list of query parts and a name for each part.

Identify the main parts and give them a name.

Identify the main tables

Usually I like the idea that the data comes from one “main” table and all the rest comes from correlated tables. For instance, if I have to return a resultset containing some columns from the “SalesOrderHeader” table and some columns from the “SalesOrderDetail” table, I consider SalesOrderHeader the main table and SalesOrderHeader a correlated table. It fits well with my mindset, but you are free to see things the way you prefer.

Probably these tables are already identified by an alias: note down the aliases and move on.

Identify non correlated subqueries and UNIONs

Non-correlated subqueries are considered as inline views. Often these subqueries are joined to the main tables to enrich the resultset with additional columns.

Don’t be scared away by huge subqueries: you can always repeat all the steps for any single subquery and rewrite it to be more compact and readable.

Again, just note down the aliases and move to the next step.

Identify correlated subqueries

Correlated subqueries are not different from non-correlated subqueries, with the exception that you will have less freedom to move them from their current position in the query. However, that difference doesn’t matter for the moment: give them a name and note it down.

5.     Write a query outline

Use the names you identified in the previous step and write a query outline. It won’t execute, but it gives you the big picture.

Won't execute, but describes what the query does.

If you really want the big picture, print the query. It may seem crazy, but sometimes I find it useful to be able to see the query as a whole, with all the parts with their names highlighted in different colors.

A touch of colour for my office.

Yes, that’s a single SELECT statement, printed in Courier new 8 pt. on 9 letter sheets, hanging on the wall in my office.

6.     Break the statement in parts with CTEs, views, functions and temporary tables

SQL Server offers a fair amount of tools that allow breaking a single statement into parts:

  • Common Table Expressions
  • Subqueries
  • Views
  • Inline Table Valued Functions
  • Multi-Statement Table Valued Functions
  • Stored procedures
  • Temporary Tables
  • Table Variables

Ideally, you will choose the one that performs best in your scenario, but you could also take usability and modularity into account.

CTEs and subqueries are a good choice when the statement they contain is not used elsewhere and there is no need to reuse that code.

Table Valued functions and views, on the contrary, are most suitable when there is an actual need to incapsulate the code in modules to be reused in multiple places.

Generally speaking, you will use temporary tables or table variables when the subquery gets used more than once in the statement, thus reducing the load.

A place for everything and everything in its place.

Though I would really like to go into deeper details on the performance pros and cons of each construct, that would take an insane amount of time and space. You can find a number of articles and blogs on those topics and I will refrain from echoing them here.

7.     Merge redundant subqueries

Some parts of your query may be redundant and you may have the opportunity to merge those parts. The merged query will be more compact and will likely perform significantly better.

For instance, you could have multiple subqueries that perform aggregate calculations on the same row set:

SELECT ProductID
    ,Name
    ,AverageSellOutPrice = (
        SELECT AVG(UnitPrice)
        FROM Sales.SalesOrderDetail
        WHERE ProductID = PR.ProductID
    )
    ,MinimumSellOutPrice = (
        SELECT MIN(UnitPrice)
        FROM Sales.SalesOrderDetail
        WHERE ProductID = PR.ProductID
    )
    ,MaximumSellOutPrice = (
        SELECT MAX(UnitPrice)
        FROM Sales.SalesOrderDetail
        WHERE ProductID = PR.ProductID
    )
FROM Production.Product AS PR;

The above query can be rewritten easily to avoid hitting the SalesOrderDetail table multiple times:

SELECT ProductID
    ,Name
    ,AverageSellOutPrice
    ,MinimumSellOutPrice
    ,MaximumSellOutPrice
FROM Production.Product AS PR
CROSS APPLY (
    SELECT AVG(UnitPrice), MIN(UnitPrice), MAX(UnitPrice)
    FROM Sales.SalesOrderDetail
    WHERE ProductID = PR.ProductID
) AS SellOuPrices (AverageSellOutPrice, MinimumSellOutPrice, MaximumSellOutPrice);

Another typical situation where you can merge some parts is when multiple subqueries perform counts on slightly different row sets:

SELECT ProductID
    ,Name
    ,OnlineOrders = (
        SELECT COUNT(*)
        FROM Sales.SalesOrderHeader AS SOH
        WHERE SOH.OnlineOrderFlag = 1
            AND EXISTS (
                SELECT *
                FROM Sales.SalesOrderDetail
                WHERE SalesOrderID = SOH.SalesOrderID
                    AND ProductID = PR.ProductID
            )
    )
    ,OfflineOrders = (
        SELECT COUNT(*)
        FROM Sales.SalesOrderHeader AS SOH
        WHERE SOH.OnlineOrderFlag = 0
            AND EXISTS (
                SELECT *
                FROM Sales.SalesOrderDetail
                WHERE SalesOrderID = SOH.SalesOrderID
                    AND ProductID = PR.ProductID
            )
    )
FROM Production.Product AS PR;

The only difference between the two subqueries is the predicate on SOH.OnlineOrderFlag. The two queries can be merged introducing a CASE expression in the aggregate:

SELECT ProductID
    ,Name
    ,ISNULL(OnlineOrders,0) AS OnlineOrders
    ,ISNULL(OfflineOrders,0) AS OfflineOrders
FROM Production.Product AS PR
CROSS APPLY (
    SELECT SUM(CASE WHEN SOH.OnlineOrderFlag = 1 THEN 1 ELSE 0 END),
           SUM(CASE WHEN SOH.OnlineOrderFlag = 0 THEN 1 ELSE 0 END)
    FROM Sales.SalesOrderHeader AS SOH
    WHERE EXISTS (
            SELECT *
            FROM Sales.SalesOrderDetail
            WHERE SalesOrderID = SOH.SalesOrderID
                AND ProductID = PR.ProductID
        )
) AS Orderscount (OnlineOrders, OfflineOrders);

There are infinite possibilities and enumerating them all would be far beyond the scope of this post. This is one of the topics that my students often find hard to understand and I realize that it really takes some experience to identify merge opportunities and implement them.

Hi query, you look very fit. Did you lose weight?

8.     Put it all together

Remember the query outline you wrote previously? It’s time to put it into action.

Some of the identifiers may have gone away in the merge process, some others are still there and have been transformed into different SQL constructs, such as CTEs, iTVFs or temporary tables.

9.     Verify the output based on multiple different input values

Now it’s time to see if your new query works exactly like the original one. You already have a script for that: you can go on and use it.

Remember that the test can be considered meaningful only if you repeat it a reasonably large number of times, with different parameters. Some queries could appear to be identical, but still be semantically different. Make sure the rewritten version handles NULLs and out-of-range parameters in the same way.

10.Comment your work thoroughly

If you don’t comment your work, somebody will find it even more difficult to maintain than the elephant you found when you started.

Comments are for free and don’t affect the query performance in any way. Don’t add comments that mimic what the query does, instead, write a meaningful description of the output of the query.

For instance, given a code fragment like this:

SELECT SalesOrderID, OrderDate, ProductID
INTO #orders
FROM Sales.SalesOrderHeader AS H
INNER JOIN Sales.SalesOrderDetail AS D
    ON H.SalesOrderID = D.SalesOrderID
WHERE OrderDate BETWEEN @StartDate AND @EndDate

a comment like “joins OrderHeader to OrderDetail” adds nothing to the clarity of the code. A comment like “Selects the orders placed between the @StartDate and @EndDate and saves the results in a temporary table for later use” would be a much better choice.

Elephant eaten. (Burp!)

If you don't see a hat, sorry: you're getting old.

After all, it was not too big, was it?

Discovering resultset definition of DBCC commands


Lots of blog posts and discussion threads suggest piping the output of DBCC commands to a table for further processing. That’s a great idea, but, unfortunately, an irritatingly high number of those posts contains an inaccurate table definition for the command output.

The reason behind this widespread inaccuracy is twofold.

On one hand the output of many DBCC commands changed over time and versions of SQL Server, and a table that was the perfect fit for the command in SQL Server 2000 is not  perfect any more. In this case, the blog/article/thread is simply old, but many people will keep referring to that source assuming that things did not change.

On the other hand, the output is not always documented in BOL, and people often have to guess the table definition based on the data returned by the command. I’ve been guilty of this myself and I’ve been corrected many times, until I decided that I needed a better way to discover the output definition.

You are a database professional and you don’t like to guess, because guessing is never as good as knowing it for sure.

In order to stop guessing, you will have to create a linked server named “loopback” that points back to the same instance where you are running the DBCC command.

I am sure you are asking yourself why you need such a strange thing as a loopback linked server. The idea behind is that you need a way to query the command as if it was a table or a view, so that it can be used as a valid source for a SELECT…INTO statement. The perfect tool for this kind of task is the OPENQUERY command, which allows sending pass-through queries, that don’t necessarily need to be SELECT statements. OPENQUERY requires a linked server, which can be any OLEDB data source, including a remote server or the same SQL Server instance where the linked server lies.

OK, let’s create it:

DECLARE @srv nvarchar(4000);
SET @srv = @@SERVERNAME; -- gather this server name

-- Create the linked server
EXEC master.dbo.sp_addlinkedserver
@server     = N'LOOPBACK',
@srvproduct = N'SQLServ', -- it’s not a typo: it can’t be “SQLServer”
@provider   = N'SQLNCLI', -- change to SQLOLEDB for SQLServer 2000
@datasrc    = @srv;


-- Set the authentication to "current security context"
EXEC master.dbo.sp_addlinkedsrvlogin
@rmtsrvname  = N'LOOPBACK',
@useself     = N'True',
@locallogin  = NULL,
@rmtuser     = NULL,
@rmtpassword = NULL;

In order to capture the output of DBCC commands, you have to wrap them inside a stored procedure, otherwise SQL Server could complain about missing column information. I don’t know the exact technical reason behind this error (I suppose it has to do with the way metadata is propagated), but this limitation can be overcome wrapping the command into a stored procedure and using “SET FMTONLY OFF” in the pass-through query.

This is also a nice way to overcome the single INSERT…EXEC limit (and implement many more interesting tricks that I hope to cover in future posts).

For instance, to capture the table definition of DBCC LOGINFO(), you will have to create a stored procedure similar to this:

USE tempdb;
GO

CREATE PROCEDURE loginfo
AS
BEGIN
    SET NOCOUNT ON;

    DBCC LOGINFO();

END
GO

With the stored procedure and the linked server in place, you can set up the call using OPENQUERY:

SELECT *
INTO tempdb.dbo.loginfo_output
FROM OPENQUERY(LOOPBACK, 'SET FMTONLY OFF; EXEC tempdb.dbo.loginfo');

DROP PROCEDURE loginfo;
GO

Running this script will create a table named “loginfo_output” in the tempdb database: you can find it in your object explorer and script it out to a new query editor window.

Repeating these steps on instances running different versions on SQL Server reveals that the table definition changed in SQL2005 and then remained the same in 2008 and 2008R2.

-- SQL Server 2000
CREATE TABLE [dbo].[loginfo_output](
    [FileId]      [int] NULL,
    [FileSize]    [numeric](20, 0) NULL,
    [StartOffset] [numeric](20, 0) NULL,
    [FSeqNo]      [int] NULL,
    [Status]      [int] NULL,
    [Parity]      [tinyint] NULL,
    [CreateLSN]   [numeric](25, 0) NULL
)


-- SQL Server 2005, 2008 and 2008R2
CREATE TABLE [dbo].[loginfo_output](
    [FileId]      [int] NULL,
    [FileSize]    [bigint] NULL,
    [StartOffset] [bigint] NULL,
    [FSeqNo]      [int] NULL,
    [Status]      [int] NULL,
    [Parity]      [tinyint] NULL,
    [CreateLSN]   [numeric](25, 0) NULL
)

Now that you know how the output looks like, you can happily pipe the results of DBCC LOGINFO to an appropriate table:

-- Declare variable for dynamic sql
DECLARE @sql nvarchar(max)

-- Drop the table if already exists
IF OBJECT_ID('tempdb..loginfo_output') IS NOT NULL
    DROP TABLE tempdb..loginfo_output

-- Check SQL Server version
IF CAST(REPLACE(LEFT(CAST(SERVERPROPERTY('ProductVersion') AS nvarchar(128)),2),'.','') AS int) > 8
BEGIN
    -- SQL Server 2005+
    SET @sql = '
        CREATE TABLE tempdb..loginfo_output(
            [FileId]      [int] NULL,
            [FileSize]    [bigint] NULL,
            [StartOffset] [bigint] NULL,
            [FSeqNo]      [int] NULL,
            [Status]      [int] NULL,
            [Parity]      [tinyint] NULL,
            [CreateLSN]   [numeric](25, 0) NULL
        )
        '
END
ELSE
BEGIN
    -- SQL Server 2000
    SET @sql = '
        CREATE TABLE tempdb..loginfo_output(
            [FileId]      [int] NULL,
            [FileSize]    [numeric](20, 0) NULL,
            [StartOffset] [numeric](20, 0) NULL,
            [FSeqNo]      [int] NULL,
            [Status]      [int] NULL,
            [Parity]      [tinyint] NULL,
            [CreateLSN]   [numeric](25, 0) NULL
        )
        '
END

-- Create the output table
EXEC(@sql)

-- Execute DBCC command and
-- pipe results to the output table
INSERT tempdb..loginfo_output
EXEC('DBCC LOGINFO()')


-- Display results
SELECT *
FROM tempdb..loginfo_output

You could ask with good reason why you should use an output table when you could query the wrapper stored procedure directly with OPENQUERY. Based on observation, the trick does not always work and SQL Server can randomly complain about missing column information.

Msg 7357, Level 16, State 2, Line 2
Cannot process the object "loginfo". The OLE DB provider "SQLNCLI10" for linked server "LOOPBACK" indicates that either the object has no columns or the current user does not have permissions on that object.

Again, I don’t have an in-depth technical answer: I can only report what I observed. It’s not a big deal indeed, because the output definition changes very slowly (typically between SQL Server versions) and you probably would review your code anyway when upgrading to a newer version. I guess you can live with a hardcoded table definition when the price to pay for having it dynamic is a random failure.

This post showed you how to capture the output of DBCC LOGINFO, but the same technique can be used for all DBCC commands that allow specifying WITH TABLERESULTS, extended stored procedures, remote stored procedures and all those programmable objects than cannot be inspected easily.

Now that you have the right tool in your hands, do yourself a favour: stop guessing!

Concatenating multiple columns across rows


Today I ran into an interesting question on the forums at SQLServerCentral and I decided to share the solution I provided, because it was fun to code and, hopefully, useful for some of you.

Many experienced T-SQL coders make use of FOR XML PATH(‘’) to build concatenated strings from multiple rows. It’s a nice technique and pretty simple to use.
For instance, if you want to create a list of databases in a single concatenated string, you can run this statement:

SELECT CAST((
    SELECT name + ',' AS [text()]
    FROM sys.databases
    ORDER BY name
    FOR XML PATH('')
) AS varchar(max))

The SELECT statement produces this result:

allDBs
------------------------------------------------------------------
BROKEN,LightHouse,master,model,msdb,tempdb,TEST,test80,TOOLS,WORK,

Great! But, what if you had to concatenate multiple columns at the same time? It’s an unusual requirement, but not an impossible one.
Let’s consider this example:


-- =================================
-- Create a sentences table
-- =================================
DECLARE @Sentences TABLE (
    sentence_id int PRIMARY KEY CLUSTERED,
    sentence_description varchar(50)
)

-- =================================
-- Sentences are broken into rows
-- =================================
DECLARE @Rows TABLE (
    sentence_id int,
    row_id      int,
    Latin       varchar(500),
    English     varchar(500),
    Italian     varchar(500)
)

-- =================================
-- Create three sentences
-- =================================
INSERT INTO @Sentences VALUES(1,'First sentence.')
INSERT INTO @Sentences VALUES(2,'Second Sentence')
INSERT INTO @Sentences VALUES(3,'Third sentence')

-- =================================
-- Create sentences rows from 
-- "De Finibus bonorum et malorum" 
-- by Cicero, AKA "Lorem Ipsum"
-- =================================
INSERT INTO @Rows VALUES(1, 1, 
    'Neque porro quisquam est,',
    'Nor again is there anyone who',
    'Viceversa non vi è nessuno che ama,')
INSERT INTO @Rows VALUES(1, 2, 
    'qui dolorem ipsum quia dolor sit amet,',
    'loves or pursues or desires to obtain pain',
    'insegue, vuol raggiungere il dolore in sé')
INSERT INTO @Rows VALUES(1, 3, 
    'consectetur, adipisci velit, sed quia non numquam',
    'of itself, because it is pain, but because occasionally',
    'perché è dolore ma perché talvolta')
INSERT INTO @Rows VALUES(1, 3, 
    'eius modi tempora incidunt',
    'circumstances occur in which',
    'capitano circostanze tali per cui')
INSERT INTO @Rows VALUES(1, 3, 
    'ut labore et dolore magnam aliquam quaerat voluptatem.',
    'toil and pain can procure him some great pleasure.',
    'con il travaglio e il dolore si cerca qualche grande piacere.') 
INSERT INTO @Rows VALUES(2, 1, 
    'Ut enim ad minima veniam,',
    'To take a trivial example,',
    'Per venire a casi di minima importanza,')
INSERT INTO @Rows VALUES(2, 2, 
    'quis nostrum exercitationem ullam corporis suscipit laboriosam,',
    'which of us ever undertakes laborious physical exercise,',
    'chi di noi intraprende un esercizio fisico faticoso')
INSERT INTO @Rows VALUES(2, 3, 
    'nisi ut aliquid ex ea commodi consequatur?',
    'except to obtain some advantage from it?',
    'se non per ottenere da esso qualche vantaggio?') 
INSERT INTO @Rows VALUES(3, 1, 
    'Quis autem vel eum iure reprehenderit qui in ea voluptate',
    'But who has any right to find fault with a man who chooses to enjoy a pleasure',
    'O chi può biasimare colui che decide di provare un piacere')
INSERT INTO @Rows VALUES(3, 2, 
    'velit esse quam nihil molestiae consequatur,',
    'that has no annoying consequences,',
    'che non porta conseguenze negative,')
INSERT INTO @Rows VALUES(3, 3, 
    'vel illum qui dolorem eum fugiat quo voluptas nulla pariatur?',
    'or one who avoids a pain that produces no resultant pleasure?',
    'o che fugge quel dolore che non produce nessun piacere?')

The setup code creates two tables: Sentences and Rows. The first one is the master table, that contains the sentence_id and a description. The second one contains the actual sentences, broken into rows and organized with languages in columns.

For the purposes of this test, I inserted in the Rows table an excerpt of Cicero’s “De Finibus bonorum et malorum”, also known as “Lorem Ipsum”, the printing and typesetting industry’s standard dummy text since the 1500s.

Here’s how the input data looks like:

What we want to do is concatenate all the rows for each sentence, keeping the languages separated. It could be accomplished very easily concatenating each column separately in a subquery, but what if the input data comes from a rather expensive query? You don’t want to run the statement for each language, do you?

Let’s see how this can be done in a single scan:

SELECT sentence_id, sentence_description, Latin, English, Italian
FROM (
    SELECT Sentences.sentence_id, sentence_description, language_name, string 
    FROM   @Sentences AS Sentences
    OUTER APPLY (
        SELECT *
        FROM (
			-- =================================
			-- Create a Languages inline query
			-- =================================
                      SELECT 'Latin'
            UNION ALL SELECT 'English'
            UNION ALL SELECT 'Italian'
        ) Languages (language_name)
        CROSS APPLY (
			-- =================================
			-- Concatenate all the rows for 
			-- the current sentence and language
			-- from an UNPIVOTed version of the
			-- original rows table
			-- =================================
            SELECT sentence_id, string = (
                SELECT string + ' ' AS [data()] 
                FROM @Rows AS src
                UNPIVOT ( string FOR language_name IN (Latin, English, Italian) ) AS u
                WHERE sentence_id = Sentences.sentence_id
                    AND language_name = Languages.language_name
                ORDER BY row_id
                FOR XML PATH('')
            )
        ) AS ca
    ) AS oa
) AS src
-- =================================
-- Re-transform rows to columns
-- =================================
PIVOT ( MIN(string) FOR language_name IN ([Latin],[English],[Italian])) AS p

If you don’t like PIVOT and UNPIVOT, you can always use CASE expressions to create a crosstab.
Here’s the final result:

With a little of PIVOT, UNPIVOT and FOR XML you can achieve really surprising results, you just need to unleash your creativity.