Skip to content

shannonlowder.com

Menu
  • About
  • Biml Interrogator Demo
  • Latest Posts
Menu

SET TRANSACTION ISOLATION LEVEL

Posted on March 23, 2009February 9, 2011 by slowder

Like I’ve mentioned before, unless you use SET TRANSACTION ISOLATION LEVEL, the server will default to READ COMMITTED.  What this means is by default, your queries will only be able to interact with records that have been committed.  If another query is affecting those records, you’re not able to see them in any way.  I am willfully ignoring the NOLOCK and READUNCOMMITTED hints right now.  If you want to change the default behavior, and interact with these records, then you can use the query hints, or you can change the isolation level for your batch.

Since I’ve already covered the hints method before… I’m going to show you how to change the isolation level for your batches.

SET TRANSACTION ISOLATION LEVEL 
 { READ COMMITTED 
 | READ UNCOMMITTED 
 | REPEATABLE READ 
 | SERIALIZABLE 
 }

You can choose any of these options.  Let me explain what each one means.

  • READ COMMITTED — This is the default case for SQL Server.  You can only read records that have been committed, and are not currently being affected by other connections (queries).
  • READ UNCOMMITTED — this allows you to make “dirty” reads.  You can see data that is uncommitted, or is in the middle of change.  If you read this data and make a decision based on that data, you have to know that the data could change at any time, and if you run your query again, you’re not going to see the same thing (most likely).  This option has the same effect as setting NOLOCK on all tables in all SELECT statements in a transaction. This is the least restrictive of the four isolation levels.
  • REPEATABLE READ — Locks are put on any data used in the query.   This will prevent other uses from updating the data while you’re using it.  But, please keep in mind new rows could be added into the data set by another user.  As long as their transactions are committe, these rows will show up later in your transaction, since that read would be repeatable… Yes, I realize I’m using the phrase to define itself, but it helps me remember it… Be careful using this option…It can be useful, but you can also get yourself into trouble!
  • SERIALIZABLE — I’ll be honest, I rarely find a use for this option where READ COMMITTED wouldn’t accomplish the same goal.  This option places a range lock on the data set, preventing other users from updating or inserting rows into the data set until the transaction is complete. This is the most restrictive of the four isolation levels. Because concurrency is lower, use this option only when necessary. This option has the same effect as setting HOLDLOCK on all tables in all SELECT statements in a transaction.

Please note you can only use one of these options at a time.  If you need to change back and forth, I recommend using query hints.  They’re a better option for the fast switch.

At this point you’re definitely getting into the fine-tuning aspects of SQL Server.  This is where you need to proceed with caution.  Definitely have a second set of eyes check your code before going into production.  Otherwise you could really foul up your datasets!  If you have any questions, send them in.  I’m always here to help!

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

Recent Posts

  • A New File Interrogator
  • Using Generative AI in Data Engineering
  • Getting started with Microsoft Fabric
  • Docker-based Spark
  • Network Infrastructure Updates

Recent Comments

  1. slowder on Data Engineering for Databricks
  2. Alex Ott on Data Engineering for Databricks

Archives

  • July 2023
  • June 2023
  • March 2023
  • February 2023
  • January 2023
  • December 2022
  • November 2022
  • October 2022
  • October 2018
  • August 2018
  • May 2018
  • February 2018
  • January 2018
  • November 2017
  • October 2017
  • September 2017
  • August 2017
  • June 2017
  • March 2017
  • February 2014
  • January 2014
  • December 2013
  • November 2013
  • October 2013
  • August 2013
  • July 2013
  • June 2013
  • February 2013
  • January 2013
  • August 2012
  • June 2012
  • May 2012
  • April 2012
  • March 2012
  • February 2012
  • January 2012
  • December 2011
  • November 2011
  • October 2011
  • September 2011
  • August 2011
  • July 2011
  • June 2011
  • May 2011
  • April 2011
  • March 2011
  • February 2011
  • January 2011
  • December 2010
  • November 2010
  • October 2010
  • September 2010
  • August 2010
  • July 2010
  • June 2010
  • May 2010
  • April 2010
  • March 2010
  • January 2010
  • December 2009
  • November 2009
  • October 2009
  • September 2009
  • August 2009
  • July 2009
  • June 2009
  • May 2009
  • April 2009
  • March 2009
  • February 2009
  • January 2009
  • December 2008
  • November 2008
  • October 2008
  • September 2008
  • August 2008
  • July 2008
  • June 2008
  • May 2008
  • April 2008
  • March 2008
  • February 2008
  • January 2008
  • November 2007
  • October 2007
  • September 2007
  • August 2007
  • July 2007
  • June 2007
  • May 2007
  • April 2007
  • March 2007
  • February 2007
  • January 2007
  • December 2006
  • November 2006
  • October 2006
  • September 2006
  • August 2006
  • July 2006
  • June 2006
  • May 2006
  • April 2006
  • March 2006
  • February 2006
  • January 2006
  • December 2005
  • November 2005
  • October 2005
  • September 2005
  • August 2005
  • July 2005
  • June 2005
  • May 2005
  • April 2005
  • March 2005
  • February 2005
  • January 2005
  • November 2004
  • September 2004
  • August 2004
  • July 2004
  • April 2004
  • March 2004
  • June 2002

Categories

  • Career Development
  • Data Engineering
  • Data Science
  • Infrastructure
  • Microsoft SQL
  • Modern Data Estate
  • Personal
  • Random Technology
  • uncategorized
© 2025 shannonlowder.com | Powered by Minimalist Blog WordPress Theme