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  • Fake statistics, and how to get rid of them

    There are two ways to test how your queries behave on huge amounts of data. The simple option is to actually use them on huge amounts of data – but where do you get that if you have no access to the production database, and how do you store it if you happen not to have a multi-terabyte storage array sitting in your basement? So here’s the second ...
  • Skewed Data - Poor Cardinality Estimates... and Plans Gone Bad

    The session Skewed Data, Poor Cardinality Estimates, and Plans Gone Bad by Kimberly Tripp (@KimberlyLTripp) has been published on channel SQLPASS TV.  Abstract When data distribution is heavily skewed, cardinality estimation (how many rows the query optimizer expects each operator to process) can be wildly incorrect, resulting in ...
    Posted to Sergio Govoni (Weblog) by Sergio Govoni on February 14, 2014
  • Fraud Detection with the SQL Server Suite Part 5

    This is the fifth, the final part of the fraud detection whitepaper. You can find the first part, the second part, the third part, and the fourth part in my previous blog posts about this topic. The Results In my original fraud detection whitepaper I wrote for SolidQ, I was advised by my friends to include some concrete and simple numbers to ...
    Posted to Dejan Sarka (Weblog) by Dejan Sarka on January 6, 2014
  • Fraud Detection with the SQL Server Suite Part 4

    This is the fourth part of the fraud detection whitepaper. You can find the first part, the second part, and the third part in my previous blog posts about this topic. Data Mining Models We create multiple mining models by using different algorithms, different input data sets, and different algorithm parameters. Then we evaluate the models in ...
    Posted to Dejan Sarka (Weblog) by Dejan Sarka on December 10, 2013
  • Fraud Detection with the SQL Server Suite Part 3

    This is the third part of the fraud detection whitepaper. You can find the first part and the second part in my previous blog posts about this topic. Data Preparation The problem of credit card fraud detection is not trivial. With every transaction processed, only a limited amount of data is available, making it difficult if not impossible to ...
    Posted to Dejan Sarka (Weblog) by Dejan Sarka on November 27, 2013
  • October Update to Rules-Driven Maintenance

    Happy Fall! It’s a beautiful October here in Minneapolis / Saint Paul. In preparation for my home town SQL Saturday this weekend, as well as the PASS Summit, I offer an update to the Rules-Driven Maintenance code I originally published back in August 2012. It’s hard to believe this thing is now more than two years old – it’s been an incredible ...
    Posted to Merrill Aldrich (Weblog) by merrillaldrich on October 9, 2013
  • Stats on Stats

    I have been working on new features for the Rules-Driven Maintenance Solution, including per-index maintenance preferences and more selective processing for statistics. SQL Server stats is a topic I knew about at a high level, but lately I have had to take a deeper dive into the DMVs and system views and wrap my head around things like ...
    Posted to Merrill Aldrich (Weblog) by merrillaldrich on September 18, 2013
  • Geek City: How old are my statistics?

    This post is basically to answer a question asked in class this week: How can we get the last statistics update date for ALL user tables in a database? After working on the query for a while, I realized that the new metadata function I posted about here can give you that info easily: SELECT object_name(sp.object_id) as object_name,name as ...
    Posted to Kalen Delaney (Weblog) by Kalen Delaney on August 31, 2013
  • Did You Know? What settings to always change

      A week ago, I taught my SQL Server 2012 Internals class to a great group of very interactive students. Even though a dozen of them were taking the class remotely, there were still lots of really great questions and and lots of discussion. One of the students asked if I could summarize all the settings that I recommended changing from the ...
    Posted to Kalen Delaney (Weblog) by Kalen Delaney on June 25, 2013
  • Geek City: More statistics info available!

      I just started using a new DMV (one that’s actually an ‘F’ not a ‘V’, as in Function) that gives us more info about distribution statistics. It returns info about the last statistics update date (which is also available with a function STATS_DATE()). It also provides the number of rows sampled when the statistics were last updated. This is ...
    Posted to Kalen Delaney (Weblog) by Kalen Delaney on April 9, 2013
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