I’ve written about statistics in SQL Server a few times now. Through conversations I am reminded that not everyone keeps their table statistics up to date. Keeping your statistics up to date is one of the more critical components of SQL Server performance issues. Please be sure you are doing more than just index maintenance to maintain your statistics. Index maintenance only maintains statistics created by indexes and single field predicate created table statistics. There are also column statistics that need to be maintained that are created by predicates usage in your queries or even manually created. For each insert, update, or delete the distribution of your data changes and…
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Statistics are the magic ingredient that helps the query optimizer create its best guess for generating an execution plan. Keeping statistics as accurate as possible will give the optimizer the information it uses to calculate estimated costs and cardinality, which enables it to properly allocate resources such as memory grants. In this blog I am not going to go into what statistics are and how they are used. There are many great resources out there to read, I am however going to tell you about a trace flag that can help you with keeping your large table statistics up to date. I will also explain why your statistics may not…
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Following up on my last post about the Cardinality Estimator let’s talk about column statistics and how they work and play a part in execution plans. The cardinality estimator relies heavily on statistics to get the answer to selectivity (the ratio of distinct values to the total number of values) questions and calculate a cost estimate. This hopefully gives us the best possible execution plans for queries. In this post, I will show you where to find information about what your statistics contain and information regarding each of those fields. Then we will look at the impact of over and under estimations caused by stale or missing statistics (or even data…
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One of the things I’ve been able to implement to help with performance is changing from Update Statistics Synchronous to Auto Update Statistics Asynchronously. It’s a simple change that can have a big impact when implemented in highly transactional OLTP environments. Notice I said OLTP not OLAP, since data in an OLAP environment tends to not be as dynamic, so it’s rare to enable this in a data warehouse. So, what’s the difference between the two and why does it help? Synchronous (defaulted as AUTO_UPDATE_STATISTICS =TRUE) By default, when Auto Update Statistics is set to True, the SQL Server Query Optimizer will automatically update statistics when data has met a threshold…
