Episode 17
| November 11, 2015
| 26 minutes
SQL Server Partitioning
Do you find you have tables and indexes that have grown really large? Are you moving around a lot more data than you used to? Are your windows for jobs and maintenance getting tighter? If you answered yes to any of these questions, partitioning may be for you!
Partitioning allows us to break a table or index down into smaller more manageable chunks. Partitioning can enable us to perform maintenance on just part of a table or index. We can even move data in and out of tables with quick and easy metadata only operations.
In this episode, we’ll go over basic partitioning concepts such as horizontal vs. vertical partitioning, how to identify if a table is ready for partitioning, and what you need to know about your applications before you implement partitioning.
Brandon on Twitter
Brandon’s Partitioning Presentation (Coming Soon)
SQL Sentry’s Performance Advisor
Meet the Hosts
Carlos Chacon
With more than 10 years of working with SQL Server, Carlos helps businesses ensure their SQL Server environments meet their users’ expectations. He can provide insights on performance, migrations, and disaster recovery. He is also active in the SQL Server community and regularly speaks at user group meetings and conferences. He helps support the free database monitoring tool found at databasehealth.com and provides training through SQL Trail events.
Eugene Meidinger
Eugene works as an independent BI consultant and Pluralsight author, specializing in Power BI and the Azure Data Platform. He has been working with data for over 8 years and speaks regularly at user groups and conferences. He also helps run the GroupBy online conference.
Kevin Feasel
Kevin is a Microsoft Data Platform MVP and proprietor of Catallaxy Services, LLC, where he specializes in T-SQL development, machine learning, and pulling rabbits out of hats on demand. He is the lead contributor to Curated SQL, president of the Triangle Area SQL Server Users Group, and author of the books PolyBase Revealed (Apress, 2020) and Finding Ghosts in Your Data: Anomaly Detection Techniques with Examples in Python (Apress, 2022). A resident of Durham, North Carolina, he can be found cycling the trails along the triangle whenever the weather's nice enough.
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