Microsoft has added the capability in SQL Server 2016 to run R and in SQL Server 2017 to run Python. How do these components interact with the rest of SQL Server? What can be done to ensure when running these solutions that the server will not run out of memory? What tools are available to monitor memory use? What security is necessary? This session will answer all of those questions by providing the attendees information they need to know to better understand what processes are running in SQL Server and, more important, the configuration and monitoring tools needed to ensure that both code running in R and Python and standard SQL Server processes such as TSQL can optimally run in the same environment.
You will learn:
- A framework for monitoring the performance and resource use of SQL Server while running R and Python code
- How to implement best-practice monitoring techniques to ensure that SQL Server is optimally configured for running R and Python code
- About the components that make up SQL Server Machine Learning solutions and understand how they interact with the core product