Book Image

SQL Server 2017 Machine Learning Services with R.

By : Julie Koesmarno, Tomaž Kaštrun
Book Image

SQL Server 2017 Machine Learning Services with R.

By: Julie Koesmarno, Tomaž Kaštrun

Overview of this book

R Services was one of the most anticipated features in SQL Server 2016, improved significantly and rebranded as SQL Server 2017 Machine Learning Services. Prior to SQL Server 2016, many developers and data scientists were already using R to connect to SQL Server in siloed environments that left a lot to be desired, in order to do additional data analysis, superseding SSAS Data Mining or additional CLR programming functions. With R integrated within SQL Server 2017, these developers and data scientists can now benefit from its integrated, effective, efficient, and more streamlined analytics environment. This book gives you foundational knowledge and insights to help you understand SQL Server 2017 Machine Learning Services with R. First and foremost, the book provides practical examples on how to implement, use, and understand SQL Server and R integration in corporate environments, and also provides explanations and underlying motivations. It covers installing Machine Learning Services;maintaining, deploying, and managing code;and monitoring your services. Delving more deeply into predictive modeling and the RevoScaleR package, this book also provides insights into operationalizing code and exploring and visualizing data. To complete the journey, this book covers the new features in SQL Server 2017 and how they are compatible with R, amplifying their combined power.
Table of Contents (12 chapters)

Creating a baseline and workloads, and replaying

Given the ability to reduce and create new measures that are tailored and adapted to your particular server or environment, now we want to understand how the system is behaving with all the other parameters unchanged (in Latin, ceteris paribus). This is the baseline. And with the baseline, we establish what is normal, or in other words, what the performance is under normal conditions. A baseline is used for comparing what might be or seem abnormal or out of the ordinary. It can also serve as a control group for any future tests (this works well especially when new patches are rolled out an upgrade of a particular environment/server needs to be performed).

A typical corporate baseline would be described as follows over a period of one day (24 hours) in the form of the number of database requests from users or machines:

When all...