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)

Dataset merging

The rxMerge() function merges two datasets into one. The datasets must be a dataframe (or XDF format) and operate similarly to the JOIN clause in T-SQL (the rxMerge() function should not be confused with T-SQL's MERGE statement). Two datasets are merged based on one or more variables using the matchVars argument. In addition, when using the local compute context (which we are using in the next sample), the sorting of the data needs to be defined as well, since data.frames-as a collection of vectors-in R are not presorted or do not hold any sorts whatsoever. So, if no presorting is done, the autoSort argument must be set to true (autosort = TRUE):

EXEC sp_execute_external_script
      @language = N'R'
      ,@script = N'
      df_sql <- InputDataSet
      someExtraData <- data.frame(BusinessEntityID = 1:1200, department...