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SQL Server 2017 Machine Learning Services with R

You're reading from   SQL Server 2017 Machine Learning Services with R Data exploration, modeling, and advanced analytics

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Product type Paperback
Published in Feb 2018
Publisher Packt
ISBN-13 9781787283572
Length 338 pages
Edition 1st Edition
Languages
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Authors (2):
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Julie Koesmarno Julie Koesmarno
Author Profile Icon Julie Koesmarno
Julie Koesmarno
Toma≈æ Ka≈°trun Kaštrun Toma≈æ Ka≈°trun Kaštrun
Author Profile Icon Toma≈æ Ka≈°trun Kaštrun
Toma≈æ Ka≈°trun Kaštrun
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Table of Contents (12) Chapters Close

Preface 1. Introduction to R and SQL Server FREE CHAPTER 2. Overview of Microsoft Machine Learning Server and SQL Server 3. Managing Machine Learning Services for SQL Server 2017 and R 4. Data Exploration and Data Visualization 5. RevoScaleR Package 6. Predictive Modeling 7. Operationalizing R Code 8. Deploying, Managing, and Monitoring Database Solutions containing R Code 9. Machine Learning Services with R for DBAs 10. R and SQL Server 2016/2017 Features Extended 11. Other Books You May Enjoy

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'
      library(RevoScaleR)
      df_sql <- InputDataSet
      someExtraData <- data.frame(BusinessEntityID = 1:1200, department...
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