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Hands-On Data Science with R

You're reading from  Hands-On Data Science with R

Product type Book
Published in Nov 2018
Publisher Packt
ISBN-13 9781789139402
Pages 420 pages
Edition 1st Edition
Languages
Authors (4):
Vitor Bianchi Lanzetta Vitor Bianchi Lanzetta
Profile icon Vitor Bianchi Lanzetta
Doug Ortiz Doug Ortiz
Profile icon Doug Ortiz
Nataraj Dasgupta Nataraj Dasgupta
Profile icon Nataraj Dasgupta
Ricardo Anjoleto Farias Ricardo Anjoleto Farias
Profile icon Ricardo Anjoleto Farias
View More author details
Toc

Table of Contents (16) Chapters close

Preface 1. Getting Started with Data Science and R 2. Descriptive and Inferential Statistics 3. Data Wrangling with R 4. KDD, Data Mining, and Text Mining 5. Data Analysis with R 6. Machine Learning with R 7. Forecasting and ML App with R 8. Neural Networks and Deep Learning 9. Markovian in R 10. Visualizing Data 11. Going to Production with R 12. Large Scale Data Analytics with Hadoop 13. R on Cloud 14. The Road Ahead 15. Other Books You May Enjoy

Providing interfaces to Spark packages

API is an acronym for application programming interfaces and you can imagine it as a user interface application, but for software instead of humans. Saying it in another way, it could be seen as a tool for your programming. When you need it to insert a nail, you call a hammer API, and if you need it to remove a nail, then you call a plier API. Spark has its own toolbox API for R, which you can access here: https://spark.apache.org/docs/2.2.0/api/R/index.html.

Following our explanation, extensions are customized R packages created to provide an interface to any Spark package, or the Spark toolbox. There are many extensions already available, but you also can create your own extension to call any of these Spark APIs. One extension example is the rsparkling package viewed in the previous section; it is the rsparkling package that provides an...

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