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Scala and Spark for Big Data Analytics

You're reading from   Scala and Spark for Big Data Analytics Explore the concepts of functional programming, data streaming, and machine learning

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Product type Paperback
Published in Jul 2017
Publisher Packt
ISBN-13 9781785280849
Length 796 pages
Edition 1st Edition
Languages
Concepts
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Authors (2):
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Sridhar Alla Sridhar Alla
Author Profile Icon Sridhar Alla
Sridhar Alla
Md. Rezaul Karim Md. Rezaul Karim
Author Profile Icon Md. Rezaul Karim
Md. Rezaul Karim
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Toc

Table of Contents (19) Chapters Close

Preface 1. Introduction to Scala 2. Object-Oriented Scala FREE CHAPTER 3. Functional Programming Concepts 4. Collection APIs 5. Tackle Big Data – Spark Comes to the Party 6. Start Working with Spark – REPL and RDDs 7. Special RDD Operations 8. Introduce a Little Structure - Spark SQL 9. Stream Me Up, Scotty - Spark Streaming 10. Everything is Connected - GraphX 11. Learning Machine Learning - Spark MLlib and Spark ML 12. My Name is Bayes, Naive Bayes 13. Time to Put Some Order - Cluster Your Data with Spark MLlib 14. Text Analytics Using Spark ML 15. Spark Tuning 16. Time to Go to ClusterLand - Deploying Spark on a Cluster 17. Testing and Debugging Spark 18. PySpark and SparkR

StopWordsRemover

StopWordsRemover is a Transformer that takes a String array of words and returns a String array after removing all the defined stop words. Some examples of stop words are I, you, my, and, or, and so on which are fairly commonly used in the English language. You can override or extend the set of stop words to suit the purpose of the use case. Without this cleansing process, the subsequent algorithms might be biased because of the common words.

In order to invoke StopWordsRemover, you need to import the following package:

import org.apache.spark.ml.feature.StopWordsRemover

First, you need to initialize a StopWordsRemover , specifying the input column and the output column. Here, we are choosing the words column created by the Tokenizer and generate an output column for the filtered words after removal of stop words:

scala> val remover = new StopWordsRemover(...
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