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Learning Spark SQL

You're reading from   Learning Spark SQL Architect streaming analytics and machine learning solutions

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Product type Paperback
Published in Sep 2017
Publisher Packt
ISBN-13 9781785888359
Length 452 pages
Edition 1st Edition
Languages
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Author (1):
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Aurobindo Sarkar Aurobindo Sarkar
Author Profile Icon Aurobindo Sarkar
Aurobindo Sarkar
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Table of Contents (13) Chapters Close

Preface 1. Getting Started with Spark SQL FREE CHAPTER 2. Using Spark SQL for Processing Structured and Semistructured Data 3. Using Spark SQL for Data Exploration 4. Using Spark SQL for Data Munging 5. Using Spark SQL in Streaming Applications 6. Using Spark SQL in Machine Learning Applications 7. Using Spark SQL in Graph Applications 8. Using Spark SQL with SparkR 9. Developing Applications with Spark SQL 10. Using Spark SQL in Deep Learning Applications 11. Tuning Spark SQL Components for Performance 12. Spark SQL in Large-Scale Application Architectures

Munging textual data

In this section, we explore data munging techniques for typical text analysis situations. Many text-based analyses tasks require computing word counts, removing stop words, stemming, and so on. In addition, we will also explore how you can process multiple files, one at a time, from HDFS directories.

First, we import all the classes that will be used in this section:

Processing multiple input data files

In the next few steps, we initialize a set of variables for defining the directory containing the input files, and an empty RDD. We also create a list of filenames from the input HDFS directory. In the following example, we will work with files contained in a single directory; however, the techniques can...

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