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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

Exploring data munging techniques


In this section, we will introduce several munging techniques using household electric consumption and weather Datasets. The best way to learn these techniques is to practice the various ways to manipulate the data contained in various publically available Datasets (in addition to the ones used here). The more you practice, the better you will get at it. In the process, you will probably evolve your own style, and develop several toolsets and techniques to achieve your munging objectives. At a minimum, you should get very comfortable working with and moving between RDDs, DataFrames, and Datasets, computing counts, distinct counts, and various aggregations to cross-check your results and match your intuitive understanding the Datasets. Additionally, it is also important to develop the ability to make decisions based on the pros and cons of executing any given munging step.

We will attempt to accomplish the following objectives in this section:

  1. Pre-process...
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