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Learning Spark SQL

You're reading from Learning Spark SQL

Product type Book

Published in Sep 2017

Publisher Packt

ISBN-13 9781785888359

Pages 452 pages

Edition 1st Edition

Languages

Concepts

Author (1):

Aurobindo Sarkar

Table of Contents (19) Chapters

Title Page

Credits

About the Author

About the Reviewer

www.PacktPub.com

Customer Feedback

Preface

1. Getting Started with Spark SQL

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

Summary

In this chapter, we presented several Spark SQL-based application architectures for building highly-scalable applications. We explored the main concepts and challenges in batch processing and stream processing. We discussed the features of Spark SQL that can help in building robust ETL pipelines. We also presented some code towards building a scalable monitoring application. Additionally, we explored an efficient deployment technique for machine learning pipelines, and some basic concepts involved in using cluster managers such as Mesos and Kubernetes.

In conclusion, this book attempts to help you build a strong foundation in Spark SQL and Scala. However, there are still many areas that you can explore in greater depth to build deeper expertise. Depending on your specific domain, the nature of data and problems could vary widely and your approach to solving them would typically encompass one or more areas described in this book. However, in all cases EDA and data munging skills will...

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Authors (1)

Aurobindo Sarkar

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