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© 2018

Practical Apache Spark

Using the Scala API

Book

Table of contents

  1. Front Matter
    Pages i-xvi
  2. Subhashini Chellappan, Dharanitharan Ganesan
    Pages 1-37
  3. Subhashini Chellappan, Dharanitharan Ganesan
    Pages 39-77
  4. Subhashini Chellappan, Dharanitharan Ganesan
    Pages 79-113
  5. Subhashini Chellappan, Dharanitharan Ganesan
    Pages 115-139
  6. Subhashini Chellappan, Dharanitharan Ganesan
    Pages 141-156
  7. Subhashini Chellappan, Dharanitharan Ganesan
    Pages 157-174
  8. Subhashini Chellappan, Dharanitharan Ganesan
    Pages 175-187
  9. Subhashini Chellappan, Dharanitharan Ganesan
    Pages 189-236
  10. Subhashini Chellappan, Dharanitharan Ganesan
    Pages 237-260
  11. Subhashini Chellappan, Dharanitharan Ganesan
    Pages 261-273
  12. Back Matter
    Pages 275-280

About this book

Introduction

Work with Apache Spark using Scala to deploy and set up single-node, multi-node, and high-availability clusters. This book discusses various components of Spark such as Spark Core, DataFrames, Datasets and SQL, Spark Streaming, Spark MLib, and R on Spark with the help of practical code snippets for each topic. Practical Apache Spark also covers the integration of Apache Spark with Kafka with examples. You’ll follow a learn-to-do-by-yourself approach to learning – learn the concepts, practice the code snippets in Scala, and complete the assignments given to get an overall exposure. 

On completion, you’ll have knowledge of the functional programming aspects of Scala, and hands-on expertise in various Spark components. You’ll also become familiar with machine learning algorithms with real-time usage.

You will:
  • Discover the functional programming features of Scala
  • Understand the complete architecture of Spark and its components
  • Integrate Apache Spark with Hive and Kafka 
  • Use Spark SQL, DataFrames, and Datasets to process data using traditional SQL queries
  • Work with different machine learning concepts and libraries using Spark's MLlib packages

Keywords

Apache Spark Scala Big Data Machine Learning Kafka R

Authors and affiliations

  1. 1.BangaloreIndia
  2. 2.KrishnagiriIndia

About the authors

Subhashini Chellappan is a technology enthusiast with expertise in the big data and cloud space. She has rich experience in both academia and the software industry. Her areas of interest and expertise are centered on business intelligence, big data analytics and cloud computing.

Dharanitharan Ganesan is a senior analyst with five years of experience in IT. He has a high level of exposure and experience in big data – Apache Hadoop, Apache Spark and various Hadoop ecosystem components. He has a proven track record of improving efficiency and productivity through the automation of various routine and administrative functions in business intelligence and big data technologies. His areas of interest and expertise are centered on machine learning algorithms, statistical modelling and predictive analysis.



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