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Apache Spark 2.x Cookbook Cover

Apache Spark 2.x Cookbook

Over 70 cloud-ready recipes for distributed Big Data processing and analytics

Publisher:Packt Publishing Limited
By:   
Paid access
|Jul 2025
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Description

Perform lightning-fast Big Data processing using Apache Spark 2.x with help of this practical guide

Key Features

  • Contains quick solutions to solving even the most complex Big Data processing problems using Apache Spark
  • Leverage the power of Apache Spark as a unified compute engine and perform streaming analytics, machine learning and graph processing with ease
  • From installing and setting up Spark to fine-tuning its performance, this practical guide is all you need to become a master in using Apache Spark

Book Description

While Apache Spark 1.x gained a lot of traction and adoption in the early years, Spark 2.x delivers notable improvements in the areas of API, schema awareness, Performance, Structured Streaming, and simplifying building blocks to build better, faster, smarter, and more accessible big data applications. This book uncovers all these features in the form of structured recipes to analyze and mature large and complex sets of data.

Starting with installing and configuring Apache Spark with various cluster managers, you will learn to set up development environments. Further on, you will be introduced to working with RDDs, DataFrames and Datasets to operate on schema aware data, and real-time streaming with various sources such as Twitter Stream and Apache Kafka. You will also work through recipes on machine learning, including supervised learning, unsupervised learning & recommendation engines in Spark.

Last but not least, the final few chapters delve deeper into the concepts of graph processing using GraphX, securing your implementations, cluster optimization, and troubleshooting.

What you will learn

  • Install and configure Apache Spark with various cluster managers & on AWS
  • Set up a development environment for Apache Spark including Databricks Cloud notebook
  • Find out how to operate on data in Spark with schemas
  • Get to grips with real-time streaming analytics using Spark Streaming & Structured Streaming
  • Master supervised learning and unsupervised learning using MLlib
  • Build a recommendation engine using MLlib
  • Graph processing using GraphX and GraphFrames libraries
  • Develop a set of common applications or project types, and solutions that solve complex big data problems

Who this book is for

This book is for data engineers, data scientists, and Big Data professionals who want to leverage the power of Apache Spark 2.x for real-time Big Data processing. If you’re looking for quick solutions to common problems while using Spark 2.x effectively, this book will also help you. The book assumes you have a basic knowledge of Scala as a programming language.

Table of Contents

  1. Getting Started with Apache Spark
  2. Developing Applications with Spark
  3. Spark SQL
  4. Working with External Data Sources
  5. Spark Streaming
  6. Getting Started with Machine Learning
  7. Supervised Learning with MLlib
  8. Supervised Learning with MLlib
  9. Unsupervised learning
  10. Recommendations Using Collaborative Filtering
  11. Graph Processing Using GraphX and GraphFrames
  12. Optimizations and Performance Tuning
PDF ISBN: 978-1-78712-751-7
Publisher: Packt Publishing Limited
Copyright owner: © 2017 Packt Publishing Limited
Publication date: 2025
Language: English
Pages: 294
Related subjects:
Computer sciences,
Databases and data mining
BISAC subjects:
COM018000,
COM021040,
COM062000
Thema subjects:
UNC,
GPH,
UND,
UNA,
UYZM

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