Book Image

Apache Spark 2.x Cookbook

By : Rishi Yadav
Book Image

Apache Spark 2.x Cookbook

By: Rishi Yadav

Overview of this book

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.
Table of Contents (19 chapters)
Title Page
About the Author
About the Reviewer
Customer Feedback

Chapter 1. Getting Started with Apache Spark

In this chapter, we will set up Spark and configure it. This chapter contains the following recipes:

  • Leveraging Databricks Cloud
  • Deploying Spark using Amazon EMR
  • Installing Spark from binaries
  • Building the Spark source code with Maven
  • Launching Spark on Amazon EC2
  • Deploying Spark on a cluster in standalone mode
  • Deploying Spark on a cluster with Mesos
  • Deploying Spark on a cluster with YARN
  • Understanding SparkContext and SparkSession
  • Understanding Resilient Distributed Datasets (RDD)