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
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

Introduction


Streaming is the process of dividing continuously flowing input data into discrete units so that it can be processed easily. Familiar examples in real life are streaming video and audio content (though a user can download the full movie before he/she can watch it, a faster solution is to stream data in small chunks that start playing for the user while the rest of the data is being downloaded in the background).

Real-world examples of streaming, besides multimedia, are the processing of market feeds, weather data, electronic stock trading data, and so on. All these applications produce large volumes of data at very fast rates and require special handling of the data so that you can derive insight from the data in real time.

Streaming has a few basic concepts; it'll be better if we discuss them before we focus on Spark Streaming. The rate at which a streaming application receives data is called data rate and is expressed in the form of kilobytes per second (Kbps) or megabytes per...