Book Image

Learning PySpark

By : Tomasz Drabas, Denny Lee
Book Image

Learning PySpark

By: Tomasz Drabas, Denny Lee

Overview of this book

Apache Spark is an open source framework for efficient cluster computing with a strong interface for data parallelism and fault tolerance. This book will show you how to leverage the power of Python and put it to use in the Spark ecosystem. You will start by getting a firm understanding of the Spark 2.0 architecture and how to set up a Python environment for Spark. You will get familiar with the modules available in PySpark. You will learn how to abstract data with RDDs and DataFrames and understand the streaming capabilities of PySpark. Also, you will get a thorough overview of machine learning capabilities of PySpark using ML and MLlib, graph processing using GraphFrames, and polyglot persistence using Blaze. Finally, you will learn how to deploy your applications to the cloud using the spark-submit command. By the end of this book, you will have established a firm understanding of the Spark Python API and how it can be used to build data-intensive applications.
Table of Contents (20 chapters)
Learning PySpark
Credits
Foreword
About the Authors
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
Index

Chapter 10. Structured Streaming

This chapter will provide a jump-start on the concepts behind Spark Streaming and how this has evolved into Structured Streaming. An important aspect of Structured Streaming is that it utilizes Spark DataFrames. This shift in paradigm will make it easier for Python developers to start working with Spark Streaming.

In this chapter, your will learn:

  • What is Spark Streaming?

  • Why do we need Spark Streaming?

  • What is the Spark Streaming application data flow?

  • Simple streaming application using DStream

  • A quick primer on Spark Streaming global aggregations

  • Introducing Structured Streaming

Note, for the initial sections of this chapter, the example code used will be in Scala, as this was how most Spark Streaming code was written. When we start focusing on Structured Streaming, we will work with Python examples.