Book Image

PySpark for Beginners [Video]

Book Image

PySpark for Beginners [Video]

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 course 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 course, you will have established a firm understanding of the Spark Python API and how it can be used to build data-intensive applications. All the code and supporting files for this course are available on Github at https://github.com/PacktPublishing/PySpark-for-Beginners
Table of Contents (6 chapters)
Chapter 1
Understanding Spark
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Section 2
Spark Jobs and APIs
In this video, you will be provided with a short overview of the Apache Spark Jobs and APIs. This covers the necessary foundation for the subsequent section on Spark 2.0 architecture. - Learn about the execution process - Explore the resilient distributed dataset - Explore DataFrames and Datasets