Book Image

Fast Data Processing with Spark 2 - Third Edition

By : Holden Karau
Book Image

Fast Data Processing with Spark 2 - Third Edition

By: Holden Karau

Overview of this book

When people want a way to process big data at speed, Spark is invariably the solution. With its ease of development (in comparison to the relative complexity of Hadoop), it’s unsurprising that it’s becoming popular with data analysts and engineers everywhere. Beginning with the fundamentals, we’ll show you how to get set up with Spark with minimum fuss. You’ll then get to grips with some simple APIs before investigating machine learning and graph processing – throughout we’ll make sure you know exactly how to apply your knowledge. You will also learn how to use the Spark shell, how to load data before finding out how to build and run your own Spark applications. Discover how to manipulate your RDD and get stuck into a range of DataFrame APIs. As if that’s not enough, you’ll also learn some useful Machine Learning algorithms with the help of Spark MLlib and integrating Spark with R. We’ll also make sure you’re confident and prepared for graph processing, as you learn more about the GraphX API.
Table of Contents (18 chapters)
Fast Data Processing with Spark 2 Third Edition
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface

SparkSession versus SparkContext


You would have noticed that we are using SparkSession and SparkContext, and this is not an error. Let's revisit the annals of Spark history for a perspective. It is important to understand where we came from, as you will hear about these connection objects for some time to come.

Prior to Spark 2.0.0, the three main connection objects were SparkContext, SqlContext, and HiveContext. The SparkContext object was the connection to a Spark execution environment and created RDDs and others, SQLContext worked with SparkSQL in the background of SparkContext, and HiveContext interacted with the Hive stores.

Spark 2.0.0 introduced Datasets/DataFrames as the main distributed data abstraction interface and the SparkSession object as the entry point to a Spark execution environment. Appropriately, the SparkSession object is found in the namespace, org.apache.spark.sql.SparkSession (Scala), or pyspark.sql.sparkSession. A few points to note are as follows:

  • In Scala and Java...