Book Image

Learning Apache Spark 2

Book Image

Learning Apache Spark 2

Overview of this book

Apache Spark has seen an unprecedented growth in terms of its adoption over the last few years, mainly because of its speed, diversity and real-time data processing capabilities. It has quickly become the preferred choice of tool for many Big Data professionals looking to find quick insights from large chunks of data. This book introduces you to the Apache Spark framework, and familiarizes you with all the latest features and capabilities introduced in Spark 2. Starting with a detailed introduction to Spark’s architecture and the installation procedure, this book covers everything you need to know about the Spark framework in the most practical manner. You will learn how to perform the basic ETL activities using Spark, and work with different components of Spark such as Spark SQL, as well as the Dataset and DataFrame APIs for manipulating your data. Then, you will perform machine learning using Spark MLlib, as well as perform streaming analytics and graph processing using the Spark Streaming and GraphX modules respectively. The book also gives special emphasis on deploying your Spark models, and how they can be operated in a clustered mode. During the course of the book, you will come across implementations of different real-world use-cases and examples, giving you the hands-on knowledge you need to use Apache Spark in the best possible manner.
Table of Contents (18 chapters)
Learning Apache Spark 2
Credits
About the Author
About the Reviewers
www.packtpub.com
Customer Feedback
Preface

Basic graph operators (RDD API)


We have already looked at some basic RDD operators while discussing the RDD API earlier in this book. Graphs also support basic operators to help create new graphs and manipulate them. The two major classes for graphs are:

  • org.apache.spark.graphx.Graph: This is an abstract class that represents a graph with arbitrary objects associated with vertices and edges. This class provides basic operations to access and manipulate the data associated with the vertices and edges, as well as the underlying structure. Like the RDD API, graph API provides a functional structure in which mutating operations would return a new Graph object.
  • org.apache.spark.graphx.GraphOps: The GraphOps class contains additional functionality for graphs. All operations are expressed in terms of efficient GraphXAPI. This class is implicitly constructed for each graph object and can be obtained from the ops value member as follows. You do not need to explicitly get a GraphOps object as Scala...