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Description

Apache Spark is the next standard of open-source cluster-computing engine for processing big data. Many practical computing problems concern large graphs, like the Web graph and various social networks. The scale of these graphs - in some cases billions of vertices, trillions of edges - poses challenges to their efficient processing. Apache Spark GraphX API combines the advantages of both data-parallel and graph-parallel systems by efficiently expressing graph computation within the Spark data-parallel framework. This book will teach the user to do graphical programming in Apache Spark, apart from an explanation of the entire process of graphical data analysis. You will journey through the creation of graphs, its uses, its exploration and analysis and finally will also cover the conversion of graph elements into graph structures. This book begins with an introduction of the Spark system, its libraries and the Scala Build Tool. Using a hands-on approach, this book will quickly teach you how to install and leverage Spark interactively on the command line and in a standalone Scala program. Then, it presents all the methods for building Spark graphs using illustrative network datasets. Next, it will walk you through the process of exploring, visualizing and analyzing different network characteristics. This book will also teach you how to transform raw datasets into a usable form. In addition, you will learn powerful operations that can be used to transform graph elements and graph structures. Furthermore, this book also teaches how to create custom graph operations that are tailored for specific needs with efficiency in mind. The later chapters of this book cover more advanced topics such as clustering graphs, implementing graph-parallel iterative algorithms and learning methods from graph data.

What you will learn

Write, build and deploy Spark applications with the Scala Build Tool.

Build and analyze largescale network datasets

Analyze and transform graphs using RDD and graphspecific operations

Implement new custom graph operations tailored to specific needs.

Develop iterative and efficient graph algorithms using message aggregation and Pregel abstraction

Extract subgraphs and use it to discover common clusters

Analyze graph data and solve various data science problems using realworld datasets.

What do you get with eBook?

Instant access to your Digital eBook purchase

Download this book in EPUB and PDF formats

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

Frequently bought together

Spark Cookbook

Jul 2015 226 pages

4.4 (18)

eBook

zł79.99 ~~zł164.99~~

Apache Spark Graph Processing

Sep 2015 148 pages

3.5 (2)

eBook

zł79.99 ~~zł132.99~~

Total zł 371.98

zł205.99

zł165.99

Total zł 371.98

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nag Jun 18, 2016

Reading it. will give full feedback later.

Amazon Verified review

MSastry Nov 01, 2015

This book is easy to read with a promise to provide step by step procedures to learn Apache Spark Graph Processing. To the most extent, Mr. Rindra Ramamonjison fulfills the promise. There are several errors in the book as such reader gets confused and can not be followed through the text. For example, spark-1.4.1-bin-hadoop2.6.tgz does not have the directories: core, graphx, mllib, sql, and streaming in SPARKHOME. Also, in the directory data, there are no files such as people.csv and links.csv.Apart from the above superficial errors, the book met my expectation to learn Graph Processing.

Apache Spark Graph Processing: Build, process and analyze large-scale graph data effectively with Spark

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