深度解析《Spark GraphX实战指南》：专为图计算探索

Spark

GraphX

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ABOUT THIS BOOK xv

How this book is organized

This book is divided into three parts. Part 1 consists of three chapters that cover the

prerequisites to using Spark GraphX. The four chapters in part 2 cover standard and

expected ways to use GraphX, and the three chapters in part 3 are on advanced topics.

We also could have divided the book into two parts, with the first five chapters cov-

ering the prerequisites and basic GraphX

API, and the last five chapters covering ways

to apply GraphX.

Here’s a run-down of the ten chapters:

 Chapter 1 sets the stage with what Big Data, Spark, and graphs are, and how

Spark GraphX fits into a processing data flow. Chapter 1 is a mini-book unto

itself—not in length, but in its breadth of overview.

 Chapter 2 is a very brief, hands-on demonstration of using GraphX—no experi-

ence required.

 Chapter 3 covers the prerequisites of Spark, Scala, and graphs.

 Chapter 4 discusses how to do basic Spark GraphX operations and presents the

two main methods of implementing custom GraphX algorithms: Map/Reduce

and Pregel.

 Chapter 5 illustrates how to use the numerous algorithms built into GraphX.

 Chapter 6 is where something outside the API is finally covered. Here we take

some of the classic mid-20th century graph algorithms and show how they can

be implemented in GraphX.

 Chapter 7 is a lengthy and ambitious chapter on machine learning. Normally

this would require a book unto itself, but here we cover machine learning with-

out assuming any prior knowledge or experience and quickly ramp up to

advanced examples of supervised, unsupervised, and semi-supervised learning.

 Chapter 8 shows how some operations can be done in GraphX that one might

assume would come built into a graph-processing package: reading RDF files,

merging graphs, finding graph isomorphisms, and computing the global clus-

tering coefficient.

 Chapter 9 shows how to monitor performance and see what your GraphX appli-

cation is doing. It then shows how to do performance tuning through tech-

niques like caching, checkpointing, and serializer tuning.

 Chapter 10 describes how to use languages other than Scala with GraphX (but

strongly advises against it) and also discusses how to use tools that complement

GraphX. It demonstrates Apache Zeppelin notebook software with GraphX to

provide visualization of graphs inline with an interactive notebook shell. The

third-party tool Spark JobServer can be used to convert GraphX from a

mere batch graph processing system to an online database of sorts. Finally,

ABOUT THIS BOOKxvi

GraphFrames is a library on GitHub (developed by some of the developers of

GraphX) that uses Spark

SQL DataFrames rather than RDDs to provide a conve-

nient and high-performing way to query graphs.

We also include four appendixes in the book. Appendix A addresses installing Spark

and appendix B gives a brief overview of Gephi visualization software. In appendix C

you’ll find a number of online resources for additional information about GraphX

and where to go to keep up with latest developments. Finally, appendix D lists the

Scala tips given throughout the book.

Anyone new to Spark, Scala, or graphs should progress through the first five chap-

ters linearly. After that, you can pick and choose topics from the last five chapters.

Anyone who is expert in Spark, Scala, and graphs but new to GraphX can skip

chapter 3 and probably also chapter 5.

About the code

The source code for this book is available for download from manning.com at https://

www.manning.com/books/spark-graphx-in-action.

For the most part, the code presented in this book and available for download is

intended to be used with the interactive Spark shell. Thus, the .scala extension is tech-

nically a misnomer, as these files can’t be compiled with the scalac compiler.

Some examples are meant to be conventionally compiled and executed, and these

are always accompanied by a pom.xml for Maven or by a .sbt for sbt (Simple Build

Tool).

This book contains many examples of source code, both in numbered listings and

inline with normal text. In both cases, source code is formatted in a

fixed-width

font like this

to separate it from ordinary text.

In many cases, the original source code has been reformatted; we’ve added line

breaks and reworked indentation to accommodate the available page space in the book.

In rare cases, even this was not enough, and listings may include line-continuation

markers (

➥

). Additionally, comments in the source code have often been removed

from the listings when the code is described in the text. Code annotations accompany

many of the listings, highlighting important concepts.

The code for the examples in this book can be downloaded from the publisher’s

website at www.manning.com/books/spark-graphx-in-action.

Author Online

Purchase of Spark GraphX in Action includes free access to a private web forum run by

Manning Publications where you can make comments about the book, ask technical

questions, and receive help from the authors and from other users. To access the

forum and subscribe to it, point your web browser to www.manning.com/books/spark-

graphx-in-action. This page provides information on how to get on the forum once you

are registered, what kind of help is available, and the rules of conduct on the forum.

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深度解析《Spark GraphX实战指南》：专为图计算探索

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