Large Scale Graph Processing Using Apache Giraph

Author : Sherif Sakr
Publisher : Springer
ISBN 13 : 3319474316
Total Pages : 197 pages
Book Rating : 4.11/5 ( download)

DOWNLOAD NOW!

Download or read book Large-Scale Graph Processing Using Apache Giraph written by Sherif Sakr and published by Springer. This book was released on 2017-01-05 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book takes its reader on a journey through Apache Giraph, a popular distributed graph processing platform designed to bring the power of big data processing to graph data. Designed as a step-by-step self-study guide for everyone interested in large-scale graph processing, it describes the fundamental abstractions of the system, its programming models and various techniques for using the system to process graph data at scale, including the implementation of several popular and advanced graph analytics algorithms. The book is organized as follows: Chapter 1 starts by providing a general background of the big data phenomenon and a general introduction to the Apache Giraph system, its abstraction, programming model and design architecture. Next, chapter 2 focuses on Giraph as a platform and how to use it. Based on a sample job, even more advanced topics like monitoring the Giraph application lifecycle and different methods for monitoring Giraph jobs are explained. Chapter 3 then provides an introduction to Giraph programming, introduces the basic Giraph graph model and explains how to write Giraph programs. In turn, Chapter 4 discusses in detail the implementation of some popular graph algorithms including PageRank, connected components, shortest paths and triangle closing. Chapter 5 focuses on advanced Giraph programming, discussing common Giraph algorithmic optimizations, tunable Giraph configurations that determine the system’s utilization of the underlying resources, and how to write a custom graph input and output format. Lastly, chapter 6 highlights two systems that have been introduced to tackle the challenge of large scale graph processing, GraphX and GraphLab, and explains the main commonalities and differences between these systems and Apache Giraph. This book serves as an essential reference guide for students, researchers and practitioners in the domain of large scale graph processing. It offers step-by-step guidance, with several code examples and the complete source code available in the related github repository. Students will find a comprehensive introduction to and hands-on practice with tackling large scale graph processing problems using the Apache Giraph system, while researchers will discover thorough coverage of the emerging and ongoing advancements in big graph processing systems.

Author : Roman Shaposhnik
Publisher : Apress
ISBN 13 : 1484212517
Total Pages : 320 pages
Book Rating : 4.16/5 ( download)

DOWNLOAD NOW!

Download or read book Practical Graph Analytics with Apache Giraph written by Roman Shaposhnik and published by Apress. This book was released on 2015-11-19 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: Practical Graph Analytics with Apache Giraph helps you build data mining and machine learning applications using the Apache Foundation’s Giraph framework for graph processing. This is the same framework as used by Facebook, Google, and other social media analytics operations to derive business value from vast amounts of interconnected data points. Graphs arise in a wealth of data scenarios and describe the connections that are naturally formed in both digital and real worlds. Examples of such connections abound in online social networks such as Facebook and Twitter, among users who rate movies from services like Netflix and Amazon Prime, and are useful even in the context of biological networks for scientific research. Whether in the context of business or science, viewing data as connected adds value by increasing the amount of information available to be drawn from that data and put to use in generating new revenue or scientific opportunities. Apache Giraph offers a simple yet flexible programming model targeted to graph algorithms and designed to scale easily to accommodate massive amounts of data. Originally developed at Yahoo!, Giraph is now a top top-level project at the Apache Foundation, and it enlists contributors from companies such as Facebook, LinkedIn, and Twitter. Practical Graph Analytics with Apache Giraph brings the power of Apache Giraph to you, showing how to harness the power of graph processing for your own data by building sophisticated graph analytics applications using the very same framework that is relied upon by some of the largest players in the industry today.

Author : Claudio Martella
Publisher :
ISBN 13 : 9781617291753
Total Pages : 0 pages
Book Rating : 4.57/5 ( download)

DOWNLOAD NOW!

Download or read book Giraph in Action written by Claudio Martella and published by . This book was released on 2015-04-07 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Graph data structures are nothing more than representations of the relationship between entities. Although graph data tends to be intuitively understandable, graph algorithms must be extremely powerful and scalable to manage the nearly-incalculable potential relationships within large data sets. To efficiently process graph data, an equally powerful graph processing framework like Apache Giraph is essential. Apache Giraph supplies many algorithms needed to draw conclusions from graph data, but can also be used to design custom graph algorithms. Whether trying to identify patterns in social data, optimize the traffic on a network, or any set of highly-connected data, Giraph has the tools that allow users to focus on the meaning of data instead of the chore of processing it. Giraph in Action is a comprehensive guide that teaches the application of the Apache Giraph programming model to real-world graph data examples. It starts by showing how to mine graph data using the most straightforward algorithms. Then, it dives into the Giraph architecture and the main APIs as readers discover how to model and process more complex scenarios. Along the way, it offers techniques for handling data from disparate sources, swapping data in and out of memory, and running Giraph in the cloud. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

Author : Sherif Sakr
Publisher : Springer
ISBN 13 : 9783319775241
Total Pages : 1820 pages
Book Rating : 4.43/5 ( download)

DOWNLOAD NOW!

Download or read book Encyclopedia of Big Data Technologies written by Sherif Sakr and published by Springer. This book was released on 2019-03-01 with total page 1820 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Encyclopedia of Big Data Technologies provides researchers, educators, students and industry professionals with a comprehensive authority over the most relevant Big Data Technology concepts. With over 300 articles written by worldwide subject matter experts from both industry and academia, the encyclopedia covers topics such as big data storage systems, NoSQL database, cloud computing, distributed systems, data processing, data management, machine learning and social technologies, data science. Each peer-reviewed, highly structured entry provides the reader with basic terminology, subject overviews, key research results, application examples, future directions, cross references and a bibliography. The entries are expository and tutorial, making this reference a practical resource for students, academics, or professionals. In addition, the distinguished, international editorial board of the encyclopedia consists of well-respected scholars, each developing topics based upon their expertise.

Author : Yingxia Shao
Publisher : Springer Nature
ISBN 13 : 9811539286
Total Pages : 154 pages
Book Rating : 4.82/5 ( download)

DOWNLOAD NOW!

Download or read book Large-scale Graph Analysis: System, Algorithm and Optimization written by Yingxia Shao and published by Springer Nature. This book was released on 2020-07-01 with total page 154 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces readers to a workload-aware methodology for large-scale graph algorithm optimization in graph-computing systems, and proposes several optimization techniques that can enable these systems to handle advanced graph algorithms efficiently. More concretely, it proposes a workload-aware cost model to guide the development of high-performance algorithms. On the basis of the cost model, the book subsequently presents a system-level optimization resulting in a partition-aware graph-computing engine, PAGE. In addition, it presents three efficient and scalable advanced graph algorithms – the subgraph enumeration, cohesive subgraph detection, and graph extraction algorithms. This book offers a valuable reference guide for junior researchers, covering the latest advances in large-scale graph analysis; and for senior researchers, sharing state-of-the-art solutions based on advanced graph algorithms. In addition, all readers will find a workload-aware methodology for designing efficient large-scale graph algorithms.

Author : Rindra Ramamonjison
Publisher : Packt Publishing Ltd
ISBN 13 : 1784398950
Total Pages : 148 pages
Book Rating : 4.58/5 ( download)

DOWNLOAD NOW!

Download or read book Apache Spark Graph Processing written by Rindra Ramamonjison and published by Packt Publishing Ltd. This book was released on 2015-09-10 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build, process and analyze large-scale graph data effectively with Spark About This Book Find solutions for every stage of data processing from loading and transforming graph data to Improve the scalability of your graphs with a variety of real-world applications with complete Scala code. A concise guide to processing large-scale networks with Apache Spark. Who This Book Is For This book is for data scientists and big data developers who want to learn the processing and analyzing graph datasets at scale. Basic programming experience with Scala is assumed. Basic knowledge of Spark is assumed. What You Will Learn Write, build and deploy Spark applications with the Scala Build Tool. Build and analyze large-scale network datasets Analyze and transform graphs using RDD and graph-specific 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 real-world datasets. In Detail 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. Style and approach A step-by-step guide that will walk you through the key ideas and techniques for processing big graph data at scale, with practical examples that will ensure an overall understanding of the concepts of Spark.

Author : Florin Pop
Publisher : Springer
ISBN 13 : 3319448811
Total Pages : 516 pages
Book Rating : 4.17/5 ( download)

DOWNLOAD NOW!

Download or read book Resource Management for Big Data Platforms written by Florin Pop and published by Springer. This book was released on 2016-10-27 with total page 516 pages. Available in PDF, EPUB and Kindle. Book excerpt: Serving as a flagship driver towards advance research in the area of Big Data platforms and applications, this book provides a platform for the dissemination of advanced topics of theory, research efforts and analysis, and implementation oriented on methods, techniques and performance evaluation. In 23 chapters, several important formulations of the architecture design, optimization techniques, advanced analytics methods, biological, medical and social media applications are presented. These chapters discuss the research of members from the ICT COST Action IC1406 High-Performance Modelling and Simulation for Big Data Applications (cHiPSet). This volume is ideal as a reference for students, researchers and industry practitioners working in or interested in joining interdisciplinary works in the areas of intelligent decision systems using emergent distributed computing paradigms. It will also allow newcomers to grasp the key concerns and their potential solutions.

Author : Sonal Raj
Publisher : Packt Publishing Ltd
ISBN 13 : 1783555165
Total Pages : 192 pages
Book Rating : 4.61/5 ( download)

DOWNLOAD NOW!

Download or read book Neo4j High Performance written by Sonal Raj and published by Packt Publishing Ltd. This book was released on 2015-03-02 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you are a professional or enthusiast who has a basic understanding of graphs or has basic knowledge of Neo4j operations, this is the book for you. Although it is targeted at an advanced user base, this book can be used by beginners as it touches upon the basics. So, if you are passionate about taming complex data with the help of graphs and building high performance applications, you will be able to get valuable insights from this book.

Author : George Fletcher
Publisher : Springer
ISBN 13 : 3319961934
Total Pages : 186 pages
Book Rating : 4.34/5 ( download)

DOWNLOAD NOW!

Download or read book Graph Data Management written by George Fletcher and published by Springer. This book was released on 2018-10-31 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a comprehensive overview of fundamental issues and recent advances in graph data management. Its aim is to provide beginning researchers in the area of graph data management, or in fields that require graph data management, an overview of the latest developments in this area, both in applied and in fundamental subdomains. The topics covered range from a general introduction to graph data management, to more specialized topics like graph visualization, flexible queries of graph data, parallel processing, and benchmarking. The book will help researchers put their work in perspective and show them which types of tools, techniques and technologies are available, which ones could best suit their needs, and where there are still open issues and future research directions. The chapters are contributed by leading experts in the relevant areas, presenting a coherent overview of the state of the art in the field. Readers should have a basic knowledge of data management techniques as they are taught in computer science MSc programs.

Author : Mark Needham
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1492047635
Total Pages : 297 pages
Book Rating : 4.36/5 ( download)

DOWNLOAD NOW!

Download or read book Graph Algorithms written by Mark Needham and published by "O'Reilly Media, Inc.". This book was released on 2019-05-16 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover how graph algorithms can help you leverage the relationships within your data to develop more intelligent solutions and enhance your machine learning models. You’ll learn how graph analytics are uniquely suited to unfold complex structures and reveal difficult-to-find patterns lurking in your data. Whether you are trying to build dynamic network models or forecast real-world behavior, this book illustrates how graph algorithms deliver value—from finding vulnerabilities and bottlenecks to detecting communities and improving machine learning predictions. This practical book walks you through hands-on examples of how to use graph algorithms in Apache Spark and Neo4j—two of the most common choices for graph analytics. Also included: sample code and tips for over 20 practical graph algorithms that cover optimal pathfinding, importance through centrality, and community detection. Learn how graph analytics vary from conventional statistical analysis Understand how classic graph algorithms work, and how they are applied Get guidance on which algorithms to use for different types of questions Explore algorithm examples with working code and sample datasets from Spark and Neo4j See how connected feature extraction can increase machine learning accuracy and precision Walk through creating an ML workflow for link prediction combining Neo4j and Spark