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Author: Jason Venner
Publisher: Apress
ISBN: 1430219432
Category : Computers
Languages : en
Pages : 424
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Book Description
You've heard the hype about Hadoop: it runs petabyte–scale data mining tasks insanely fast, it runs gigantic tasks on clouds for absurdly cheap, it's been heavily committed to by tech giants like IBM, Yahoo!, and the Apache Project, and it's completely open-source (thus free). But what exactly is it, and more importantly, how do you even get a Hadoop cluster up and running? From Apress, the name you've come to trust for hands–on technical knowledge, Pro Hadoop brings you up to speed on Hadoop. You learn the ins and outs of MapReduce; how to structure a cluster, design, and implement the Hadoop file system; and how to build your first cloud–computing tasks using Hadoop. Learn how to let Hadoop take care of distributing and parallelizing your software—you just focus on the code, Hadoop takes care of the rest. Best of all, you'll learn from a tech professional who's been in the Hadoop scene since day one. Written from the perspective of a principal engineer with down–in–the–trenches knowledge of what to do wrong with Hadoop, you learn how to avoid the common, expensive first errors that everyone makes with creating their own Hadoop system or inheriting someone else's. Skip the novice stage and the expensive, hard–to–fix mistakes...go straight to seasoned pro on the hottest cloud–computing framework with Pro Hadoop. Your productivity will blow your managers away.
Author: Jason Venner
Publisher: Apress
ISBN: 1430219432
Category : Computers
Languages : en
Pages : 424
Get Book Here
Book Description
You've heard the hype about Hadoop: it runs petabyte–scale data mining tasks insanely fast, it runs gigantic tasks on clouds for absurdly cheap, it's been heavily committed to by tech giants like IBM, Yahoo!, and the Apache Project, and it's completely open-source (thus free). But what exactly is it, and more importantly, how do you even get a Hadoop cluster up and running? From Apress, the name you've come to trust for hands–on technical knowledge, Pro Hadoop brings you up to speed on Hadoop. You learn the ins and outs of MapReduce; how to structure a cluster, design, and implement the Hadoop file system; and how to build your first cloud–computing tasks using Hadoop. Learn how to let Hadoop take care of distributing and parallelizing your software—you just focus on the code, Hadoop takes care of the rest. Best of all, you'll learn from a tech professional who's been in the Hadoop scene since day one. Written from the perspective of a principal engineer with down–in–the–trenches knowledge of what to do wrong with Hadoop, you learn how to avoid the common, expensive first errors that everyone makes with creating their own Hadoop system or inheriting someone else's. Skip the novice stage and the expensive, hard–to–fix mistakes...go straight to seasoned pro on the hottest cloud–computing framework with Pro Hadoop. Your productivity will blow your managers away.
Author: Matt Massie
Publisher: "O'Reilly Media, Inc."
ISBN: 1449329705
Category : Computers
Languages : en
Pages : 255
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Book Description
"Taking dynamic host and application metrics at scale"--Cover.
Author: Danil Zburivsky
Publisher: Packt Publishing Ltd
ISBN: 1783281723
Category : Computers
Languages : en
Pages : 186
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Book Description
This book is a step-by-step tutorial filled with practical examples which will show you how to build and manage a Hadoop cluster along with its intricacies.This book is ideal for database administrators, data engineers, and system administrators, and it will act as an invaluable reference if you are planning to use the Hadoop platform in your organization. It is expected that you have basic Linux skills since all the examples in this book use this operating system. It is also useful if you have access to test hardware or virtual machines to be able to follow the examples in the book.
Author: Bhushan Lakhe
Publisher: Apress
ISBN: 1430265450
Category : Computers
Languages : en
Pages : 199
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Book Description
Practical Hadoop Security is an excellent resource for administrators planning a production Hadoop deployment who want to secure their Hadoop clusters. A detailed guide to the security options and configuration within Hadoop itself, author Bhushan Lakhe takes you through a comprehensive study of how to implement defined security within a Hadoop cluster in a hands-on way. You will start with a detailed overview of all the security options available for Hadoop, including popular extensions like Kerberos and OpenSSH, and then delve into a hands-on implementation of user security (with illustrated code samples) with both in-the-box features and with security extensions implemented by leading vendors. No security system is complete without a monitoring and tracing facility, so Practical Hadoop Security next steps you through audit logging and monitoring technologies for Hadoop, as well as ready to use implementation and configuration examples--again with illustrated code samples. The book concludes with the most important aspect of Hadoop security – encryption. Both types of encryptions, for data in transit and data at rest, are discussed at length with leading open source projects that integrate directly with Hadoop at no licensing cost. Practical Hadoop Security: Explains importance of security, auditing and encryption within a Hadoop installation Describes how the leading players have incorporated these features within their Hadoop distributions and provided extensions Demonstrates how to set up and use these features to your benefit and make your Hadoop installation secure without impacting performance or ease of use
Author: Jeffrey Aven
Publisher: Sams Publishing
ISBN: 0134456726
Category : Computers
Languages : en
Pages : 851
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Book Description
Apache Hadoop is the technology at the heart of the Big Data revolution, and Hadoop skills are in enormous demand. Now, in just 24 lessons of one hour or less, you can learn all the skills and techniques you'll need to deploy each key component of a Hadoop platform in your local environment or in the cloud, building a fully functional Hadoop cluster and using it with real programs and datasets. Each short, easy lesson builds on all that's come before, helping you master all of Hadoop's essentials, and extend it to meet your unique challenges. Apache Hadoop in 24 Hours, Sams Teach Yourself covers all this, and much more: Understanding Hadoop and the Hadoop Distributed File System (HDFS) Importing data into Hadoop, and process it there Mastering basic MapReduce Java programming, and using advanced MapReduce API concepts Making the most of Apache Pig and Apache Hive Implementing and administering YARN Taking advantage of the full Hadoop ecosystem Managing Hadoop clusters with Apache Ambari Working with the Hadoop User Environment (HUE) Scaling, securing, and troubleshooting Hadoop environments Integrating Hadoop into the enterprise Deploying Hadoop in the cloud Getting started with Apache Spark Step-by-step instructions walk you through common questions, issues, and tasks; Q-and-As, Quizzes, and Exercises build and test your knowledge; "Did You Know?" tips offer insider advice and shortcuts; and "Watch Out!" alerts help you avoid pitfalls. By the time you're finished, you'll be comfortable using Apache Hadoop to solve a wide spectrum of Big Data problems.
Author: Zhigang Fang
Publisher: CRC Press
ISBN: 1315680955
Category : Nature
Languages : en
Pages : 569
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Book Description
Energy Science and Applied Technology includes contributions on a wide range of topics:- Technologies in geology, mining, oil and gas exploration and exploitation of deposits- Energy transfer and conversion, materials and chemical technologies- Environmental engineering and sustainable development- Electrical and electronic technology, power system
Author: Sherif Sakr
Publisher: Springer
ISBN: 3319474316
Category : Computers
Languages : en
Pages : 214
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Book Description
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: Cybellium Ltd
Publisher: Cybellium Ltd
ISBN:
Category : Computers
Languages : en
Pages : 202
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Book Description
Unleash the Power of Big Data Processing In the realm of big data, the MapReduce framework stands as a cornerstone, enabling the processing of massive datasets with unparalleled efficiency. "Mastering the MapReduce Framework" is your comprehensive guide to understanding and harnessing the capabilities of this transformative technology, equipping you with the skills needed to navigate the landscape of large-scale data processing. About the Book: As the volume of data continues to grow exponentially, traditional data processing methods fall short. The MapReduce framework emerges as a powerful solution, allowing organizations to process and analyze vast datasets in parallel, thereby unlocking insights and accelerating decision-making. "Mastering the MapReduce Framework" provides a deep dive into this technology, catering to both beginners and experienced professionals seeking to maximize their proficiency in big data processing. Key Features: Foundation Building: Begin by comprehending the fundamental concepts underlying MapReduce. Understand how the framework breaks down complex tasks into smaller, manageable components that can be processed concurrently. Parallel Processing: Dive into the intricacies of parallel processing, a cornerstone of MapReduce. Learn how data is partitioned and distributed across a cluster of machines, enabling lightning-fast computation. Map and Reduce Functions: Grasp the significance of map and reduce functions in the MapReduce paradigm. Learn how to structure these functions to transform and aggregate data efficiently. Hadoop Ecosystem: Explore the Hadoop ecosystem, which houses the MapReduce framework. Understand how Hadoop integrates with other tools to create a comprehensive big data processing environment. Optimizing Performance: Discover techniques for optimizing MapReduce performance. Learn about data locality, combiners, and partitioners that enhance efficiency and reduce resource consumption. Real-World Use Cases: Gain insights into real-world applications of MapReduce across industries. From web log analysis to recommendation systems, explore how the framework powers data-driven solutions. Challenges and Solutions: Explore the challenges of working with MapReduce, such as debugging and handling skewed data. Master strategies to address these challenges and ensure smooth execution. Why This Book Matters: In a data-driven world, the ability to process and extract insights from massive datasets is a competitive advantage. "Mastering the MapReduce Framework" empowers data engineers, analysts, and technology enthusiasts to tap into the potential of big data processing, enabling them to drive innovation and make data-driven decisions with confidence. Who Should Read This Book: Data Engineers: Enhance your big data processing skills with a deep understanding of MapReduce. Data Analysts: Grasp the principles that power large-scale data analysis and gain insights from big data. Technology Enthusiasts: Dive into the world of big data processing and stay ahead of emerging trends. Harness the Power of Big Data Processing: The era of big data requires sophisticated processing tools, and the MapReduce framework stands as a pioneer in this realm. "Mastering the MapReduce Framework" equips you with the knowledge needed to harness the power of MapReduce, unleashing the potential of big data processing and enabling you to navigate the complexities of large-scale data analysis with ease. Your journey to mastering the art of big data processing begins here. © 2023 Cybellium Ltd. All rights reserved. www.cybellium.com
Author: Piotr Gaj
Publisher: Springer
ISBN: 3319194194
Category : Computers
Languages : en
Pages : 471
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Book Description
This book constitutes the thoroughly refereed proceedings of the 22st International Conference on Computer Networks, CN 2015, held in Brunów, Poland, in June 2015. The 42 revised full papers presented were carefully reviewed and selected from 79 submissions. The papers in these proceedings cover the following topics: computer networks, distributed computer systems, communications and teleinformatics.
Author: Mayank Bhushan
Publisher: BPB Publications
ISBN: 9355516665
Category : Computers
Languages : en
Pages : 618
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Book Description
KEY FEATURES ● Learn Apache Hadoop ecosystem and its core components. ● Discover advanced tools like Spark for real-time data processing. ● Master the fundamentals of Big Data and its applications. DESCRIPTION In today's data-driven world, harnessing the power of big data is no longer a luxury, but a necessity. This comprehensive guide, "Big Data and Hadoop," dives deep into the world of big data and equips you with the knowledge and skills you need to conquer even the most complex data landscapes. Start with the fundamentals of big data, exploring its growing significance and diverse applications. You'll look into the heart of the Apache Hadoop ecosystem, mastering its core components like HDFS and MapReduce. We'll demystify NoSQL databases, introducing you to HBase and Cassandra as powerful alternatives to traditional databases. Clarify the details of MapReduce programming with practical examples, and discover the power of PigLatin and HiveQL for efficient data analysis. Explore advanced tools like Spark, unlocking its potential for real-time data processing and analytics. Rounding out your knowledge, the book delves into practical applications, exploring real-world scenarios and research-based insights. By the end of this book, you'll emerge as a confident big data explorer, equipped to tackle any data challenge with expertise and precision. WHAT YOU WILL LEARN ● Gain a solid grasp of the fundamental concepts of big data. ● Acquire a comprehensive understanding of HDFS, MapReduce, YARN, Spark, and related components. ● Learn how to set up and configure Hadoop clusters to create scalable and reliable data processing environments. ● Develop the expertise to design, code, and execute MapReduce jobs to process and analyze vast datasets efficiently. ● Learn how to use Hadoop and related tools to perform advanced data analytics. WHO THIS BOOK IS FOR Whether you are a beginner or have some experience with big data. This book is for aspiring big data professionals, including data analysts, software developers, IT professionals, and students in computer science and related fields. TABLE OF CONTENTS 1. Big Data Introduction and Demand 2. NoSQL Data Management 3. MapReduce Technique 4. Basics of Hadoop 5. Hadoop Installation 6. MapReduce Applications 7. Hadoop Related Tools-I: HBase and Cassandra 8. Hadoop Related Tools-II: PigLatin and HiveQL 9. Practical and Research-based Topics 10. Spark
