Hadoop In Practice
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Hadoop In Practice
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Author : Alex Holmes
language : en
Publisher: Simon and Schuster
Release Date : 2014-09-29
Hadoop In Practice written by Alex Holmes and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-29 with Computers categories.
Summary Hadoop in Practice, Second Edition provides over 100 tested, instantly useful techniques that will help you conquer big data, using Hadoop. This revised new edition covers changes and new features in the Hadoop core architecture, including MapReduce 2. Brand new chapters cover YARN and integrating Kafka, Impala, and Spark SQL with Hadoop. You'll also get new and updated techniques for Flume, Sqoop, and Mahout, all of which have seen major new versions recently. In short, this is the most practical, up-to-date coverage of Hadoop available anywhere. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Book It's always a good time to upgrade your Hadoop skills! Hadoop in Practice, Second Edition provides a collection of 104 tested, instantly useful techniques for analyzing real-time streams, moving data securely, machine learning, managing large-scale clusters, and taming big data using Hadoop. This completely revised edition covers changes and new features in Hadoop core, including MapReduce 2 and YARN. You'll pick up hands-on best practices for integrating Spark, Kafka, and Impala with Hadoop, and get new and updated techniques for the latest versions of Flume, Sqoop, and Mahout. In short, this is the most practical, up-to-date coverage of Hadoop available. Readers need to know a programming language like Java and have basic familiarity with Hadoop. What's Inside Thoroughly updated for Hadoop 2 How to write YARN applications Integrate real-time technologies like Storm, Impala, and Spark Predictive analytics using Mahout and RR Readers need to know a programming language like Java and have basic familiarity with Hadoop. About the Author Alex Holmes works on tough big-data problems. He is a software engineer, author, speaker, and blogger specializing in large-scale Hadoop projects. Table of Contents PART 1 BACKGROUND AND FUNDAMENTALS Hadoop in a heartbeat Introduction to YARN PART 2 DATA LOGISTICS Data serialization—working with text and beyond Organizing and optimizing data in HDFS Moving data into and out of Hadoop PART 3 BIG DATA PATTERNS Applying MapReduce patterns to big data Utilizing data structures and algorithms at scale Tuning, debugging, and testing PART 4 BEYOND MAPREDUCE SQL on Hadoop Writing a YARN application
Hadoop Practice Guide
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Author : Jisha Mariam Jose
language : en
Publisher: Notion Press
Release Date : 2019-08-19
Hadoop Practice Guide written by Jisha Mariam Jose and has been published by Notion Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-19 with Juvenile Nonfiction categories.
This book is a complete practical approach for Hadoop lovers. It is mainly aimed at beginners who want to have a hands-on experience with Hadoop and its ecosystem. Its simplicity and step-by-step explanation will help students and other readers in the computer science industry to use this book as a reference manual. The book has been divided into various chapters that cover Hadoop installation, Summary on Hadoop core components, General commands in Hadoop with examples, SQOOP-import & export commands with verification steps, Pig Latin Commands, Analysis using Pig Latin, Pig Script examples, HiveQL Queries and expected outputs and HBase with CRUD operations. In short, this book is a guide for programmers and non-programmers to begin their projects in Hadoop. It is also suitable as a reference manual for students and professionals who are new to the Hadoop Ecosystems.
Hadoop In Action
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Author : Chuck Lam
language : en
Publisher: Simon and Schuster
Release Date : 2010-11-30
Hadoop In Action written by Chuck Lam and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-11-30 with Computers categories.
Hadoop in Action teaches readers how to use Hadoop and write MapReduce programs. The intended readers are programmers, architects, and project managers who have to process large amounts of data offline. Hadoop in Action will lead the reader from obtaining a copy of Hadoop to setting it up in a cluster and writing data analytic programs. The book begins by making the basic idea of Hadoop and MapReduce easier to grasp by applying the default Hadoop installation to a few easy-to-follow tasks, such as analyzing changes in word frequency across a body of documents. The book continues through the basic concepts of MapReduce applications developed using Hadoop, including a close look at framework components, use of Hadoop for a variety of data analysis tasks, and numerous examples of Hadoop in action. Hadoop in Action will explain how to use Hadoop and present design patterns and practices of programming MapReduce. MapReduce is a complex idea both conceptually and in its implementation, and Hadoop users are challenged to learn all the knobs and levers for running Hadoop. This book takes you beyond the mechanics of running Hadoop, teaching you to write meaningful programs in a MapReduce framework. This book assumes the reader will have a basic familiarity with Java, as most code examples will be written in Java. Familiarity with basic statistical concepts (e.g. histogram, correlation) will help the reader appreciate the more advanced data processing examples. Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book.
Hadoop In Practice
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Author : Alex Holmes
language : en
Publisher: Manning
Release Date : 2012-10-13
Hadoop In Practice written by Alex Holmes and has been published by Manning this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-10-13 with Computers categories.
Summary Hadoop in Practice collects 85 Hadoop examples and presents them in a problem/solution format. Each technique addresses a specific task you'll face, like querying big data using Pig or writing a log file loader. You'll explore each problem step by step, learning both how to build and deploy that specific solution along with the thinking that went into its design. As you work through the tasks, you'll find yourself growing more comfortable with Hadoop and at home in the world of big data. About the Technology Hadoop is an open source MapReduce platform designed to query and analyze data distributed across large clusters. Especially effective for big data systems, Hadoop powers mission-critical software at Apple, eBay, LinkedIn, Yahoo, and Facebook. It offers developers handy ways to store, manage, and analyze data. About the Book Hadoop in Practice collects 85 battle-tested examples and presents them in a problem/solution format. It balances conceptual foundations with practical recipes for key problem areas like data ingress and egress, serialization, and LZO compression. You'll explore each technique step by step, learning how to build a specific solution along with the thinking that went into it. As a bonus, the book's examples create a well-structured and understandable codebase you can tweak to meet your own needs. This book assumes the reader knows the basics of Hadoop. Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book. What's Inside Conceptual overview of Hadoop and MapReduce 85 practical, tested techniques Real problems, real solutions How to integrate MapReduce and R Table of Contents PART 1 BACKGROUND AND FUNDAMENTALS Hadoop in a heartbeat PART 2 DATA LOGISTICS Moving data in and out of Hadoop Data serialization?working with text and beyond PART 3 BIG DATA PATTERNS Applying MapReduce patterns to big data Streamlining HDFS for big data Diagnosing and tuning performance problems PART 4 DATA SCIENCE Utilizing data structures and algorithms Integrating R and Hadoop for statistics and more Predictive analytics with Mahout PART 5 TAMING THE ELEPHANT Hacking with Hive Programming pipelines with Pig Crunch and other technologies Testing and debugging
Hadoop Application Architectures
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Author : Mark Grover
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2015-06-30
Hadoop Application Architectures written by Mark Grover and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-30 with Computers categories.
Get expert guidance on architecting end-to-end data management solutions with Apache Hadoop. While many sources explain how to use various components in the Hadoop ecosystem, this practical book takes you through architectural considerations necessary to tie those components together into a complete tailored application, based on your particular use case. To reinforce those lessons, the book’s second section provides detailed examples of architectures used in some of the most commonly found Hadoop applications. Whether you’re designing a new Hadoop application, or planning to integrate Hadoop into your existing data infrastructure, Hadoop Application Architectures will skillfully guide you through the process. This book covers: Factors to consider when using Hadoop to store and model data Best practices for moving data in and out of the system Data processing frameworks, including MapReduce, Spark, and Hive Common Hadoop processing patterns, such as removing duplicate records and using windowing analytics Giraph, GraphX, and other tools for large graph processing on Hadoop Using workflow orchestration and scheduling tools such as Apache Oozie Near-real-time stream processing with Apache Storm, Apache Spark Streaming, and Apache Flume Architecture examples for clickstream analysis, fraud detection, and data warehousing
Big Data Analytics With Hadoop 3
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Author : Sridhar Alla
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-05-31
Big Data Analytics With Hadoop 3 written by Sridhar Alla and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-31 with Computers categories.
Explore big data concepts, platforms, analytics, and their applications using the power of Hadoop 3 Key Features Learn Hadoop 3 to build effective big data analytics solutions on-premise and on cloud Integrate Hadoop with other big data tools such as R, Python, Apache Spark, and Apache Flink Exploit big data using Hadoop 3 with real-world examples Book Description Apache Hadoop is the most popular platform for big data processing, and can be combined with a host of other big data tools to build powerful analytics solutions. Big Data Analytics with Hadoop 3 shows you how to do just that, by providing insights into the software as well as its benefits with the help of practical examples. Once you have taken a tour of Hadoop 3’s latest features, you will get an overview of HDFS, MapReduce, and YARN, and how they enable faster, more efficient big data processing. You will then move on to learning how to integrate Hadoop with the open source tools, such as Python and R, to analyze and visualize data and perform statistical computing on big data. As you get acquainted with all this, you will explore how to use Hadoop 3 with Apache Spark and Apache Flink for real-time data analytics and stream processing. In addition to this, you will understand how to use Hadoop to build analytics solutions on the cloud and an end-to-end pipeline to perform big data analysis using practical use cases. By the end of this book, you will be well-versed with the analytical capabilities of the Hadoop ecosystem. You will be able to build powerful solutions to perform big data analytics and get insight effortlessly. What you will learn Explore the new features of Hadoop 3 along with HDFS, YARN, and MapReduce Get well-versed with the analytical capabilities of Hadoop ecosystem using practical examples Integrate Hadoop with R and Python for more efficient big data processing Learn to use Hadoop with Apache Spark and Apache Flink for real-time data analytics Set up a Hadoop cluster on AWS cloud Perform big data analytics on AWS using Elastic Map Reduce Who this book is for Big Data Analytics with Hadoop 3 is for you if you are looking to build high-performance analytics solutions for your enterprise or business using Hadoop 3’s powerful features, or you’re new to big data analytics. A basic understanding of the Java programming language is required.
Hadoop The Definitive Guide
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Author : Tom White
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2012-05-10
Hadoop The Definitive Guide written by Tom White and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-05-10 with Computers categories.
Ready to unlock the power of your data? With this comprehensive guide, you’ll learn how to build and maintain reliable, scalable, distributed systems with Apache Hadoop. This book is ideal for programmers looking to analyze datasets of any size, and for administrators who want to set up and run Hadoop clusters. You’ll find illuminating case studies that demonstrate how Hadoop is used to solve specific problems. This third edition covers recent changes to Hadoop, including material on the new MapReduce API, as well as MapReduce 2 and its more flexible execution model (YARN). Store large datasets with the Hadoop Distributed File System (HDFS) Run distributed computations with MapReduce Use Hadoop’s data and I/O building blocks for compression, data integrity, serialization (including Avro), and persistence Discover common pitfalls and advanced features for writing real-world MapReduce programs Design, build, and administer a dedicated Hadoop cluster—or run Hadoop in the cloud Load data from relational databases into HDFS, using Sqoop Perform large-scale data processing with the Pig query language Analyze datasets with Hive, Hadoop’s data warehousing system Take advantage of HBase for structured and semi-structured data, and ZooKeeper for building distributed systems
Professional Hadoop Solutions
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Author : Boris Lublinsky
language : en
Publisher: John Wiley & Sons
Release Date : 2013-09-12
Professional Hadoop Solutions written by Boris Lublinsky and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-09-12 with Computers categories.
The go-to guidebook for deploying Big Data solutions withHadoop Today's enterprise architects need to understand how the Hadoopframeworks and APIs fit together, and how they can be integrated todeliver real-world solutions. This book is a practical, detailedguide to building and implementing those solutions, with code-levelinstruction in the popular Wrox tradition. It covers storing datawith HDFS and Hbase, processing data with MapReduce, and automatingdata processing with Oozie. Hadoop security, running Hadoop withAmazon Web Services, best practices, and automating Hadoopprocesses in real time are also covered in depth. With in-depth code examples in Java and XML and the latest onrecent additions to the Hadoop ecosystem, this complete resourcealso covers the use of APIs, exposing their inner workings andallowing architects and developers to better leverage and customizethem. The ultimate guide for developers, designers, and architectswho need to build and deploy Hadoop applications Covers storing and processing data with various technologies,automating data processing, Hadoop security, and deliveringreal-time solutions Includes detailed, real-world examples and code-levelguidelines Explains when, why, and how to use these tools effectively Written by a team of Hadoop experts in theprogrammer-to-programmer Wrox style Professional Hadoop Solutions is the reference enterprisearchitects and developers need to maximize the power of Hadoop.
Practical Hadoop Migration
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Author : Bhushan Lakhe
language : en
Publisher: Apress
Release Date : 2016-08-10
Practical Hadoop Migration written by Bhushan Lakhe and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-10 with Computers categories.
Re-architect relational applications to NoSQL, integrate relational database management systems with the Hadoop ecosystem, and transform and migrate relational data to and from Hadoop components. This book covers the best-practice design approaches to re-architecting your relational applications and transforming your relational data to optimize concurrency, security, denormalization, and performance. Winner of IBM’s 2012 Gerstner Award for his implementation of big data and data warehouse initiatives and author of Practical Hadoop Security, author Bhushan Lakhe walks you through the entire transition process. First, he lays out the criteria for deciding what blend of re-architecting, migration, and integration between RDBMS and HDFS best meets your transition objectives. Then he demonstrates how to design your transition model. Lakhe proceeds to cover the selection criteria for ETL tools, the implementation steps for migration with SQOOP- and Flume-based data transfers, and transition optimization techniques for tuning partitions, scheduling aggregations, and redesigning ETL. Finally, he assesses the pros and cons of data lakes and Lambda architecture as integrative solutions and illustrates their implementation with real-world case studies. Hadoop/NoSQL solutions do not offer by default certain relational technology features such as role-based access control, locking for concurrent updates, and various tools for measuring and enhancing performance. Practical Hadoop Migration shows how to use open-source tools to emulate such relational functionalities in Hadoop ecosystem components. What You'll Learn Decide whether you should migrate your relational applications to big data technologies or integrate them Transition your relational applications to Hadoop/NoSQL platforms in terms of logical design and physical implementation Discover RDBMS-to-HDFS integration, data transformation, and optimization techniques Consider when to use Lambda architecture and data lake solutions Select and implement Hadoop-based components and applications to speed transition, optimize integrated performance, and emulate relational functionalities Who This Book Is For Database developers, database administrators, enterprise architects, Hadoop/NoSQL developers, and IT leaders. Its secondary readership is project and program managers and advanced students of database and management information systems.
Hadoop Operations
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Author : Eric Sammer
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2012-09-26
Hadoop Operations written by Eric Sammer and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-09-26 with Computers categories.
If you’ve been asked to maintain large and complex Hadoop clusters, this book is a must. Demand for operations-specific material has skyrocketed now that Hadoop is becoming the de facto standard for truly large-scale data processing in the data center. Eric Sammer, Principal Solution Architect at Cloudera, shows you the particulars of running Hadoop in production, from planning, installing, and configuring the system to providing ongoing maintenance. Rather than run through all possible scenarios, this pragmatic operations guide calls out what works, as demonstrated in critical deployments. Get a high-level overview of HDFS and MapReduce: why they exist and how they work Plan a Hadoop deployment, from hardware and OS selection to network requirements Learn setup and configuration details with a list of critical properties Manage resources by sharing a cluster across multiple groups Get a runbook of the most common cluster maintenance tasks Monitor Hadoop clusters—and learn troubleshooting with the help of real-world war stories Use basic tools and techniques to handle backup and catastrophic failure