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Hadoop
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1. |  By: Garry Turkington; Publisher: Packt Publishing Publication Date: 22-FEB-2013 Insert Date: 27-FEB-2013 Slots: 1.0 | Overview: Hadoop Beginner's Guide
Learn how to crunch big data to extract meaning from the data avalanche
Learn tools and techniques that let you approach big data with relish and not fear
Shows how to build a complete infrastructure to handle your needs as your data grows
Hands-on examples in each chapter give the big picture while also giving direct experience
In Detail
Data is arriving faster than you can process it and the overall volumes keep growing at a rate that keeps you awake at night. Hadoop can help you tame the data beast. Effective use of Hadoop however requires a mixture of programming,...
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2. |  Hadoop Real-World Solutions Cookbook By: Jonathan R. Owens; Brian Femiano; Jon Lentz Publisher: Packt Publishing Publication Date: 07-FEB-2013 Insert Date: 11-FEB-2013 Slots: 1.0 | Overview: Hadoop Real-World Solutions Cookbook
Realistic, simple code examples to solve problems at scale with Hadoop and related technologies
Solutions to common problems when working in the Hadoop environment
Recipes for (un)loading data, analytics, and troubleshooting
In depth code examples demonstrating various analytic models, analytic solutions, and common best practices
In Detail
Helping developers become more comfortable and proficient with solving problems in the Hadoop space. People will become more familiar with a wide variety of Hadoop related tools and best practices for implementation.
Hadoop Real...
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3. |  By: Srinath Perera; Thilina Gunarathne Publisher: Packt Publishing Publication Date: 25-JAN-2013 Insert Date: 30-JAN-2013 Slots: 1.0 | Overview: Hadoop MapReduce Cookbook
Recipes for analyzing large and complex data sets with Hadoop MapReduce
Learn to process large and complex data sets, starting simply, then diving in deep
Solve complex big data problems such as classifications, finding relationships, online marketing and recommendations
More than 50 Hadoop MapReduce recipes, presented in a simple and straightforward manner, with step-by-step instructions and real world examples
In Detail
We are facing an avalanche of data. The unstructured data we gather can contain many insights that might hold the key to business success or failure....
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4. |  By: Alex Holmes Publisher: Manning Publications Publication Date: 28-OCT-2012 Insert Date: 09-NOV-2012 Slots: 1.0 | Overview: Hadoop in Practice 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...
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5. |  By: Edward Capriolo; Dean Wampler; Jason Rutherglen Publisher: O'Reilly Media, Inc. Publication Date: 26-SEP-2012 Insert Date: 19-SEP-2012 Slots: 1.0 | Overview: Programming Hive This comprehensive guide introduces you to Apache Hive, Hadoop’s data warehouse infrastructure. You’ll quickly learn how to use Hive’s SQL dialect—HiveQL—to summarize, query, and analyze large datasets stored in Hadoop’s distributed filesystem. This example-driven guide shows you how to set up and configure Hive in your environment, provides a detailed overview of Hadoop and MapReduce, and demonstrates how Hive works within the Hadoop ecosystem....
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6. |  By: Eric Sammer Publisher: O'Reilly Media, Inc. Publication Date: 10-OCT-2012 Insert Date: 09-MAY-2012 Slots: 1.0 | Overview: Hadoop Operations If you’ve been tasked with the job of maintaining large and complex Hadoop clusters, or are about to be, this book is a must. You’ll learn the particulars of Hadoop operations, from planning, installing, and configuring the system to providing ongoing maintenance....
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7. |  By: Chuck Lam Publisher: Manning Publications Publication Date: 15-DEC-2010 Insert Date: 26-FEB-2011 Slots: 1.0 | Overview: Hadoop in Action
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...
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8. |  Hadoop: The Definitive Guide, 2nd Edition By: Tom White Publisher: O'Reilly Media, Inc. Publication Date: 05-OCT-2010 Insert Date: 25-SEP-2010 Slots: 1.0 | Overview: Hadoop: The Definitive Guide, 2nd Edition Apache Hadoop is ideal for organizations with a growing need to store and process massive application datasets. With Hadoop: The Definitive Guide, programmers will find details for analyzing large datasets with Hadoop, and administrators will learn how to set up and run Hadoop clusters. The book includes case studies that illustrate how Hadoop is used to solve specific problems....
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9. |  By: Jason Venner Publisher: Apress Publication Date: 15-JUN-2009 Insert Date: 23-MAY-2010 Slots: 1.0 | Overview: Pro Hadoop
You learn the ins and outs of MapReduce; how to structure a cluster, design, and implement the Hadoop file system; and how to structure 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.
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10. |  By: Tom White Publisher: O'Reilly Media, Inc. Publication Date: 05-JUN-2009 Insert Date: 16-SEP-2008 Slots: 1.0 | Overview: Hadoop: The Definitive Guide Hadoop: The Definitive Guide helps you harness the power
of your data. Ideal for processing large datasets, the Apache
Hadoop framework is an open source implementation of the MapReduce
algorithm on which Google built its empire. This comprehensive
resource demonstrates how to use Hadoop to build reliable,
scalable, distributed systems: programmers will find details for
analyzing large datasets, and administrators will learn how to set
up and run Hadoop clusters.
Complete with case studies that illustrate how Hadoop solves
specific problems, this book helps you:
Use the Hadoop Distributed...
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