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OverviewPro Apache Hadoop, Second Edition brings you up to speed on Hadoop – the framework of big data. Revised to cover Hadoop 2.0, the book covers the very latest developments such as YARN (aka MapReduce 2.0), new HDFS high-availability features, and increased scalability in the form of HDFS Federations. All the old content has been revised too, giving the latest on the ins and outs of MapReduce, cluster design, the Hadoop Distributed File System, and more. This book covers everything you need to build your first Hadoop cluster and begin analyzing and deriving value from your business and scientific data. Learn to solve big-data problems the MapReduce way, by breaking a big problem into chunks and creating small-scale solutions that can be flung across thousands upon thousands of nodes to analyze large data volumes in a short amount of wall-clock time. 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. Covers all that is new in Hadoop 2.0 Written by a professional involved in Hadoop since day one Takes you quickly to the seasoned pro level on the hottest cloud-computing framework Full Product DetailsAuthor: Jason Venner , Sameer Wadkar , Madhu SiddalingaiahPublisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG Imprint: APress Edition: 2nd ed. Dimensions: Width: 17.80cm , Height: 2.30cm , Length: 25.40cm Weight: 8.218kg ISBN: 9781430248637ISBN 10: 1430248637 Pages: 444 Publication Date: 09 September 2014 Audience: Professional and scholarly , Professional & Vocational Format: Paperback Publisher's Status: Active Availability: Manufactured on demand ![]() We will order this item for you from a manufactured on demand supplier. Table of Contents1. Motivation for Big Data 2. Hadoop Concepts 3. Getting Started with the Hadoop Framework 4. Hadoop Administration 5. Basics of MapReduce Development 6. Advanced MapReduce Development 7. Hadoop Input Output 8. Testing Hadoop Programs 9. Monitoring Hadoop 10. Data Warehousing using Hadoop 11. Data Processing using Pig 12. HCatalog and Hadoop in the Enterprise 13. Log Analysis using Hadoop 14. Building Real-Time Systems using HBase 15. Data Science With Hadoop 16. Hadoop in the Cloud 17. Building a YARN Application 18. Appendix A 19. Appendix B 20. Appendix CReviewsAuthor InformationJason Venner has more than 20 years of software engineering, managing, designing, and coding experience. He has been a vice president, director, and consultant. Currently, his interests and expertise are in Java, Hadoop, cloud computing, and more. For more, visit www.prohadoopbook.com. Tab Content 6Author Website:Countries AvailableAll regions |