Pro Apache Hadoop, 2/e (Paperback)
內容描述
Pro 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 What you’ll learn Build a resilient and scalable Hadoop compute cluster. Analyze large volumes of data in amazingly short time. Optimize Hadoop tasks like a seasoned professional. Implement bulletproof patterns that are proven successful. Scale out using the new HDFS Federations feature set. Chunk large problems into highly-parallel, MapReduce modules Who this book is for This book is aimed at I.T. professionals investigating Hadoop and implementing it in their organizations. Existing Hadoop users will deepen their toolkits and come up to speed on what’s new Hadoop 2.0. New Hadoop users will quickly move to the seasoned professional level in their use of the toolset. Table of Contents1. Motivation for Big Data2. Hadoop Concepts3. Getting Started with the Hadoop Framework4. Hadoop Administration5. Basics of MapReduce Development6. Advanced MapReduce Development7. Hadoop Input Output8. Testing Hadoop Programs 9. Monitoring Hadoop10. Data Warehousing using Hadoop11. Data Processing using Pig 12. HCatalog and Hadoop in the Enterprise13. Log Analysis using Hadoop14. Building Real-Time Systems using HBase15. Data Science With Hadoop16. Hadoop in the Cloud17. Building a YARN Application18. Appendix A19. Appendix B20. Appendix C
