Sebastopol, CA—"Hadoop is the de facto platform for big data analysis," explains author Tom White (@tom_e_white). "The kernel is HDFS and MapReduce, but more interesting to most users is the very large ecosystem of tools and applications that run on top of this kernel. This book covers both the kernel and programs that are built on it, like Pig, Hive, and Sqoop."
In this third edition of Hadoop: The Definitive Guide (O'Reilly Media, $49.99 USD), you'll find illuminating case studies that demonstrate how Hadoop is used to solve specific problems. "Most chapters have been updated to cover new features or changes."
"And," White says, "the biggest change is the addition of material about MapReduce 2, and the new distributed resource management system it is built on, called YARN. Also, the new MapReduce API is now used for most examples.
In addition to finding out more about the new MapReduce API, as well as MapReduce 2 and its more flexible execution model (YARN), with Hadoop: The Definitive Guide you'll learn to:
- 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
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For more information about the book, including table of contents, author bios, and cover graphic, see: http://shop.oreilly.com/product/0636920021773.do
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