Hadoop : the definitive guide / Tom White
Material type:
TextPublisher: Sebastopol ; O'Reilly Media, 2015Edition: 4th edDescription: xxiii, 657 pages : illustrations ; 25 cmISBN: 9789352130672Subject(s): Apache -- Hadoop | File organization (Computer science)DDC classification: 005.74 | Item type | Current location | Call number | Status | Date due | Barcode |
|---|---|---|---|---|---|
| Books | Institute of Public Enterprise, Library S Campus | 005.74 WHI (Browse shelf) | Available | 46643 | |
| Books | Institute of Public Enterprise, Library S Campus | 005.74 WHI (Browse shelf) | Available | 46644 | |
| Books | Institute of Public Enterprise, Library S Campus | 005.74 WHI (Browse shelf) | Available | 46645 |
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| 005.74 SIL Database system concepts / | 005.74 SIL Database system concepts / | 005.74 SIL Database system concepts / | 005.74 WHI Hadoop : the definitive guide / | 005.74 WHI Hadoop : the definitive guide / | 005.74 WHI Hadoop : the definitive guide / | 005.74068 DHU Blockchain in e-governance: driving the next frontier in G2C services / |
Meet Hadoop
MapReduce
The Hadoop distributed filesystem
Hadoop I/O
Developing a MapReduce application
How MapReduce works
MapReduce types and formats
MapReduce features
Setting up a Hadoop cluster
Administering Hadoop
Pig
Hive
HBase
ZooKepper
Sqoop
Case studies
Installing Apache Hadoop
Cloudera's distribution including Apache Hadoop
Preparing the NCDC weather data
Get ready to unlock the power of your data. With the fourth edition of 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. Using Hadoop 2 exclusively, author Tom White presents new chapters on YARN and several Hadoop-related projects such as Parquet, Flume, Crunch, and Spark. You’ll learn about recent changes to Hadoop, and explore new case studies on Hadoop’s role in healthcare systems and genomics data processing. Learn fundamental components such as MapReduce, HDFS, and YARN Explore MapReduce in depth, including steps for developing applications with it Set up and maintain a Hadoop cluster running HDFS and MapReduce on YARN Learn two data formats: Avro for data serialization and Parquet for nested data Use data ingestion tools such as Flume (for streaming data) and Sqoop (for bulk data transfer) Understand how high-level data processing tools like Pig, Hive, Crunch, and Spark work with Hadoop Learn the HBase distributed database and the ZooKeeper distributed configuration service
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