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Hadoop

Author: Garry Turkington; Tanmay Deshpande; Sandeep Karanth
Publisher: Birmingham : Packt Publishing, 2016.
Edition/Format:   eBook : Document : EnglishView all editions and formats
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Turkington, Garry
Hadoop: Data Processing and Modelling
Birmingham : Packt Publishing,c2016
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Garry Turkington; Tanmay Deshpande; Sandeep Karanth
ISBN: 9781787120457 1787120457
OCLC Number: 974588620
Notes: Description based upon print version of record.
Implementing a user-defined counter in a Map Reduce program
Description: 1 online resource (979 p.)
Contents: Cover ; Copyright; Credits; Preface; Table of Contents ; Module 1: Hadoop Beginner's Guide ; Chapter 1: What It's All About ; Big data processing; Cloud computing with Amazon Web Services; Summary; Chapter 2: Getting Hadoop Up and Running ; Hadoop on a local Ubuntu host; Using Elastic MapReduce; Comparison of local versus EMR Hadoop; Summary; Chapter 3: Understanding MapReduce ; Key/value pairs; The Hadoop Java API for MapReduce; Writing MapReduce programs; Walking through a run of WordCount; Hadoop-specific data types; Input/output; Summary; Chapter 4: Developing MapReduce Programs Using languages other than Java with HadoopAnalyzing a large dataset; Counters, status, and other output; Summary; Chapter 5: Advanced MapReduce Techniques ; Simple, advanced, and in-between; Joins; Graph algorithms; Using language-independent data structures; Summary; Chapter 6: When Things Break ; Failure; Summary; Chapter 7: Keeping Things Running ; A note on EMR; Hadoop configuration properties; Setting up a cluster; Cluster access control; Managing the NameNode; Managing HDFS; MapReduce management; Scaling; Summary; Chapter 8: A Relational View on Data with Hive ; Overview of Hive Setting up HiveUsing Hive; Hive on Amazon Web Services; Summary; Chapter 9: Working with Relational Databases ; Common data paths; Setting up MySQL; Getting data into Hadoop; Getting data out of Hadoop; AWS considerations; Summary; Chapter 10: Data Collection with Flume ; A note about AWS; Data data everywhere...; Introducing Apache Flume; The bigger picture; Summary; Chapter 11: Where to Go Next ; What we did and didn't cover in this book; Upcoming Hadoop changes; Alternative distributions; Other Apache projects; Other programming abstractions; AWS resources; Sources of information; Summary Appendix: Pop Quiz Answers Module 2: Hadoop Real-World Solutions Cookbook, Second Edition ; Chapter 1: Getting Started with Hadoop 2.X ; Introduction; Installing a single-node Hadoop Cluster; Installing a multi-node Hadoop cluster; Adding new nodes to existing Hadoop clusters; Executing the balancer command for uniform data distribution; Entering and exiting from the safe mode in a Hadoop cluster; Decommissioning DataNodes; Performing benchmarking on a Hadoop cluster; Chapter 2: Exploring HDFS ; Introduction; Loading data from a local machine to HDFS; Exporting HDFS data to a local machine Changing the replication factor of an existing file in HDFSSetting the HDFS block size for all the files in a cluster; Setting the HDFS block size for a specific file in a cluster; Enabling transparent encryption for HDFS; Importing data from another Hadoop cluster; Recycling deleted data from trash to HDFS; Saving compressed data in HDFS; Chapter 3: Mastering Map Reduce Programs ; Introduction; Writing the Map Reduce program in Java to analyze web log data; Executing the Map Reduce program in a Hadoop cluster; Adding support for a new writable data type in Hadoop

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