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Hadoop Beginner's Guide

You're reading from   Hadoop Beginner's Guide Get your mountain of data under control with Hadoop. This guide requires no prior knowledge of the software or cloud services ‚Äì just a willingness to learn the basics from this practical step-by-step tutorial.

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Product type Paperback
Published in Feb 2013
Publisher Packt
ISBN-13 9781849517300
Length 398 pages
Edition 1st Edition
Tools
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Toc

Table of Contents (19) Chapters Close

Hadoop Beginner's Guide
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. What It's All About 2. Getting Hadoop Up and Running FREE CHAPTER 3. Understanding MapReduce 4. Developing MapReduce Programs 5. Advanced MapReduce Techniques 6. When Things Break 7. Keeping Things Running 8. A Relational View on Data with Hive 9. Working with Relational Databases 10. Data Collection with Flume 11. Where to Go Next Pop Quiz Answers Index

Time for action – validating the table


The easiest way to do some initial validation is to perform some summary queries to validate the import. This is similar to the types of activities for which we used Hadoop Streaming in Chapter 4, Developing MapReduce Programs.

  1. Instead of using the Hive shell, pass the following HiveQL to the hive command-line tool to count the number of entries in the table:

    $ hive -e "select count(*) from ufodata;"
    

    You will receive the following response:

    Total MapReduce jobs = 1
    Launching Job 1 out of 1
    
    Hadoop job information for Stage-1: number of mappers: 1; number of reducers: 1
    2012-03-03 16:15:15,510 Stage-1 map = 0%,  reduce = 0%
    2012-03-03 16:15:21,552 Stage-1 map = 100%,  reduce = 0%
    2012-03-03 16:15:30,622 Stage-1 map = 100%,  reduce = 100%
    Ended Job = job_201202281524_0006
    MapReduce Jobs Launched: 
    Job 0: Map: 1  Reduce: 1   HDFS Read: 75416209 HDFS Write: 6 SUCESS
    Total MapReduce CPU Time Spent: 0 msec
    OK
    61393
    Time taken: 28.218 seconds
    
  2. Display a sample...

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