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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 – making a partitioned UFO sighting table


We will create a new table for the UFO data to demonstrate the usefulness of partitioning.

  1. Save the following query as createpartition.hql:

    CREATE TABLE partufo(sighted string, reported string, sighting_location string,shape string, duration string, description string) 
    PARTITIONED BY (year string)
    ROW FORMAT DELIMITED
    FIELDS TERMINATED BY '\t' ;
  2. Save the following query as insertpartition.hql:

    SET hive.exec.dynamic.partition=true ;
    SET hive.exec.dynamic.partition.mode=nonstrict ;
    
    INSERT OVERWRITE TABLE partufo partition (year)
    SELECT sighted, reported, sighting_location, shape, duration, description,
    SUBSTR(TRIM(sighted), 1,4)  FROM ufodata ;
  3. Create the partitioned table:

    $ hive -f createpartition.hql 
    

    You will receive the following response:

    Logging initialized using configuration in jar:file:/opt/hive-0.8.1/lib/hive-common-0.8.1.jar!/hive-log4j.properties
    Hive history file=/tmp/hadoop/hive_job_log_hadoop_201203101838_17331656.txt
    OK...
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