Book Image

Hadoop Beginner's Guide

Book Image

Hadoop Beginner's Guide

Overview of this book

Data is arriving faster than you can process it and the overall volumes keep growing at a rate that keeps you awake at night. Hadoop can help you tame the data beast. Effective use of Hadoop however requires a mixture of programming, design, and system administration skills."Hadoop Beginner's Guide" removes the mystery from Hadoop, presenting Hadoop and related technologies with a focus on building working systems and getting the job done, using cloud services to do so when it makes sense. From basic concepts and initial setup through developing applications and keeping the system running as the data grows, the book gives the understanding needed to effectively use Hadoop to solve real world problems.Starting with the basics of installing and configuring Hadoop, the book explains how to develop applications, maintain the system, and how to use additional products to integrate with other systems.While learning different ways to develop applications to run on Hadoop the book also covers tools such as Hive, Sqoop, and Flume that show how Hadoop can be integrated with relational databases and log collection.In addition to examples on Hadoop clusters on Ubuntu uses of cloud services such as Amazon, EC2 and Elastic MapReduce are covered.
Table of Contents (19 chapters)
Hadoop Beginner's Guide
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Time for action – importing data from a raw query


Let's see an example of an import where a raw SQL statement is used to select the data to be imported.

  1. Delete any existing output directory:

    $ hadoop fs –rmr employees
    
  2. Drop any existing Hive employee table:

    $ hive -e 'drop table employees'
    
  3. Import data using an explicit query:

    sqoop import --connect jdbc:mysql://10.0.0.100/hadooptest 
    --username hadoopuser -P
    --target-dir employees  
    --query 'select first_name, dept, salary, 
    timestamp(start_date) as start_date from employees where $CONDITIONS' 
    --hive-import --hive-table employees 
    --map-column-hive start_date=timestamp -m 1
    
  4. Examine the created table:

    $ hive -e "describe employees"
    

    You will receive the following response:

    OK
    first_name  string  
    dept  string  
    salary  int  
    start_date  timestamp  
    Time taken: 2.591 seconds
    
  5. Examine the data:

    $ hive -e "select * from employees"
    

    You will receive the following response:

    OK
    Alice  Engineering  50000  2009-03-12 00:00:00
    BobSales  35000  2011-10...