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

Chapter 9. Working with Relational Databases

As we saw in the previous chapter, Hive is a great tool that provides a relational database-like view of the data stored in Hadoop. However, at the end of the day, it is not truly a relational database. It does not fully implement the SQL standard, and its performance and scale characteristics are vastly different (not better or worse, just different) from a traditional relational database.

In many cases, you will find a Hadoop cluster sitting alongside and used with (not instead of) relational databases. Often the business flows will require data to be moved from one store to the other; we will now explore such integration.

In this chapter, we will:

  • Identify some common Hadoop/RDBMS use cases

  • Explore how we can move data from RDBMS into HDFS and Hive

  • Use Sqoop as a better solution for such problems

  • Move data with exports from Hadoop into an RDBMS

  • Wrap up with a discussion of how this can be applied to AWS