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

The bigger picture


It's important to realize that "simply" getting data from one point to another is rarely the extent of your data considerations. Terms such as data lifecycle management have become widely used recently for good reason. Let's briefly look at some things to consider, ideally before you have the data flooding across the system.

Data lifecycle

The main question to be asked in terms of data lifecycle is for how long will the value you gain from data storage be greater than the storage costs. Keeping data forever may seem attractive but the costs of holding more and more data will increase over time. These costs are not just financial; many systems see their performance degrade as volumes increase.

This question isn't—or at least rarely should be—decided by technical factors. Instead, you need the value and costs to the business to be the driving factors. Sometimes data becomes worthless very quickly, other times the business cannot delete it for either competitive or legal reasons...