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

Managing HDFS


As we saw when killing and restarting nodes in Chapter 6, When Things Break, Hadoop automatically manages many of the availability concerns that would consume a lot of effort on a more traditional filesystem. There are some things, however, that we still need to be aware of.

Where to write data

Just as the NameNode can have multiple locations for storage of fsimage specified via the dfs.name.dir property, we explored earlier that there is a similar-appearing property called dfs.data.dir that allows HDFS to use multiple data locations on a host, which we will look at now.

This is a useful mechanism that works very differently from the NameNode property. If multiple directories are specified in dfs.data.dir, Hadoop will view these as a series of independent locations that it can use in parallel. This is useful if you have multiple physical disks or other storage devices mounted at distinct points on the filesystem. Hadoop will use these multiple devices intelligently, maximizing...