Title: Apache Flume : Distributed Log Collection for Hadoop
Publisher: Packt Publishing
Publication Date: 2013
Language: English
ISBN 10: 1782167919
ISBN 13: 9781782167914
Binding: Taschenbuch
Condition: Neu
Dimensions: 235 millimeters width by 191 millimeters height by 7 millimeters depth
Weight: 219 grams

About this title

Synopsis

If your role includes moving datasets into Hadoop, this book will help you do it more efficiently using Apache Flume. From installation to customization, it's a complete step-by-step guide on making the service work for you.

Overview

Integrate Flume with your data sources
Transcode your data en-route in Flume
Route and separate your data using regular expression matching
Configure failover paths and load-balancing to remove single points of failure
Utilize Gzip Compression for files written to HDFS

In Detail

Apache Flume is a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large amounts of log data. Its main goal is to deliver data from applications to Apache Hadoop's HDFS. It has a simple and flexible architecture based on streaming data flows. It is robust and fault tolerant with many failover and recovery mechanisms.

Apache Flume: Distributed Log Collection for Hadoop covers problems with HDFS and streaming data/logs, and how Flume can resolve these problems. This book explains the generalized architecture of Flume, which includes moving data to/from databases, NO-SQL-ish data stores, as well as optimizing performance. This book includes real-world scenarios on Flume implementation.

Apache Flume: Distributed Log Collection for Hadoop starts with an architectural overview of Flume and then discusses each component in detail. It guides you through the complete installation process and compilation of Flume.

It will give you a heads-up on how to use channels and channel selectors. For each architectural component (Sources, Channels, Sinks, Channel Processors, Sink Groups, and so on) the various implementations will be covered in detail along with configuration options. You can use it to customize Flume to your specific needs. There are pointers given on writing custom implementations as well that would help you learn and implement them.

By the end, you should be able to construct a series of Flume agents to transport your streaming data and logs from your systems into Hadoop in near real time.

What you will learn from this book

Understand the Flume architecture
Download and install open source Flume from Apache
Discover when to use a memory or file-backed channel
Understand and configure the Hadoop File System (HDFS) sink
Learn how to use sink groups to create redundant data flows
Configure and use various sources for ingesting data
Inspect data records and route to different or multiple destinations based on payload content
Transform data en-route to Hadoop
Monitor your data flows

Approach

A starter guide that covers Apache Flume in detail.

Who this book is written for

Apache Flume: Distributed Log Collection for Hadoop is intended for people who are responsible for moving datasets into Hadoop in a timely and reliable manner like software engineers, database administrators, and data warehouse administrators.

About the Author

Steve Hoffman

Steve Hoffman has 30 years of software development experience and holds a B.S. in computer engineering from the University of Illinois Urbana-Champaign and a M.S. in computer science from the DePaul University. He is currently a Principal Engineer at Orbitz Worldwide.

More information on Steve can be found at http://bit.ly/bacoboy or on Twitter @bacoboy.

This is Steve's first book.

"About this title" may belong to another edition of this title.

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