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Mastering Hadoop

You're reading from   Mastering Hadoop Go beyond the basics and master the next generation of Hadoop data processing platforms

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Product type Paperback
Published in Dec 2014
Publisher
ISBN-13 9781783983643
Length 374 pages
Edition 1st Edition
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Author (1):
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Sandeep Karanth Sandeep Karanth
Author Profile Icon Sandeep Karanth
Sandeep Karanth
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Table of Contents (15) Chapters Close

Preface 1. Hadoop 2.X FREE CHAPTER 2. Advanced MapReduce 3. Advanced Pig 4. Advanced Hive 5. Serialization and Hadoop I/O 6. YARN – Bringing Other Paradigms to Hadoop 7. Storm on YARN – Low Latency Processing in Hadoop 8. Hadoop on the Cloud 9. HDFS Replacements 10. HDFS Federation 11. Hadoop Security 12. Analytics Using Hadoop A. Hadoop for Microsoft Windows Index

Apache Storm


Apache Storm is one of the most popular open source streaming engines and provides real-time analytics on unbounded streams of data. It is a distributed framework that can work on multiple nodes, providing both fault tolerance and horizontal scalability. Another primary feature of Apache Storm is that it provides guaranteed event processing, that is, every event that enters the system is processed without a loss of events. Apache Storm applications can be deployed with any programming language of the developer's choice, making it extremely attractive for usage in low-latency analytics.

MapReduce provides the Map and Reduce function primitives to build batch applications. Similarly, Storm provides its own set of primitives to support real-time analytics. If a framework such as Apache Storm is not available, writing real-time applications will mean a lot of complexity. It will involve adding and maintaining processing queues to guarantee processing of all events in the system....

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