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Scaling Big Data with Hadoop and Solr, Second Edition

You're reading from   Scaling Big Data with Hadoop and Solr, Second Edition Understand, design, build, and optimize your big data search engine with Hadoop and Apache Solr

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Product type Paperback
Published in Apr 2015
Publisher
ISBN-13 9781783553396
Length 166 pages
Edition 1st Edition
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Author (1):
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 Vijay Karambelkar Vijay Karambelkar
Author Profile Icon Vijay Karambelkar
Vijay Karambelkar
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Scaling Solr through Storm


Apache Storm is a real time distributed computation framework. It processes humongous data in real time. Recently, Storm has been adapted by Apache as the incubating project and the development for Apache Storm. You can read more information about Apache Storm Features here: http://storm.incubator.apache.org/.

Apache Storm can be used to process massive streams of data in a distributed manner. It therefore provides excellent batch-oriented processing capabilities for time-sensitive analytics. With Apache Solr and Storm together, organizations can process big data in real time: for example, such industrial plants that would like to extract information from their plant system, which is emitting raw data continuously, and process it to facilitate real-time analytics such as identifying the top problematic systems or looking for recent errors/failures. Apache Solr and Storm can work together to execute such batch processing for big data in real time.

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