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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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Hrishikesh Vijay Karambelkar Hrishikesh Vijay Karambelkar
Author Profile Icon Hrishikesh Vijay Karambelkar
Hrishikesh Vijay Karambelkar
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Chapter 2. Understanding Apache Solr

In the previous chapter, we discussed how big data has evolved to cater to the needs of various organizations, in order to deal with a humongous data size. There are many other challenges while working with data of different shapes. For example, the log files of any application server have semi-structured data or Microsoft Word documents, making it difficult to store the data in traditional relational storage. The challenge to handling such data is not just related to storage: there is also the big question of how to access the required information. Enterprise search engines are designed to address this problem.

Today, finding the required information within a specified timeframe has become more crucial than ever. Enterprises without information retrieval capabilities suffer from problems such as lost productivity of employees, poor decisions based on faulty/incomplete information, duplicated efforts, and so on. Given these scenarios, it is...

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Scaling Big Data with Hadoop and Solr, Second Edition
Published in: Apr 2015
Publisher:
ISBN-13: 9781783553396
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