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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

Product type Paperback

Published in Apr 2015

Publisher

ISBN-13 9781783553396

Length 166 pages

Edition 1st Edition

Tools

Solr

Concepts

Big Data

Author (1):

Hrishikesh Vijay Karambelkar

View More author details

Table of Contents (8) Chapters

Preface

1. Processing Big Data Using Hadoop and MapReduce

2. Understanding Apache Solr FREE CHAPTER

3. Enabling Distributed Search using Apache Solr

4. Big Data Search Using Hadoop and Its Ecosystem

5. Scaling Search Performance

A. Use Cases for Big Data Search

Index

Chapter 4. Big Data Search Using Hadoop and Its Ecosystem

Sometime back, Gartner (http://www.gartner.com/newsroom/id/2304615) published an executive program survey report, which revealed that big data and analytics are among the top 10 business priorities for CIOs; similarly, analytics and BI are also at the top of CIO's Technical Priorities. Big data presents three major concerns for any organization: namely the storage of big data, data access or querying, and data analytics. Apache Hadoop provides an excellent implementation framework for the organizations looking to solve these problems. Similarly, there is other software that provides efficient storage and access to big data, such as Apache Cassandra and R Statistical. In this chapter, we will explore the possibilities of Apache Solr in working with big data.

We have already discussed a scaling search with SolrCloud in the previous chapters. In this chapter, we will be focusing on the following topics:

Understanding NoSQL...

The rest of the chapter is locked

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Authors (1)

Vijay Karambelkar

Vijay Karambelkar

Hrishikesh Vijay Karambelkar is an innovator and an enterprise architect with 16 years of software design and development experience, specifically in the areas of big data, enterprise search, data analytics, text mining, and databases. He is passionate about architecting new software implementations for the next generation of software solutions for various industries, including oil and gas, chemicals, manufacturing, utilities, healthcare, and government infrastructure. In the past, he has authored three books for Packt Publishing: two editions of Scaling Big Data with Hadoop and Solr and one of Scaling Apache Solr. He has also worked with graph databases, and some of his work has been published at international conferences such as VLDB and ICDE.

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