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Scaling Apache Solr

You're reading from   Scaling Apache Solr Optimize your searches using high-performance enterprise search repositories with Apache Solr

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Product type Paperback
Published in Jul 2014
Publisher
ISBN-13 9781783981748
Length 298 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
LinkedIn
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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Table of Contents (13) Chapters Close

Preface 1. Understanding Apache Solr FREE CHAPTER 2. Getting Started with Apache Solr 3. Analyzing Data with Apache Solr 4. Designing Enterprise Search 5. Integrating Apache Solr 6. Distributed Search Using Apache Solr 7. Scaling Solr through Sharding, Fault Tolerance, and Integration 8. Scaling Solr through High Performance 9. Solr and Cloud Computing 10. Scaling Solr Capabilities with Big Data A. Sample Configuration for Apache Solr Index

Summary

In this chapter, we focused mainly on working with big databases that work on large datasets for processing and how Apache Solr can add value to them. We also looked at some of the implementations to integrate Apache Solr with MongoDB, Apache Cassandra, and Apache Storm. We also looked at some of the advanced topics such as clustering the outcomes/results from Apache Solr using Carrot2. In the next chapter, we will be focusing on optimizing Apache Solr for high performance.

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Authors (1)

Profile icon Vijay Karambelkar
Vijay Karambelkar
LinkedIn icon
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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