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  • Book Overview & Buying Scaling Big Data with Hadoop and Solr, Second Edition
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Scaling Big Data with Hadoop and Solr, Second Edition

Scaling Big Data with Hadoop and Solr, Second Edition

By : Vijay Karambelkar
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Scaling Big Data with Hadoop and Solr, Second Edition

Scaling Big Data with Hadoop and Solr, Second Edition

3 (4)
By: Vijay Karambelkar

Overview of this book

This book is aimed at developers, designers, and architects who would like to build big data enterprise search solutions for their customers or organizations. No prior knowledge of Apache Hadoop and Apache Solr/Lucene technologies is required.
Table of Contents (8 chapters)
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7
Index

Chapter 3. Enabling Distributed Search using Apache Solr

With the growth of data for searching, it becomes necessary to scale up the performance of search applications, to cater to the increasing needs of indexing and searching quickly over large datasets. Distributed search can be used when a single index store becomes difficult to operate in terms of its size (large to fit in memory or disk). As more number of users start using enterprise search, single node searches have limitations in terms of response time and parallel sessions for users. For smaller data sizes, standalone search architecture performs better compared to distributed searches, due to single index availability. However, with the growth in the data size, its performance degrades eventually. The Distributed Search application increases the operation and maintenance cost. It also increases the complexity of overall landscape. However, with the scaling of information for searching, distributed search is the way...

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