In the last chapter, we looked at how effectively Apache Solr can be used with advanced capabilities. Apache Solr can work on low-cost hardware, thereby making it a strong candidate for adaption at various organizations looking at cutting costs. Besides cutting costs, an important aspect of any enterprise search implementation is to get optimal performance out of the existing hardware and search infrastructure. This is one of the challenging domains, because with the inflow of more and more data, the search indexing as well as real-time search on these indexes slows down. In such cases, the need for distributed instances comes into the frame. At the same time, the unit of performance does not scale linearly with the number of CPU cores or memory; hence, at times, even if you increase the memory after certain limits, the performance does not improve. Therefore, it makes sense to optimize the Solr instance for high performance to ensure maximum...
Scaling Apache Solr
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Scaling Apache Solr
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Overview of this book
Table of Contents (18 chapters)
Scaling Apache Solr
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Free Chapter
Understanding Apache Solr
Getting Started with Apache Solr
Analyzing Data with Apache Solr
Designing Enterprise Search
Integrating Apache Solr
Distributed Search Using Apache Solr
Scaling Solr through Sharding, Fault Tolerance, and Integration
Scaling Solr through High Performance
Solr and Cloud Computing
Scaling Solr Capabilities with Big Data
Sample Configuration for Apache Solr
Index
Customer Reviews