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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
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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

Searching Solr documents in near real time


Apache Solr performs indexing on the updated data, and the data is available for search. In many cases, the index-generation job is run during offline hours (late nights, weekends) to update the search with the newer data. Until this point, Apache Solr cannot search for documents added in the customer document repository. Many times, the demand is to make a document available for search as and when it is uploaded to the customer repository. Apache Solr can perform search on these documents in near real time. There is a delay to generate index for a document and to make it available for search; hence, Apache Solr can support near real-time search on documents.

Strategies for near real-time search in Apache Solr

In Apache Solr, a commit operation is required to enable the document to be made available for searching. Commit operation in Apache Solr involves Solr access transaction logs (or update logs), which pick the identifiers and sync the index files...

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