Many enterprise search applications consolidate data from various data sources. Each separate system may also use a different method of data organization and/or format. To use Apache Solr effectively in these systems, all the important data that is to be searched must be fed to the Solr engine, and it goes through a complete process chain (which is explained in brief in Chapter 1, Understanding Apache Solr). Interestingly, since this data is fed only to generate indexing, we do not really have to worry about the formatting, and other presentation aspects of this data. However, if the expectation from enterprise search engines is also to provide an excellent browsing experience, each data element should carry structure information. This information is extracted by Apache Solr and is used to provide further dimensional navigation for a better user experience, that is, facets.
Scaling Apache Solr
By :
Scaling Apache Solr
By:
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