Apache Solr is a code layer that covers Lucene which transforms it into a search platform for creating search applications. Solr features many capabilities that can spin a core search-capability into a fully fledged search applications. It lends users a chance to choose to work directly with underlying license library to explore and manipulate lower Lucene competencies.
Solr puts Lucene on top of http, allowing to be written in any language to invoke it Lucene. It leverages XML-based schemes to manage a host of indexed-fields and their varied characteristics. Solr enables a large-scale distributed search with fixed/paid result list placement.
Solr leverages the end-users with an array of advantages. The following are few:
Speed - Solr works entirely on Java and performs at a sub-second for most queries to deliver results, enhancing organizational efficiency.
Complete query capability - The search technology encompasses everything from spell-checking proximity operators to enabling multi-lingual search.
Holistic results - Solr performs a full-result processing that includes relevancy-sorting, sorting using date or any given field and also dynamic summaries.
Probability - It run on just about any platform that is compatible with Java. What's more, its indexes are portable across platforms too.
Creating a holistic full text search is a much demanding undertaking. Owning the best technology would only help solve half the solution. Search engines like Solr have such a superior default settings to aid apps to not just work, but work effectively. The architecture of the best search engines require a thorough understanding of both, the data and users. The data must be aggregated and indexed from the file systems, databases and websites.
The competency to build an ideal search engines comes from the expertise of building and setting other ones. Search engine developers should always be on the lookout for experienced resources to aid application design, development and deployment.