Apache Solr as your Search and Suggest Engine
Do you require a search and suggest engine that could scale up catering to millions of records? This session render a real world project experience of using Solr as a search engine delimiting what could you really expect out of Solr. This session on Apache Solr as your Search and Suggest Engine was presented at 6th Annual IndicThreads.com Conference On Java, December 2011, Pune, India.
This case study shall focus on the following points:
- Why choose Solr as your search engine : What lured us to go for Solr
- Solr offers various configurations and components to build a Google style Suggestions engine – Elicit pros and limiting factors of these components and highlight when to use which component.
- Fuzzy Searching with Solr – I want to search ‘Karan’ but I type ‘Naran’ yet Solr finds it. – Analyse what fuzzy searching can do for you and to what extent should you stretch your engine’s fuzzy search quotient.
- Discuss Solr scaling topology – Point out what factors should you consider while scaling Solr
- Unit testing Solr code
Speaker
Karan Nangru is a Senior Consultant at Xebia IT Architects. He is a J2EE practitioner and a RIA, Cloud Computing enthusiast. He writes articles and blogs on technology and agile, has been a cover page author twice for a renowned RIA magazine. Off late, he has been working on technologies such Gigaspaces, SOLR, JavaFX. He often speaks in conferences and knowledge sharing sessions on Technology and Agile.
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