In the Lucene/Solr Revolution session, “High Performance JSON Search and Relational Faceted Browsing with Lucene,” Renaud Delbru, Co-Founder of SindiceTech, will discuss how Lucene and Solr can be used for very efficient search of tree-shaped schemaless documents, e.g. JSON or XML, and can be then made to address both graph and relational data search. He will discuss the capabilities of SIREn, a Lucene/Solr plugin they have developed to deal with huge collections of tree-shaped schemaless documents, and how SIREn is built using Lucene extensibility capabilities (Analysis, Codec, Flexible Query Parser). He will compare it with Lucene’s BlockJoin Query API in nested schemaless data intensive scenarios. He will then go through use cases that show how relational or graph data can be turned into JSON documents using Hadoop and Pig, and how this can be used in conjunction with SIREn to create relational faceting systems with unprecedented performance.

Take-away lessons from this session will be awareness about using Lucene/Solr and Hadoop for relational and graph data search, as well as the awareness that it is now possible to have relational faceted browsers with sub-second response time on commodity hardware.

This advanced level session will take place from 11:55-12:40 on Thursday, November 7. Click here for more details.

About the Speaker:

Renaud Delbru is a co-founder of SindiceTech, a company that provides knowledge graph technologies to enterprises. He is also a researcher at the National University of Ireland, Galway. His activities focus around Semantic Web, Information Retrieval, and Large Scale Data Integration scenarios. He has published over a dozen papers and was a speaker at several conferences in these areas. He has been working with Lucene and Solr for six years, developing – the largest search engine for the semantic web – and SIREn the Semantic Information Retrieval Engine.

More Details:

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Lucene/Solr Revolution is presented by Lucidworks, the commercial entity for Apache Lucene/Solr open source search — the future of search technology.

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