Monday 15th June, 2015
3:30pm to 4:00pm
As more organizations seek to leverage Spark for big data analytics and machine learning, the need for seamless integration between Spark and Solr emerges. In this presentation, Timothy Potter covers how to populate Solr from a Spark streaming job as well as how to expose the results of any Solr query as an RDD. Attendees will come away with a solid understanding of common use cases, access to open source code, and performance metrics to help them develop their own large-scale search and discovery solution with Spark and Solr.
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