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The Search Is Over: Integrating Solr and Hadoop in the Same Cluster to Simplify Big Data Analytics

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The Search Is Over: Integrating Solr and Hadoop in the Same Cluster to Simplify Big Data Analytics

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Companies like DataStax and MapR have found a significant demand for having technologies like Hadoop and Solr easily deployable in one cluster.  Jack Norris of MapR talks about this strategy in this video.

This session addresses the biggest issue facing Big Data – Search, Discovery and Analytics need to be integrated. While creating and maintaining separate SOLR and Hadoop clusters is time consuming, error prone and difficult to keep in synch, most Hadoop installations do not integrate with SOLR within the same cluster. Find out how to easily integrate these capabilities into a single cluster. The session will also touch on some of the technical aspects of Big Data Search including how to; protect against silent index corruption that permeates large distributed clusters, overcome the shard distribution problem by leveraging Hadoop to ensure accurate distributed search results, and provide real-time indexing for distributed search including support for streaming data capture. Srivas will also share relevant experiences from his days at Google where he ran one of the major search infrastructure teams where GFS, BigTable and MapReduce were used extensively.

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