As we countdown to the annual Lucene/Solr Revolution conference in Boston this October, we’re highlighting talks and sessions from past conferences. Today, we’re highlighting Joel Bernstein’s session about Parallel Computing in SolrCloud.

This presentation provides a deep dive into SolrCloud’s parallel computing capabilities – breaking down the framework into four main areas: shuffling, worker collections, the Streaming API, and Streaming Expressions. The talk describes how each of these technologies work individually and how they interact with each other to provide a general purpose parallel computing framework.

Also included is a discussion of some of the core use cases for the parallel computing framework. Use cases involving real-time map reduce, parallel relational algebra, and streaming analytics will be covered.

Joel Bernstein is a Solr committer and search engineer for the open source ECM company Alfresco.

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