Storm is a real-time distributed computation system used to process massive streams of data. Many organizations are turning to technologies like Storm to complement batch-oriented big data technologies, such as Hadoop, to deliver time-sensitive analytics at scale.
This intermediate level session by Timothy Potter, Founder of Text Centrix, introduces an emerging architectural pattern of integrating Solr and Storm to process big data in real time. There are a number of natural integration points between Solr and Storm, such as populating a Solr index or supplying data to Storm using Solr’s real-time get support.
During the session, Timothy will cover the basic concepts of Storm, such as spouts and bolts. He’ll then provide examples of how to integrate Solr into Storm to perform large-scale indexing in near real-time. In addition, we’ll see how to embed Solr in a Storm bolt to match incoming tuples against pre-configured queries, commonly known as percolator. Attendees will come away from this presentation with a good introduction to stream processing technologies and several real-world use cases of how to integrate Solr with Storm.
This intermediate level session will take place from 10:15-11:00 on Wednesday, November 6. Click here for more details.
About the Speaker:
Timothy Potter (@thelabdude) is an independent consultant, specializing in search and big data technologies. Previously at the Dachis Group, Tim led the design and development of a number of mission-critical big data analytics projects using Solr, Hadoop, Pig, Hive, Mahout, and Storm. He was the chief architect, developer, and operations engineer for DG’s large-scale Solr 4 implementation including a 1TB index containing ~900M documents. Tim is the co-author of Solr In Action from Manning publishers and has worked extensively with Lucene and Solr technologies.
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