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SpringOne2GX 2014 Replay: Building a Recommendation Engine with Spring and Hadoop

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SpringOne2GX 2014 Replay: Building a Recommendation Engine with Spring and Hadoop

· Java Zone
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In the complimentary O’Reilly eBook, Migrating to Cloud-Native Application Architectures, Pivotal’s Matt Stine examines the cultural, organizational, and technical changes necessary to migrate traditional monolithic applications and service-oriented architectures to cloud-native architectures.

Recorded at SpringOne2GX 2014.

Speaker: Michael Minella

Big Data Track

Slides: http://www.slideshare.net/SpringCentral/building-a-recommendation-engine-with-spring-and-hadoop

The Amazon’s and Google’s of the world have had Ph.D.’s locked up in back rooms for years creating algorithms to get you to click on things and subsequently buy stuff. One of the big things that those smart people have been working on are recommendation engines. Today, a recommendation engine isn’t something that only the Amazon’s of the world can have. With an hour, and a handful of open source tools, we’ll build a recommendation engine based on the data from the website we probably spend the most time on…StackOverflow. We’ll use Spring XD and Spring Batch to orchestrate the full lifecycle of Hadoop processing (ingest, process, export) and use Apache Mahout to provide us with the recommendation processing. A basic understanding of Hadoop concepts (what Map/Reduce is) and Spring (basic D/I configuration) is expected for this talk.

Learn more about Spring Batch: http://projects.spring.io/spring-batch

In this complimentary eBook, you will find a migration cookbook, with recipes for decomposing monolithic applications into microservices, implementing fault-tolerant patterns, and performing automated testing of cloud-native services.

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Published at DZone with permission of Pieter Humphrey, DZone MVB. See the original article here.

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