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Building a Recommendation Engine with Spring and Hadoop

Michael Minella (Pivotal)
Java & JVM
D136
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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.

Photo of Michael Minella

Michael Minella

Pivotal

Michael Minella is a software engineer, teacher and author with over a decade of enterprise development experience. Michael was a member of the expert group for JSR-352 (java batch processing). He currently works for Pivotal as the project lead for the Spring Batch project as well as an instructor at DePaul University. Michael is the author of Pro Spring Batch from Apress and the popular Refcard JUnit and EasyMock.

Outside of the daily grind, Michael enjoys spending time with his family and enjoys woodworking, photography, and InfoSec as hobbies.

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