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Tuesday, August 18 • 2:50pm - 3:10pm
Large volume data analysis on the Typesafe Reactive Platform

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This talk focuses on processing of large volumes of data on Typesafe platform using Scala, Akka, Reactive Streams and Spark, mainly to utilise machine learning algorithms in parallel or distributed environment. It aims to explain different parallel and distributed programming models, use cases, developer considerations, internals and important ideas and concepts behind mentioned frameworks in developer level detail. Focuses on usability of the mentioned approaches for machine learning pipelines and efficient and scalable analytics over large amounts of data. It also demonstrates usage of mentioned principles on a large scale sensor event processing application use case from practice (using Scala, Akka Cluster, Reactive Streams, CQRS, event sourcing, Spark, machine learning and more). NOTE: Similar talk submitted for SBTB. This talk would concentrate more on the Big Data, ML and how Scala and the Typesafe technologies fit these use cases.

Speakers
avatar for Martin Zapletal

Martin Zapletal

Cake Solutions
Martin Zapletal is heading up the technical team of Cake Solutions Inc. in New York. Martin specialises in the design and implementation of reactive, scalable, resilient distributed systems, machine learning and working with large amounts of data. He also has background in functional programming and promotes the use of functional languages, mainly Scala, and patterns in enterprise level production systems.


Tuesday August 18, 2015 2:50pm - 3:10pm
Track A

Attendees (17)