Experimenting with Distributed Data Processing in Haskell

Explore distributed data processing in Haskell through this 22-minute conference talk from YOW! 2019. Dive into the world of functional programming for large-scale data processing as Utku Demir, a Software Engineer at Movio, introduces the 'distributed-dataset' framework. Learn how Haskell's features like purity, higher-order functions, and laziness can be leveraged for efficient data processing across multiple machines. Discover the advantages of using Haskell in this domain, compare it to popular frameworks like Apache Spark, and gain insights into key implementation ideas. Get a brief introduction to the library and understand how the StaticPointers extension of GHC Haskell enables distributed computation. Ideal for developers interested in functional programming, distributed systems, and data processing at scale.