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Scala seems to be, suddenly, an important language within the Apache Hadoop ecosystem, with the arrival of Scala-based projects like Apache Kafka and Apache Spark -- which is in essence "distributed Scala". In fact, it's not a surprising marriage: Hadoop has been building on functional paradigms and immutability in its way for years through MapReduce/HDFS, and projects like Crunch and Cascading. This talk will give a Hadoop-centric take on the evolution of Scala, its benefits to Hadoop-related projects, why it succeeds where other languages don't in Hadoop, and some quirks that remain barriers to its further adoption in "big data".
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Sean is Director of Data Science at Cloudera in London. Before Cloudera, he founded Myrrix Ltd (now, the Oryx project) to commercialize large-scale real-time recommender systems on Apache Hadoop. He is an Apache Spark committer and co-authored Advanced Analytics on Spark. He was a committer and VP for Apache Mahout, and co-author of Mahout in Action. Previously, Sean was a senior engineer at Google.