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And yet it was written in Scala. That shows how little the compile times offset the goodies of using Scala.


At the time Spark was started, Java didn't have lambdas or closures, making the equivalent Java code for functional-programming-style ML code much more verbose. Whether the same decision would be made today is an open question (and probably depends on who you ask). A lot of other frameworks have made different decisions, such as keeping the core of the project in Java and supporting other languages as shims on top (in my opinion a more sensible decision...)




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