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It seems to me that the Spark model is much more sensible in terms of performance. In Spark, individual tasks are finally compiled into optimized Java code. As I understand Dusk works, a separate Python process is run for each data subset. So because of this architecture, Dusk is unlikely to ever get Spark performance. By the way, both systems build and optimize the operation graph. This is confirmed by benchmarks: https://h2oai.github.io/db-benchmark/
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