Mars-on-Ray: Accelerating Large-scale Tensor and DataFrame Workloads

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Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions. Ray, which provides a general purpose task and actor API, is extremely expressive, and guarantees high performance for distributed Python applications. Mars-on-Ray takes advantage of both Mars and Ray; Mars provides familiar data science APIs, and highly optimized, locality-aware, fine-grained task scheduling, and now Mars-on-Ray allows Mars workloads to run on Ray with the same scheduling strategy, but has an extensive ability to scale on Ray clusters.