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Scientists today have the ability to generate data at an unprecedented scale and rate and, as a result, they must increasingly turn to parallel data processing engines to perform their analyses. However, the simple execution model of these engines can make it difficult to implement efficient algorithms for scientific analytics. In particular, many scientific analytics require the extraction of features from data represented as either a multidimensional array or points in a multidimensionaldoi:10.1145/1807128.1807140 dblp:conf/cloud/KwonBHR10 fatcat:uycukwm6ebdlhffywcv7ypzdjy