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Symmetric and Asymmetric Aggregate Function in Massively Parallel Computing

Abstract : Applications of aggregation for information summary have great meanings in various fields. In big data era, processing aggregate function in parallel is drawing researchers' attention. The aim of our work is to propose a generic framework enabling to map an arbitrary aggregation into a generic algorithm and identify when it can be efficiently executed on modern large-scale data-processing systems. We describe our preliminary results regarding classes of symmetric and asymmetric aggregation that can be mapped, in a systematic way, into efficient MapReduce-style algorithms.
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Contributor : Chao Zhang <>
Submitted on : Saturday, August 5, 2017 - 1:35:25 PM
Last modification on : Wednesday, March 4, 2020 - 12:28:02 PM


symmetric and asymmetric aggre...
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  • HAL Id : hal-01533675, version 3



Chao Zhang, Farouk Toumani, Emmanuel Gangler. Symmetric and Asymmetric Aggregate Function in Massively Parallel Computing. [Research Report] LIMOS (UMR CNRS 6158), université Clermont Auvergne, France. 2017. ⟨hal-01533675v3⟩



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