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Rapport (Rapport De Recherche) Année : 2017

Symmetric and Asymmetric Aggregate Function in Massively Parallel Computing(extended version)

Fonctions d'agrégation symétriques et asymétriques dans le calcul massivement parallèle (version étendue)

Résumé

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 that enables to map an aggregation function into an efficient massively parallel algorithm that can be executed on modern large-scale data-processing systems. We describe our preliminary results regarding classes of symmetric and asymmetric aggregation functions that can be mapped, in a systematic way, into efficient MapReduce algorithms.
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Dates et versions

hal-01533675 , version 1 (06-06-2017)
hal-01533675 , version 2 (11-06-2017)
hal-01533675 , version 3 (05-08-2017)

Identifiants

  • HAL Id : hal-01533675 , version 1

Citer

Chao Zhang, Farouk Toumani, Emmanuel Gangler. Symmetric and Asymmetric Aggregate Function in Massively Parallel Computing(extended version). [Research Report] LIMOS (UMR CNRS 6158), université Clermont Auvergne, France. 2017. ⟨hal-01533675v1⟩
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