Please use this identifier to cite or link to this item: http://repositorio.inesctec.pt/handle/123456789/4213
Title: Holistic Shuffler for the Parallel Processing of SQL Window Functions
Authors: Fábio André Coelho
José Orlando Pereira
Ricardo Pereira Vilaça
Rui Carlos Oliveira
Issue Date: 2016
Abstract: Window functions are a sub-class of analytical operators that allow data to be handled in a derived view of a given relation, while taking into account their neighboring tuples. Currently, systems bypass parallelization opportunities which become especially relevant when considering Big Data as data is naturally partitioned. We present a shuffling technique to improve the parallel execution of window functions when data is naturally partitioned when the query holds a partitioning clause that does not match the natural partitioning of the relation. We evaluated this technique with a non-cumulative ranking function and we were able to reduce data transfer among parallel workers in 85% when compared to a naive approach.
URI: http://repositorio.inesctec.pt/handle/123456789/4213
http://dx.doi.org/10.1007/978-3-319-39577-7_6
metadata.dc.type: conferenceObject
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Appears in Collections:HASLab - Articles in International Conferences

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