%0 Conference Paper
%B Distributed Applications and Interoperable Systems - 16th {IFIP} {WG} 6.1 International Conference, {DAIS} 2016, Held as Part of the 11th International Federated Conference on Distributed Computing Techniques, DisCoTec 2016, Heraklion, Crete, Greece, June
%D 2016
%T Holistic Shuffler for the Parallel Processing of SQL Window Functions
%A Fábio Coelho
%A José Orlando Pereira
%A Ricardo Vilaça
%A Rui Oliveira
%P 75–81
%R 10.1007/978-3-319-39577-7_6
%U http://dx.doi.org/10.1007/978-3-319-39577-7_6
%X <p>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.<br /> 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.</p>
%Z <p>n/a</p>
%> https://haslab.uminho.pt/sites/default/files/facoelho/files/holistic-proceedings.pdf