<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Fábio Coelho</style></author><author><style face="normal" font="default" size="100%">José Orlando Pereira</style></author><author><style face="normal" font="default" size="100%">Ricardo Vilaça</style></author><author><style face="normal" font="default" size="100%">Rui Oliveira</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Holistic Shuffler for the Parallel Processing of SQL Window Functions</style></title><secondary-title><style face="normal" font="default" size="100%">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</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1007/978-3-319-39577-7_6</style></url></web-urls><related-urls><url><style face="normal" font="default" size="100%">https://haslab.uminho.pt/sites/default/files/facoelho/files/holistic-proceedings.pdf</style></url></related-urls></urls><pages><style face="normal" font="default" size="100%">75–81</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;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.&lt;br /&gt;
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.&lt;/p&gt;
</style></abstract><notes><style face="normal" font="default" size="100%">&lt;p&gt;n/a&lt;/p&gt;
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