@conference {DBLP:conf/dais/CoelhoPVO16,
	title = {Holistic Shuffler for the Parallel Processing of SQL Window Functions},
	booktitle = {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},
	year = {2016},
	note = {<p>n/a</p>
},
	pages = {75{\textendash}81},
	abstract = {<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>
},
	doi = {10.1007/978-3-319-39577-7_6},
	url = {http://dx.doi.org/10.1007/978-3-319-39577-7_6},
	attachments = {https://haslab.uminho.pt/sites/default/files/facoelho/files/holistic-proceedings.pdf},
	author = {F{\'a}bio Coelho and Jos{\'e} Orlando Pereira and Ricardo Vila{\c c}a and Rui Oliveira}
}