By Fábio Coelho, HASLab, INESC TEC & UMinho.
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..
Keywords. Distributed Systems, SQL, Window Functions, Distributed Query Engines.
About the speaker. Fábio Coelho is currently a PhD Student at the MAP-i Doctoral Program – a joint program between the Universities of Minho, Aveiro and Porto, under the supervision of Prof. Rui Oliveira. He obtained his B.Sc. in Computer Networks and Multimedia in 2011. Afterwards, he enrolled in the M.Sc. in Computer Science at Universidade do Minho in 2013, specializing in Distributed Systems and Cryptography and Security. He is currently working on his thesis with the title “Towards a transactional and analytical data management system for Big Data” at HASLab, INESC TEC and Univ. of Minho. Fabio has published several papers so far, spanning his interests in both transactional systems and scalable SQL Analytical operators.
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