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conference paper

Squall: Scalable Real-time Analytics

Vitorovic, Aleksandar  
•
El Seidy, Mohammed
•
Guliyev, Khayyam Mubariz Oglu
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2016
Proceedings of the VLDB Endowment
42nd International Conference on Very Large Data Bases

Squall is a scalable online query engine that runs complex analytics in a cluster using skew-resilient, adaptive operators. Squall builds on state-of-the-art partitioning schemes and local algorithms, including some of our own. This paper presents the overview of Squall, including some novel join operators. The paper also presents lessons learned over the five years of working on this system, and outlines the plan for the proposed system demonstration.

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