Squall

Aleksandar Vitorovic, Mohammed Elseidy, Khayyam Guliyev, Khue Vu Minh, Daniel Espino, Mohammad Dashti, Yannis Klonatos, Christoph Koch
2016 Proceedings of the VLDB Endowment  
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.
doi:10.14778/3007263.3007307 fatcat:gjwsccccqjasbkexrojikud56y