conference paper
Squall: Scalable Real-time Analytics
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.
Type
conference paper
Author(s)
El Seidy, Mohammed
Guliyev, Khayyam Mubariz Oglu
Vu, Minh Khue
Espino Timón, Daniel
Dashti, Mohammad
Date Issued
2016
Publisher
Published in
Proceedings of the VLDB Endowment
Volume
9
Issue
13
Start page
1553
End page
1556
Subjects
Editorial or Peer reviewed
REVIEWED
Written at
EPFL
EPFL units
| Event name | Event place | Event date |
New Delhi, India | September 5-9, 2016 | |
Available on Infoscience
July 14, 2016
Use this identifier to reference this record