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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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Type
conference paper
DOI
10.14778/3007263.3007307
Author(s)
Vitorovic, Aleksandar  
El Seidy, Mohammed
Guliyev, Khayyam Mubariz Oglu
Vu, Minh Khue
Espino Timón, Daniel
Dashti, Mohammad
Klonatos, Ioannis  
Koch, Christoph  
Date Issued

2016

Publisher

VLDB Endowment Inc.

Published in
Proceedings of the VLDB Endowment
Volume

9

Issue

13

Start page

1553

End page

1556

Subjects

online multi-way joins

•

skew-resilience

•

scalability

URL

URL

https://infoscience.epfl.ch/record/217286?ln=en
Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
DATA  
Event nameEvent placeEvent date
42nd International Conference on Very Large Data Bases

New Delhi, India

September 5-9, 2016

Available on Infoscience
July 14, 2016
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/127191
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