18620

PanJoin: A Partition-based Adaptive Stream Join

Fei Pan, Hans-Arno Jacobsen
Electrical & Computer Engineering, University of Toronto, Toronto, Canada
arXiv:1811.05065 [cs.DB], (13 Nov 2018)

@article{pan2018panjoin,

   title={PanJoin: A Partition-based Adaptive Stream Join},

   author={Pan, Fei and Jacobsen, Hans-Arno},

   year={2018},

   month={nov},

   archivePrefix={"arXiv"},

   primaryClass={cs.DB}

}

Download Download (PDF)   View View   Source Source   

238

views

In stream processing, stream join is one of the critical sources of performance bottlenecks. The sliding-window-based stream join provides a precise result but consumes considerable computational resources. The current solutions lack support for the join predicates on large windows. These algorithms and their hardware accelerators are either limited to equi-join or use a nested loop join to process all the requests. In this paper, we present a new algorithm called PanJoin which has high throughput on large windows and supports both equi-join and non-equi-join. PanJoin implements three new data structures to reduce computations during the probing phase of stream join. We also implement the most hardware-friendly data structure, called BI-Sort, on FPGA. Our evaluation shows that PanJoin outperforms several recently proposed stream join methods by more than 1000x, and it also adapts well to highly skewed data.
Rating: 2.0/5. From 1 vote.
Please wait...

* * *

* * *

HGPU group © 2010-2018 hgpu.org

All rights belong to the respective authors

Contact us: