Accommodating Bursts in Distributed Stream Processing Systems. Yannis Drougas, ESRI email@example.com Vana Kalogeraki, AUEB firstname.lastname@example.org. Stream Processing Applications. Large class of emerging applications in which data streams must be processed online Example applications include:
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High-volume, continuous input streams
Processed result streams
On-line processing functions / continuous query operators implemented on each node:
Application layer: Execution of stream processing applications.
Overlay network consisted of processing nodes. Built over a DHT (currently, Pastry).
The physical (IP) network.
Initial resource requirements
Additional resource requirements due to single burst
p’ = p +δ
p2 dominates p, however,
when there is a burst we may
have to change plans to p3
Index Point (Pareto Point) Database calculation time, this is why index points need to be pre-calculated.
BARRE avoids missing data units during the burst and minimizes lost data units. Also, resulting plan is “safer”, so it prevents future drops
BARRE results in fewer data units dropped. It can sustain up to about 80% (vs. about 20%) application rate increase without dropping any data unit.
BARRE achieves a high percentage of data unit delivery.