PANDA: Performance Prediction for Parallel ANd Dynamic StreAm Processing
Key: Agn22-1
Author: Pratyush Agnihotri, Boris Koldehofe, Carsten Binnig, Manisha Luthra
Date: June 2022
Kind: In proceedings
Book title: Proceedings of the 16th ACM International Conference on Distributed and Event-Based Systems (DEBS '22)
Abstract: Distributed Stream Processing (DSP) systems highly rely on parallelism mechanisms to deliver high performance in terms of latency and throughput. Yet the development of such parallel systems altogether comes with numerous significant challenges. In this paper, we focus on how to select appropriate resources for parallel stream processing under the presence of highly dynamic and unseen workloads. We present PANDA, which aims to provide a new learned approach for supporting highly efficient and parallel DSP systems. The main idea is that PANDA can provide accurate resource estimates, particularly parallelism degree, to guarantee elasticity and performance demands of large-scale applications.
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