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Parallelizing Intra-Window Join on Multicores: An Experimental Study
Zitatschlüssel ZhangMHGZHMM21
Autor Zhang, Shuhao and Mao, Yancan and He, Jiong and Grulich, Philipp M. and Zeuch, Steffen and He, Bingsheng and Ma, Richard T. B. and Markl, Volker
Buchtitel 2021 ACM SIGMOD/PODS International Conference on Management of Data, Xi'an, Shaanxi, China
Jahr 2021
Notiz to be published
Zusammenfassung The intra-window join (IaWJ), i.e., joining two input streams over a single window, is a core operation in modern stream processing applications. This paper presents the first comprehensive study on parallelizing the IaWJ on modern multicore architectures. In particular, we classify IaWJ algorithms into lazy and eager execution approaches. For each approach, there are further design aspects to consider, including different join methods and partitioning schemes, leading to a large design space. Our results show that none of the algorithms always performs the best, and the choice of the most performant algorithm depends on: (i) workload characteristics, (ii) application requirements, and (iii) hardware architectures. Based on the evaluation results, we propose a decision tree that can guide the selection of an appropriate algorithm.
Link zur Publikation [1] Download Bibtex Eintrag [2]

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