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TU Berlin, DFKI and NUS Paper was Accepted at SIGMOD 2021
The
paper "Parallelizing Intra-Window Join on Multicores: An
Experimental Study" by Shuhao Zhang, Yancan Mao,
Jiong He, Philipp Grulich, Steffen Zeuch, Bingsheng He, Richard
Ma and Volker Markl was accepted for
presentation at the ACM SIGMOD/PODS International Conference on
Management of Data (SIGMOD/PODS 2021), which will take place from June
20 - 25, 2021 in Xi'an, China. This work is the result of a
collaboration between researchers from the Database Systems and
Information Management (DIMA) group at TU Berlin, the Intelligent
Analytics for Massive Data (IAM) group at DFKI, the Department of
Computer Science at the National University of Singapore (NUS) and
ByteDance.
The annual ACM SIGMOD/PODS Conference is a leading
international forum for database researchers, practitioners,
developers, and users to explore cutting-edge ideas and results, and
to exchange techniques, tools, and experiences in all aspects of data
management. To learn more about SIGMOD/PODS, please visit
https://2021.sigmod.org/. [1]
Abstract:
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.
A preprint version
of the paper is available here. [2]
kation/Papers/Zhang_SIGMOD-2021_preprint.pdf