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joinTree: A novel join-oriented multivariate operator for spatio-temporal data management in Flink

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Abstract

In the era of intelligent Internet, the management and analysis of massive spatio-temporal data is one of the important links to realize intelligent applications and build smart cities, in which the interaction of multi-source data is the basis of realizing spatio-temporal data management and analysis. As an important carrier to achieve the interactive calculation of massive data, Flink provides the advanced Operator Join to facilitate user program development. In a Flink job with multi-source data connection operations, the selection of join sequences and the data communication in the repartition phase are both key factors that affect the efficiency of the job. However, Flink does not provide any optimization mechanism for the two factors, which in turn leads to low job efficiency. If the enumeration method is used to find the optimal join sequence, the result will not be obtained in polynomial time, so the optimization effect cannot be achieved. We investigate the above problems, design and implement a more advanced Operator joinTree that can support multi-source data connection in Flink, and introduce two optimization strategies into the Operator. In summary, the advantages of our work are highlighted as follows: (1) the Operator enables Flink to support multi-source data connection operation, and reduces the amount of calculation and data communication by introducing lightweight optimization strategies to improve job efficiency; (2) with the optimization strategy for join sequence, the total running time can be reduced by 29% and the data communication can be reduced by 34% compared with traditional sequential execution; (3) the optimization strategy for data repartition can further enable the job to bring 35% performance improvement, and in the average case can reduce the data communication by 43%.

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All data in the experiment is authoritative and available.

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Funding

This research was supported by the National Key R&D Program of China under Grant No. 2018YFB1004402; and the NSFC under Grant No. 61872072, 62072087, 61772124, 61932004, 61732003, and 61729201; and the Fundamental Research Funds for the Central Universities under Grant No. N2016009.

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Authors and Affiliations

  1. School of Computer Science and Engineering, Northeastern University, No. 3-11, Wenhua Road, Heping District, Shenyang, 110819, China

    Hangxu Ji, Gang Wu & Yuhai Zhao

  2. School of Computer Science and Technology, Beijing Institute of Technology, No. 5, South Street, Zhongguancun Street, Haidian District, Beijing, 100081, China

    Shiye Wang & Guoren Wang

  3. Thinvent Digital Technology Co., Ltd., No.681 Torch Avenue, High-Tech Development Zone, Nanchang, 410000, China

    George Y. Yuan

Authors
  1. Hangxu Ji
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  2. Gang Wu
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  4. Shiye Wang
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  5. Guoren Wang
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Contributions

Conceptualization, Hangxu Ji; software, Hangxu Ji; methodology, Hangxu Ji and Yuhai Zhao; supervision, Hangxu Ji and Shiye Wang; validation, Hangxu Ji and Shiye Wang; writing-original draft, Hangxu Ji; writing-review and editing, Gang Wu, George Y. Yuan, and Guoren Wang.

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Correspondence to Gang Wu.

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Ji, H., Wu, G., Zhao, Y. et al. joinTree: A novel join-oriented multivariate operator for spatio-temporal data management in Flink. Geoinformatica 27, 107–132 (2023). https://doi.org/10.1007/s10707-022-00470-5

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