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Computer Science > Databases

arXiv:2502.15181 (cs)
[Submitted on 21 Feb 2025]

Title:Debunking the Myth of Join Ordering: Toward Robust SQL
Analytics

Authors:Junyi Zhao, Kai Su, Yifei Yang, Xiangyao Yu, Paraschos
Koutris, Huanchen Zhang
View a PDF of the paper titled Debunking the Myth of Join Ordering:
Toward Robust SQL Analytics, by Junyi Zhao and 4 other authors
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    Abstract:Join order optimization is critical in achieving good
    query performance. Despite decades of research and practice,
    modern query optimizers could still generate inferior join plans
    that are orders of magnitude slower than optimal. Existing
    research on robust query processing often lacks theoretical
    guarantees on join-order robustness while sacrificing query
    performance. In this paper, we rediscover the recent Predicate
    Transfer technique from a robustness point of view. We introduce
    two new algorithms, LargestRoot and SafeSubjoin, and then propose
    Robust Predicate Transfer (RPT) that is provably robust against
    arbitrary join orders of an acyclic query. We integrated Robust
    Predicate Transfer with DuckDB, a state-of-the-art analytical
    database, and evaluated against all the queries in TPC-H, JOB,
    and TPC-DS benchmarks. Our experimental results show that RPT
    improves join-order robustness by orders of magnitude compared to
    the baseline. With RPT, the largest ratio between the maximum and
    minimum execution time out of random join orders for a single
    acyclic query is only 1.6x (the ratio is close to 1 for most
    evaluated queries). Meanwhile, applying RPT also improves the
    end-to-end query performance by 1.5x (per-query geometric mean).
    We hope that this work sheds light on solving the practical join
    ordering problem.

Subjects: Databases (cs.DB)
Cite as:  arXiv:2502.15181 [cs.DB]
          (or arXiv:2502.15181v1 [cs.DB] for this version)
          https://doi.org/10.48550/arXiv.2502.15181
          Focus to learn more
          arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Junyi Zhao [view email]
[v1] Fri, 21 Feb 2025 03:24:06 UTC (2,075 KB)
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