Counter strike

Author:

Fender Pit1,Moerkotte Guido1

Affiliation:

1. University of Mannheim, Mannheim, Germany

Abstract

Finding the optimal execution order of join operations is a crucial task of today's cost-based query optimizers. There are two approaches to identify the best plan: bottom-up and top-down join enumeration. But only the top-down approach allows for branch-and-bound pruning, which can improve compile time by several orders of magnitude while still preserving optimality. For both optimization strategies, efficient enumeration algorithms have been published. However, there are two severe limitations for the top-down approach: The published algorithms can handle only (1) simple (binary) join predicates and (2) inner joins. Since real queries may contain complex join predicates involving more than two relations, and outer joins as well as other non-inner joins, efficient top-down join enumeration cannot be used in practice yet. We develop a novel top-down join enumeration algorithm that overcomes these two limitations. Furthermore, we show that our new algorithm is competitive when compared to the state of the art in bottom-up processing even without playing out its advantage by making use of its branch-and-bound pruning capabilities.

Publisher

VLDB Endowment

Subject

General Earth and Planetary Sciences,Water Science and Technology,Geography, Planning and Development

Cited by 11 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Efficient Enumeration of Recursive Plans in Transformation-Based Query Optimizers;Proceedings of the VLDB Endowment;2024-07

2. Keep It Simple: Testing Databases via Differential Query Plans;Proceedings of the ACM on Management of Data;2024-05-29

3. CERT: Finding Performance Issues in Database Systems Through the Lens of Cardinality Estimation;Proceedings of the IEEE/ACM 46th International Conference on Software Engineering;2024-04-12

4. Neighborhood-Based Hypergraph Core Decomposition;Proceedings of the VLDB Endowment;2023-05

5. A Survey on Advancing the DBMS Query Optimizer: Cardinality Estimation, Cost Model, and Plan Enumeration;Data Science and Engineering;2021-01-15

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