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- W2055633823 abstract "We present a simple geometric framework for the relational join. Using this framework, we design an algorithm that achieves the fractional hypertree-width bound, which generalizes classical and recent worst-case algorithmic results on computing joins. In addition, we use our framework and the same algorithm to show a series of what are colloquially known as beyond worst-case results. The framework allows us to prove results for data stored in Btrees, multidimensional data structures, and even multiple indices per table. A key idea in our framework is formalizing the inference one does with an index as a type of geometric resolution; transforming the algorithmic problem of computing joins to a geometric problem. Our notion of geometric resolution can be viewed as a geometric analog of logical resolution. In addition to the geometry and logic connections, our algorithm can also be thought of as backtracking search with memoization." @default.
- W2055633823 created "2016-06-24" @default.
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- W2055633823 date "2015-05-20" @default.
- W2055633823 modified "2023-09-24" @default.
- W2055633823 title "Joins via Geometric Resolutions" @default.
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- W2055633823 doi "https://doi.org/10.1145/2745754.2745776" @default.
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