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- W2053688343 abstract "The goal of multi-objective query optimization (MOQO) is to find query plans that realize a good compromise between conflicting objectives such as minimizing execution time and minimizing monetary fees in a Cloud scenario. A previously proposed exhaustive MOQO algorithm needs hours to optimize even simple TPC-H queries. This is why we propose several approximation schemes for MOQO that generate guaranteed near-optimal plans in seconds where exhaustive optimization takes hours. We integrated all MOQO algorithms into the Postgres optimizer and present experimental results for TPC-H queries; we extended the Postgres cost model and optimize for up to nine conflicting objectives in our experiments. The proposed algorithms are based on a formal analysis of typical cost functions that occur in the context of MOQO. We identify properties that hold for a broad range of objectives and can be exploited for the design of future MOQO algorithms." @default.
- W2053688343 created "2016-06-24" @default.
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- W2053688343 date "2014-06-18" @default.
- W2053688343 modified "2023-10-02" @default.
- W2053688343 title "Approximation schemes for many-objective query optimization" @default.
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- W2053688343 doi "https://doi.org/10.1145/2588555.2610527" @default.
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