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Our extensive evaluation shows that DQ achieves plans with optimization costs and query execution times competitive with the native query optimizer in each system, but can execute significantly faster ... We implement three versions of DQ to illustrate the ease of integration into existing DBMSes: (1) A version built on top of Apache Calcite, (2) a version integrated into PostgreSQL, and (3) a version integrated ... Our empirical results with DQ span across multiple systems, multiple cost models, and workloads. ...arXiv:1808.03196v2 fatcat:w35hsr6li5g23lbhnw6z3ueibe
We show empirically that even with an approximate tree structure, BayesCard can achieve comparable or better accuracy than the current SOTA methods. ... Evaluation metric: We use the Q-error as our evaluation metrics, which is define as follow: Q-error = ( Estimated Cardinality True Cardinality , True Cardinality Estimated Cardinality ) This evaluation ...arXiv:2012.14743v2 fatcat:b2wf3gs5x5antmrces4jatpafq