Combining Histograms and Parametric Curve Fitting for Feedback-Driven Query Result-size Estimation

This paper aims to improve the accuracy of query result-size estimations in query optimizers by leveraging the dynamic feedback obtained from observations on the executed query workload. To this end, an approximate synopsis" of data-value distributions is devised that combines histogramswith parametric curve tting, leading to a speci c class of linear splines. The approach reconciles the bene ts of histograms, simplicity and versatility, with those of parametric techniques especially the adaptivity to statistically biased and dynamically evolving query workloads. The paper presents e cient algorithms for constructing the linear-spline synopsis for data-value distributions from a moving window of the most recent observations on the most critical query executions. The approach is worked out in full detail for capturing frequency as well as density distributions of data values, and it is shown how result size estimations are inferred for exact-match and range queries as well as pr...

• Type: Conference
• Year: 1999
• Where: VLDB
• Authors: Arnd Christian König, Gerhard Weikum
• Keywords: Critical Query Executions, Data-value Distributions, Database, Query Workloads, VLDB 1999