Clustering database queries for runtime prediction
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United States of America Patent
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Jan 29, 2019
Grant Date -
Jun 30, 2016
app pub date -
Dec 22, 2015
filing date -
Dec 27, 2014
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Abstract
The invention notably relates to a computer-implemented method of clustering reference queries in a database for prediction of the runtime of a target query in the database based on similarity of the target query with the reference queries. The method comprises providing a number of numerical values that represent the runtimes of the reference queries; computing the optimal K-means clustering of the numerical values for a predetermined number of clusters, wherein the computing includes iterating, a number of times corresponding to the predetermined number of clusters, a linear-time Row Minima Searching algorithm applied to a square matrix of order equal to the number of numerical values; and clustering the reference queries according to the computed clustering of the numerical values.
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