发明授权
US07512629B2 Consistent and unbiased cardinality estimation for complex queries with conjuncts of predicates 有权
具有谓词结合的复杂查询的一致且无偏差的基数估计

Consistent and unbiased cardinality estimation for complex queries with conjuncts of predicates
摘要:
The present invention provides a method of selectivity estimation in which preprocessing steps improve the feasibility and efficiency of the estimation. The preprocessing steps are partitioning (to make iterative scaling estimation terminate in a reasonable time for even large sets of predicates), forced partitioning (to enable partitioning in case there are no “natural” partitions, by finding the subsets of predicates to create partitions that least impact the overall solution); inconsistency resolution (in order to ensure that there always is a correct and feasible solution), and implied zero elimination (to ensure convergence of the iterative scaling computation under all circumstances). All of these preprocessing steps make a maximum entropy method of selectivity estimation produce a correct cardinality model, for any kind of query with conjuncts of predicates. In addition, the preprocessing steps can also be used in conjunction with prior art methods for building a cardinality model.
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