Patent
Cardinality estimation of joins
TLDR
In this article, a method of estimating cardinality of a join of tables using multi-column density values and additionally using coarser density values of a subset of the multiscale density attributes is presented.Abstract:
A method of estimating cardinality of a join of tables using multi-column density values and additionally using coarser density values of a subset of the multi-column density attributes In one embodiment, the subset of attributes for the coarser densities is a prefix of the set of multi-column density attributes A number of tuples from each table that participate in the join may be estimated using densities of the subsets The cardinality of the join can be estimated using the multi-column density for each table and the estimated number of tuples that participate in the join from each tableread more
Citations
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References
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Proceedings ArticleDOI
Access path selection in a relational database management system
TL;DR: System R as mentioned in this paper is an experimental database management system developed to carry out research on the relational model of data, which chooses access paths for both simple (single relation) and complex queries (such as joins), given a user specification of desired data as a boolean expression of predicates.
Proceedings ArticleDOI
STHoles: a multidimensional workload-aware histogram
TL;DR: STHoles is introduced, a “workload-aware” histogram that allows bucket nesting to capture data regions with reasonably uniform tuple density and outperform the best multidimensional histogram techniques that require access to and processing of the full data sets during histogram construction.
Patent
A method of generating attribute cardinality maps
TL;DR: In this paper, the authors proposed a method for creating a histogram for use in minimizing response time and resource consumption when optimizing a query in a database, and other like structures, the histogram being created by placing ordered elements into specific range until the next element to be considered for inclusion in the range is a predetermined distance from the (generalized) mean value associated with the elements within the range, whereupon that next element is placed in the following range.
Proceedings ArticleDOI
Exploiting statistics on query expressions for optimization
Nicolas Bruno,Surajit Chaudhuri +1 more
TL;DR: This paper shows how to extend a generic optimizer so that it also exploits statistics built on expressions corresponding to intermediate nodes of query plans, and shows that in some cases, the quality of the resulting plans is significantly better than when only base-table statistics are available.