Techniques for query processing using high dimension histograms
US10140353B2 · kind B2 · utility
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Key dates
| Filing date | Dec 22, 2014 |
| Grant date | Nov 27, 2018 |
| Priority date | — |
| Expiry date | Jun 10, 2036 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F16/2456
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Relational data for a database table having multiple columns (dimensions) is represented as a histogram. The buckets of the histogram are clustered into clusters, the clusters are fewer in number than the buckets of the histogram. Each cluster is represented in hyper-space as a line segment (vector) with a thickness value. Average frequencies for the line segments (vectors) and their thickness values are computed. The average frequencies are processed by a query optimizer when processing a query predicate of a query to use as an estimation of selectivity or an estimation of a cardinality of a join operation.
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