Good cardinality estimates are critical for generating good execution plans during query optimization. Complex predicates, correlations between columns, and user-defined functions are extremely hard to handle when using the traditional histogram approach. This demo illustrates the use of sample views for cardinality estimations as prototyped in Microsoft SQL Server. We show the creation of sample views, discuss how they are exploited during query optimization, and explain their potential effect on query plans. In addition, we also show our implementation of maintenance policies using statistical quality control techniques based on query feedback.
Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:80836 |
Date | 13 December 2022 |
Creators | Larson, Per-Ake, Lehner, Wolfgang, Zhou, Jingren, Zabback, Peter |
Publisher | ACM |
Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
Language | English |
Detected Language | English |
Type | info:eu-repo/semantics/acceptedVersion, doc-type:conferenceObject, info:eu-repo/semantics/conferenceObject, doc-type:Text |
Rights | info:eu-repo/semantics/openAccess |
Relation | 978-1-59593-686-8 |
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