Cardinality Estimation Using Sample Views with Quality Assurance
Summary: Proposes a general cardinality estimator that blends random sampling with materialized views for complex predicates, correlations, and UDFs. Uses execution feedback with data-change controls to keep estimates valid, demonstrated on a SQL Server prototype. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Per-Ake Larson
- 2. Wolfgang Lehner
- 3. Jingren Zhou
- 4. Peter Zabback
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