Antisampling for Estimation: An Overview
IEEE Transactions on Software Engineering
Statistical profile estimation in database systems
ACM Computing Surveys (CSUR)
Database management
Data caching issues in an information retrieval system
ACM Transactions on Database Systems (TODS)
Statistical estimators for aggregate relational algebra queries
ACM Transactions on Database Systems (TODS)
Optimal update policies for distributed materialized views
Management Science
An Analytic Approach to Statistical Databases
VLDB '83 Proceedings of the 9th International Conference on Very Large Data Bases
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The problem of determining data requirements in cases where statistical query answers are desired is studied. Specifically, we consider the value of storing aggregate data that can be used to speed up answering such queries, but at the potential costs of incomplete information due to either estimation error or staleness, as well as increased costs of update. We formulate the overall optimization problem for design, and decompose it into several subproblems that can be separately addressed. Two of these subproblems are the choice of update method, and choice of aggregates. Qualitative results are given regarding the selection of update policy, and design heuristics, based on numerical experiments, are given for single-attribute Legendre polynomial aggregates. Multivariate Legendre aggregates are also discussed, and suggestions for future research are given.