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Forespørgselsoptimering×Databasenormalisering×Indekseringsstrategi×
FagområdeInformationssystemerInformationssystemerInformationssystemer
FamilieProcess / pipelineProcess / pipelineProcess / pipeline
Oprindelsesår197919701972
OphavspersonIBM San Jose Research LaboratoryEdgar F. CoddRudolf Bayer and Edward M. McCreight
TypeDatabase optimization techniqueData organization methodologyDatabase optimization technique
Oprindelig kildeJarke, M., & Koch, J. (1984). Query optimization in database systems. ACM Computing Surveys, 16(2), 111-152. DOI ↗Codd, E. F. (1970). A relational model of data for large shared data banks. Communications of the ACM, 13(6), 377-387. DOI ↗Bayer, R., & McCreight, E. (1972). Organization and maintenance of large ordered indices. Acta Informatica, 1(3), 173-189. DOI ↗
Aliasserindex design, indexing
Relaterede211
ResuméQuery optimization is a critical process in database management that transforms high-level SQL queries into efficient execution plans. Developed systematically by IBM researchers in the late 1970s, it aims to minimize execution time, disk I/O, and resource consumption by selecting the most effective access paths and join strategies.Database normalization is a systematic process for organizing relational database schemas to eliminate redundancy and enforce data integrity. Introduced by Edgar Codd in 1970-1971 as part of the relational database model, it defines a series of normal forms (1NF through BCNF) that progressively eliminate different types of data anomalies.Indexing strategy is the practice of systematically designing database indexes to accelerate query performance. Developed following Bayer and McCreight's foundational B-tree work in 1972, effective indexing requires analyzing query patterns, choosing appropriate index structures, and maintaining index health as data evolves.
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ScholarGateSammenlign metoder: Query Optimization · Database Normalization · Indexing Strategy. Hentet 2026-06-16 fra https://scholargate.app/da/compare