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쿼리 최적화×데이터베이스 정규화×인덱싱 전략×
분야정보시스템정보시스템정보시스템
계열Process / pipelineProcess / pipelineProcess / pipeline
기원 연도197919701972
창시자IBM San Jose Research LaboratoryEdgar F. CoddRudolf Bayer and Edward M. McCreight
유형Database optimization techniqueData organization methodologyDatabase optimization technique
원전Jarke, 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 ↗
별칭index design, indexing
관련211
요약Query 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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ScholarGate방법 비교: Query Optimization · Database Normalization · Indexing Strategy. 2026-06-16에 다음에서 검색함: https://scholargate.app/ko/compare