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| Kyselyoptimointi× | Tietokannan normalisointi× | Indeksointistrategia× | |
|---|---|---|---|
| Tieteenala | Tietojärjestelmätiede | Tietojärjestelmätiede | Tietojärjestelmätiede |
| Menetelmäperhe | Process / pipeline | Process / pipeline | Process / pipeline |
| Syntyvuosi≠ | 1979 | 1970 | 1972 |
| Kehittäjä≠ | IBM San Jose Research Laboratory | Edgar F. Codd | Rudolf Bayer and Edward M. McCreight |
| Tyyppi≠ | Database optimization technique | Data organization methodology | Database optimization technique |
| Alkuperäislähde≠ | Jarke, 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 ↗ |
| Rinnakkaisnimet≠ | — | — | index design, indexing |
| Liittyvät≠ | 2 | 1 | 1 |
| Tiivistelmä≠ | Query 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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