Abstract
Considering that in future DBMS's it will be possible to hold the active database in main memory, a new physical database organization is proposed. This organization aims two objectives: be compact and decomposable such as the active database always fits in main memory and speed up extended relational algebra in term of CPU time. Tuples and indices are integrated in a unique data structure called DBGraph. Tuples and values are stored separately and constitute the vertices of the DBGraph. Edges between tuples and values are maintained using OID's in order to constitute a bipartite graph. This graph precompiles selection, join and transitive closure operations. Set oriented execution of relational algebra is generated using a breadth first traversal of this graph while pipeline execution is produced using a depth first traversal. The two strategies lead to the same temporal complexity. Storage cost evaluations demonstrate the compactness of the DBGraph structure. Performance evaluations show that in a main memory context transitive closure on DBGraph outperforms transitive closure on join indices, still considered as one of the best algorithm.
This work has been supported by the ISIDE Esprit Project no1133
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Puchmeral, P., Thevenin, JM. (1989). A graph based data structure for efficient implementation of main memory DBMS's. In: Boral, H., Faudemay, P. (eds) Database Machines. IWDM 1989. Lecture Notes in Computer Science, vol 368. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-51324-8_29
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DOI: https://doi.org/10.1007/3-540-51324-8_29
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