Hybrid Architecture for Query Optimizers Using Checkpoints with Plan Reduction Algorithms
DEEPIKA MALVIYA, SYED IMRAN ALI and ZOHA USMANI
Department of CSE, Sagar Institute of Science Technology and Research, Ratibad, Bhopal-462044 (M.P.) (India)
Query Optimization, Selectivity, Plan Cardinality, Plan Diagrams, Checkpoints
Query Optimization is an important component of all Database Systems. Designing optimizers which takes less search time yet provides the most optimal query execution plan has been a challenge for DBMS research community in the last decade. Most of the optimization techniques focus on the static compilation of selectivity of base relations. The cost of executing a plan depends heavily on selectivity which keeps changing frequently and thus static compilation provides an inconsistent performance. Adaptive query optimization is an excellent method of generating optimal plans consistently. This paper proposes new hybrid architecture for query optimizers which combine features of adaptive query processing and also reduces the search space for re optimization using reduced plan diagrams and cost diagrams. This hybrid architecture is bound to give more efficient performance as compared to any other optimization technique along with increased robustness and a substantial increase in consistency of selecting most optimal execution plan.
2455-9997 (Online) - 2229-3531 (Print)
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