Browsing by Author "Chen, Chungmin Melvin"
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Item Adaptive Cost Estimation for Client-Server based Heterogeneous Database Systems(1998-10-15) Yao, Zhaohui; Chen, Chungmin Melvin; Roussopoulos, NickIn this paper, we propose a new method for estimating query cost in client-server based heterogeneous database management system. The cost estimation parameters are adjusted by an Adaptive Cost Estimation (ACE) module which uses query execution feedback yielding more and more accurate cost estimates. The most important features of ACE are its detailed cost model which accounts for all costs incurred, its rapid convergence to the actual parameter values, and its low overhead which permits continuous adaptation during the run time of the system. ACE has been implemented and tested with Oracle 6, Oracle 7, Ingres, and ADMS. Extensive experiments performed on these systems show that the ACE's time estimates are within 20% of the real wall-clock time for more than 92% of the queries. This percentage surpasses 98% for queries over 20 seconds. (Also cross-referenced as UMIACS-TR-96-37)Item Adaptive Database Buffer Allocation Using Query Feedback(1998-10-15) Chen, Chungmin Melvin; Roussopoulos, NickIn this paper, we propose the concept of using query execution feedback for improving database buffer management. A query feedback model which adaptively quantifies the page fault characteristics of all query access patterns including sequential, looping and most importantly random, is defined. Based on this model, a load control and a marginal gain ratio buffer allocation scheme are developed. Simulation experiments show that the proposed method is consistently better than the previous methods and in most cases, it significantly outperforms all other methods for random access reference patterns. (Also cross-referenced as UMIACS-TR-93-49)Item Adaptive Selectivity Estimation Using Query Feedback(1998-10-15) Chen, Chungmin Melvin; Roussopoulos, NickItem The Implementation and Performance Evaluation of the ADMS Query Optimizer: Integrating Query Result Caching and Matching(1998-10-15) Chen, Chungmin Melvin; Roussopoulos, NickIn this paper, we describe the design and evaluation of the ADMS optimizer. Capitalizing on a structure called Logical Access Path Schema to model the derivation relationship among cached query results, the optimizer is able to perform query matching coincidently with the optimization and generate more efficient query plans using cached results. The optimizer also features data caching and pointer caching, different cache replacement strategies, and different cache update strategies. An extensive set of experiments were conducted, and the results showed that pointer caching and dynamic cache update strategies substantially speedup query computations and, thus, increase query throughput under situations with fair query correlation and update load. The requirement of the cache space is relatively small and the extra computation overhead introduced by the caching and matching mechanism is more than offset by the time saved in query processing. (Also cross-referenced as UMIACS-TR-93-106)