G. Copeland et al. Buffering schemes for permanent data. In Proceedings of the Int'l Conf. on Data Engineering, pages 214--21, Los Angeles, Calif., 1986. Home/Search Document Not in Database Summary Related Articles Check |
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A Piggyback Method to Collect Statistics for Query .. - Zhu, Dunkel.. (1998) (1 citation) (Correct)
....base statistics (profile) for the tables in a database, intermediate statistics for the intermediate result tables during query processing, and target statistics for the final result table of a query. They discussed the relationships between statistics and cost estimates in query processing. In [4, 11, 23], Zander, Copeland, and Mackert et al. proposed a number of techniques to estimate physical statistics (e.g. page references) for data and index files in a database. In [6] Haas et al. introduced several sampling based estimators to estimate the number of distinct valus of a column in a table. ....
G. Copeland et al. Buffering schemes for permanent data. In Proceedings of the Int'l Conf. on Data Engineering, pages 214--21, Los Angeles, Calif., 1986.
Scalable Visual Hierarchy Exploration - Stroe, Rundensteiner, Ward (2000) (Correct)
....together is identified with the query that generated it is called semantic caching [4] or predicate caching [11] Our buffer management requirements are similar to those present in semantic cashing. Other work in the area of object level caching for database applications have been addressed in [3, 13]. 7 Conclusions With the increasing amount of data being accumulated nowadays, the need for visually exploring large datasets becomes imperative. A viable way to achieve scalability in visualization is to integrate visualization applications with database management systems. Such integrations ....
G. P. Copeland, S. Khoshafian, M. G. Smith, and P. Valduriez. Buffering schemes for permanent data. In Intl Conf on Data Engineering, pages 214--221, 1986.
Scalable Visual Hierarchy Exploration - Stroe, Rundensteiner, Ward (2000) (Correct)
....the parameters of the active window. In our system however only one query is required at a time, thus further influencing the strategy used for preventing duplicate entries in the buffer. Other work in the area of object level caching for database applications have been addressed for example in [5, 24]. Due to not needing to fully consider caching, our buffer management strategy is simple, yet efficient not requiring any unnecessary data accesses. 7 Conclusions and Future Work With the increasing amount of data being accumulated nowadays, the need for visually exploring large datasets ....
G. P. Copeland, S. Khoshafian, M. G. Smith, and P. Valduriez. Buffering schemes for permanent data. In Proc of the Second Intl Conf on Data Engineering, Feb 5-7, 1986, Los Angeles, Cal, USA, pages 214--221, 1986.
Semantic Data Caching and Replacement - Dar, Franklin, Jónsson.. (1996) (111 citations) (Correct)
....separate object cache. These approaches aim to balance the tradeoff between overhead and sensitivity to cluster ing. Semantic caching takes the different approach of using predicates to dynamically group tuples. The caching of results based on projections (rather than selections) was studied in [CKSV86]. However, the work most closely related to ours is the predicate caching approach of Keller and Basu [KB96] which uses a collection of possibly overlapping constraint formulas, derived from queries, to describe client cache contents. Our work differs from [KB96] in three significant respects. ....
G. P. Copeland, S. N. Khosafian, M. G. Smith, P. Valduriez. Buffering schemes for permanent data. Proc. of IEEE Conf. on Data Engineering, 1986.
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