Query progress estimation

Data processing: database and file management or data structures – Database design – Data structure types

Reexamination Certificate

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Details

C707S793000

Reexamination Certificate

active

07493337

ABSTRACT:
A query progress indicator that provides an indication to a user of the progress of a query being executed on a database. The indication of the progress of the query allows the user to decide whether the query should be allowed to complete or should be aborted. One method that may be used to estimate the progress of a query that is being executed on a database defines a model of work performed during execution of a query. The total amount of work that will be performed during execution of the query is estimated according to the model. The amount of work performed at a given point during execution of the query is estimated according to the model. The progress of the query is estimated using the estimated amount of work at the given point in time and the estimated total amount of work. This estimated progress of query execution may be provided to the user.

REFERENCES:
patent: 6301580 (2001-10-01), Eigel-Danielson
patent: 6865717 (2005-03-01), Wright
Ramakrishnan et al., “Database Management Systems”, 3rd Edition, McGraw-Hill Press, 2003, pp. 404-409.
Lezius et al., “TigerSearch Manual”, University of Stuttgart, Apr. 5, 2002.
Kabra et al., “Efficient Mid-Query Re-Optimization of Sub-Optimal Query Execution Plans”, Proceedings of ACM SIGMOD, 1998.
Aboulnaga, A., and Chaudhuri, S.Self-Tuning Histograms: Building Histograms Without Looking at Data. Proceedings of ACM SIGMOD 1999.
Antoshenkov, G.Dynamic Query Optimization in Rdb/VMS. Proceedings of IEEE JCDE 1993.
Dewitt, D., and Kabra, N.Efficient Mid-Query Re-Optimization of Sub-Optimal Query Execution Plans. Proceedings of ACM SIGMOD 1998.
Graefe, G.Query Evaluation Techniques for Large Databases. ACM Conput. Surv. 25(2): 73-170(1993).
Haas, P.J., and Hellerstein J.M.Ripple Joins for Online Aggregation. Proceedings of ACM SIGMOD, 1995.
Hans, P.J., Naughton, J.F., Seshadri, S., and Stokes L.Sampling-based estimation of the number of distinct values of an attribute. Proceedings of VLDB 1995.
Hellerstein, J.M., Haas, P.J., and Wang, H.J.Online Aggregation. Proceedings of ACM SIGMOD 1997.
Ioannidis, Y., and Christodoulakis, S.On the propagation of errors in the size of join results. Proceedings of ACM SIGMOD, 1991.
Ioannidis, Y., and Poosala. V.Balancing Histogram Optimality and Practicality for Query Result Size Estimation. Proceedings of ACM SIGMOD 1995.
Myers, B.A.The Importance of Percent-Done Progress Indicators for Computer-Human Interfaces. Proceedings of ACM SIGCHI 1985.
Stillger, M., Lohman, O., Markl, V., and Kandil, M.LEO: DB2's LEarning Optimizer. Proceedings of VLDB 2001 , (CHI '00) (The Hague, The Netherlands, Apr. 1-6, 2000). ACM Press, New York, NY, 2000, 526-531.

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