Optimizer dynamic sampling

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

Reexamination Certificate

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

C707S793000

Reexamination Certificate

active

10435228

ABSTRACT:
Described herein are approaches to implementing dynamic sampling in a way that lessens or eliminates the additional overhead incurred to perform dynamic sampling. Also described are techniques for determining characteristics about predicates not previously determined by conventional techniques for dynamic sampling. Dynamic sampling is used by a query optimizer to dynamically estimate predicate selectivities and statistics. When a database statement is received by a database server, an initial analysis of the database statement is made to determine the efficacy of dynamic sampling, that is, to determine whether optimization of the query would benefit from dynamic sampling and whether performance is not excessively impacted by the dynamic sampling process. If this analysis determines dynamic sampling should be used, then dynamic sampling is undertaken.

REFERENCES:
patent: 6012064 (2000-01-01), Gibbons et al.
patent: 6353826 (2002-03-01), Seputis
patent: 6745652 (2004-06-01), Bestgen et al.
patent: 6801905 (2004-10-01), Andrei
patent: 6934695 (2005-08-01), Kase et al.
patent: 7007009 (2006-02-01), Bestgen et al.
patent: 7010521 (2006-03-01), Hinshaw et al.
Barlos et al, “On the Development of a Site Selection Optimizer for Distributed and Parallel Database Systems”, ACM 1993, pp. 684-693.
Hsu et al, “Semantic Query Optimization for Query Plans of Heterogeneous Multi Database Systems”, IEEE 2000, pp. 959-978.
Ng et al, “On Reconfiguring Query Execution Plans in Distributed Object-Relational DBMS”, Parallel and Distributed Systems, 1998 Proceedings, 1998 International Conference on, Publication Date: Dec. 14-16, 1998, pp. 59-66.
Frank Olken et al., “Random Sampling from Databases—A Survey,” Mar. 22, 1994, pp. 1-54.
Frank Olken, “Random Sampling from Databases,” 1993, 172 pages.
Frank Olken et al., “Random Sampling from B+trees,” Proceedings of the International Conference on Very Large Data Bases, Amsterdam, 1989, 9 pages.
Dan E. Willard, “Optimal Sample Cost Residues for Differential Database Batch Query Problems,” Journal of the Association for Computing Machinery, vol. 38. No. 1, Jan. 1991, pp. 104-119.
Sumit Ganguly et al., “Bifocal Sampling for Skew-Resistant Join Size Estimation,”ACM SIGMOD '96, Montreal, Canada, ACM, 1996, pp. 271-281.
Peter J. Haas et al., “Fixed-Precision Estimation of Join Selectivity,” ACM, PODS, May 1993, Washingotn, D.C., pp. 190-201.
Yi-Leh Wu et al., “Applying the Golden Rule of Sampling for Query Estimation,” ACM SIGMOD 2001, May 21-24 Santa Barbara, California, pp. 449-460.
Peter J. Haas et al., “On the Relative Cost of Sampling for Join Selectivity Estimation,” SIGMOD/PODS '94, May 1994, Minneapolis, Minnesota, pp. 14-24.
Peter J. Haas et al., “Sequential Sampling Procedures for Query Size Estimation,” 1992 ACM SIGMOD, Jun. 1992, pp. 341-350.
Richard J. Lipton et al., “Practical Selectivity Estimation through Adaptive Sampling,” 1990, ACM, pp. 1-11.

LandOfFree

Say what you really think

Search LandOfFree.com for the USA inventors and patents. Rate them and share your experience with other people.

Rating

Optimizer dynamic sampling does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Optimizer dynamic sampling, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Optimizer dynamic sampling will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFUS-PAI-O-3724981

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.