Concurrency control in high performance database systems

Details Concurrency control in high performance database systems Concurrency control in high performance database systems

2006-05-23

2006-05-23

Ali, Mohammad (Department: 2166)

Data processing: database and file management or data structures

Database design

Data structure types

C707S793000

Reexamination Certificate

active

07051028

ABSTRACT:
A system and method for concurrency control in high performance database systems. Generally includes receiving a database access request message from a transaction. Then, generating an element that corresponds to the access request message. The element type is that of a read element, commit element, validated element, or restart element. The element is then posted to a read-commit (RC) queue. If the element is a commit element, an intervening validation of the transaction is performed. Upon the transaction passing validation the requested database access is performed.

REFERENCES:
patent: 6052695 (2000-04-01), Abe et al.
patent: 2003/0236786 (2003-12-01), Shi et al.
Thomasian, Alexander, “Distributed optimistic concurrency control methods for high-performance transaction processing”, Jan.-Feb. 1998, IBM, NY, USA, pp. 173-189.
Dias et al, “Integrated concurrency-coherency controls for multisystem data sharing”, SE, IEEE Transactions, Apr. 1989, NY, USA, pp. 437-448.
Jenq et al, “A queueing network model for a distributed database tested”, SE, IEEE Transactions, MA, USA, pp. 908-921.
“Mining Association Rules Between Sets of Items in Large Database,” R. Agrawal, T. Imielinski, A. Swami, ACM-SIGMOD 93, Washington, D.C., pp. 207-216, May 1993.
“Fast Algorithms for Mining Association Rules,” R. Agrawal, R. Srikant, Proceedings of the International Conference on VLDB, Santiago, Chile, 13 pgs., Sep. 1994.
“Mining Quantitative Association Rules in Large Relational Tables,” R. Srikant, R. Agrawal, ACM-SIGMOND 96, Montreal, Canada, pp. 1-12, Jun. 1996.
“An Effective Hash-Based Algorithm for Mining Association Rules,” J.S. Park, M.S. Chen, P.S. Yu, ACM-SIGMOD 95, California, pp. 175-186, 1995.
“Multidimensional Access Methods,” V. Gaede, O. Gunther, ACM Computing Surveys, vol. 30, No. 2, pp. 171-231, Jun. 1998.
“The Quadtree and Related Hierarchical Data Structure,” H. Samet, ACM Computing Survey, vol. 16, No. 2, pp. 188-260, Jun. 1984.
“Quad Trees: A Data Structure for Retrieval of Composite Keys,” R.A. Finkel, J.L. Bentley, Acta Informatica, vol. 4, pp. 1-9, 1974.
Web site print-out: “What are HH-codes and how can they be used to store hydrographic date?,” H. Iverson, Norwegian Hydorgraphic Service (NHS), http://www.statkart.no
lhdb/iveher/hhtext.htm, 7 pgs., Jan. 1998.
“Run-Length Encodings,” S.W. Golomb, IEEE Trans. On Information Theory, vol. 12, No. 3, pp. 399-401, Jul. 1966.
“Mining Frequent Patterns Without Candidate Generation,” J. Han. J. Pei, Y. Yin, ACM-SIGMOD 2000, Dallas, Texas, pp. 1-12, May 2000.
“Spatial Data Mining: A Database Approach,” M. Ester, H-P. Kriegel, J. Sander, Proceedings of the Fifth International Symposium on Large Spatial Databases (SSD), Berlin, Germany, 20 pgs., 1997.
“Spatial Data Mining: Progress and Challenges Survey Paper,” K. Koperski, J. Adhikary, J. Han, Data Mining and Knowledge Discovery, 16 pgs., 1996.
“Spatial Data Mining: Database Primitives, Algorithms and Efficient DBMS Support,” M. Ester, A. Frommelt, H-P. Kriegel, J. Sander, Data Mining and Knowledge Discovery, 28 pgs., 1999.
“Discovery of Spatial Association Rules in Geographic Information Databases,” K. Koperski, J. Han, SSD, 20 pgs., 1995.
Web site print-out:SMILEY(Spatial Miner&Interface Language for Earth Yield), Database Systems Users & Research Group at NDSU (DataSURG) http://www.midas.cs.ndsu.nodak.edu/˜smiley, 5 pgs., undated.
“The Application of Association Rule Mining on Remotely Sensed Data,” J. Dong, W. Perrizo, Q. Ding, J. Zhou, Proceedings of ACM Symposium on Applied Computers, Italy, 6 pgs., Mar. 2000.
“Brute-Force Mining of High-Confidence Classification Rules,” R.J. Bayardo, Jr., Knowledge Discovery & Data Mining, pp. 123-126, 1997.
“Finding Interesting Associations Without Support Pruning,” E. Cohen, M. Datar, S. Fujiwara, A. Gionis, P. Indyk, R. Motwani, J. Ullman, C. Yang, Proceedings of 26th International Conference on Very Large Data Bases, Cairo, Egypt, 12 pgs., Sep. 2000.
“Growing Decision Trees on Support-Less Association Rules,” K. Wang S. Zhou, Y. He, 6thACM SIGKDD International Conference on Knowledge Discovery & Data Mining, Boston, Massachusetts, 5 pgs., Aug. 2000.
“Integrating Classification and Association Rule Mining,” B. Liu, W. Hsu, Y. Ma, The Fourth International Conference on Knowledge Discovery and Data Mining, New York, New York, 7 pgs., Aug. 1998.
“Inferring Decision Trees Using the Minimum Description Length Principle,” J.R. Quinlan, R.L. Rivest, Information and Computation, Academic Press, Inc., vol. 80, pp. 227-248, 1989.
“An Interval Classifier for Database Mining Applications,” R. Agrawal, S. Ghosh, T. Imielinski, B. Iyer, A. Swami, 18th International Conference on Very Large Data Bases, Vancouver, Canada, 14 pgs., Aug. 1992.
“SPRINT: A Scalable Parallel Classifier for Data Mining,” J. Shafer, R. Agrawal, M. Mehta, 22nd International Conference on Very Large Data Bases, Bombay, India, pp. 544-555, Sep. 1996.
“Fast Approach for Association Rule Mining for Remotely Sensed Imagery,” Q. Zhou, Q. Ding, W. Perrizo, Proceedings of the ISCA International Conference on Computers and Their Applications, New Orleans, Louisiana, 4 pgs., Mar. 2000.
“Automatic Subspace Clustering of High Dimensional Data for Data Mining Application,” R. Agrawal, J. Cehrke, D. Gunopulos, P. Raghavan, Proceedings of ACM SIGMOD International Conference on Management of Data, Seattle, Washington, 12 pgs., Jun. 1998.
“Efficient and Effective Clustering Method for Spatial Data Mining,” R. Ng, J. Han, Proceedings of the 20th International Conference on Very Large Data Bases, Santiago, Chile, 12 pgs., Sep. 1994.
“Constraint-Based Clustering in Large Databases,” A.K.H. Tung, J. Han, L.V.S. Lakshmanan, R.T. Ng, The 8th International Conference on Database Theory, London, United Kingdom, 15 pgs., Jan. 2001.
“Data Mining: An Overview from a Database Perspective,” M.S. Chen, J. Han, P.S. Yu, IEEE Transactions on Knowledge and Data Engineering, vol. 8, No. 6, pp. 1-40, Dec. 1996.
William Perrizo, “Request Order Linked List (ROLL): A Concurrency Control Object”, Proceedings of IEEE International Conference on Data Engineering, Apr. 11, 1991, Kobe, Japan, pp. 278-285.
William Perrizo, Joseph Rajkumar, and Prabhu Ram, “HYDRO: A Heterogeneous Distributed Database System”, ACM Conference on Management of Data (SIGMOD), Denver, CO, May, 1991, pp. 32-39.
William Perrizo, Lester I. McCann, Joseph Rajkumar, and Prabhu Ram, “Transaction Management in HYDRO: A Multi-database System”, IEEE-IPSJ MDBS-RIDE Workshop, Kyoto, Japan, Apr., 1991, pp. 279-279.
William Perrizo and Donald A. Varvel, “Some Alternative Algorithms to the Standard Locking Algorithm in Database Systems”, IEEE-ACM System Sci. Conf.; Honolulu, HI; Jan., 1986, pp. 633-642.
William Perrizo and Donald A. Varvel, “Efficient Computation of Optimal Transaction Processing in a Database System”, Computer Software and Applications, Chicago, IL; Oct., 1985, pp. 152-155.
William Perrizo, Min Luo, and Donald A. Varvel, “Ordering Accesses to Improve Transaction Processing Performance”, IEEE Conference on Data Engineering, Los Angeles, CA, Feb. 4, 1988, pp. 58-63.
William Perrizo and Russell Richter, “Concurrency Control Using an Extended Query Language”, Conference on Supercomputing, Santa Clara, CA, Apr. 30-May 5, 1989, pp. 436-442.
William Perrizo, “Distributed Window Request Order Linked List (DW-ROLL): Concurrency Control for Distributed and Multi-databases”, Computer Applications in Industry and Engineering, Honolulu, Dec., 1993, pp. 223-227.
Hossein Hakimzadeh, William Perrizo, Prabhu Ram,

Affiliated with

Also associated with

Rating

Concurrency control in high performance database systems does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Concurrency control in high performance database systems, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Concurrency control in high performance database systems will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFUS-PAI-O-3637351