The threshold algorithm: From middleware systems to the relational engine

IEEE Transactions on Knowledge and Data Engineering

Volumn 19, Issue 4, 2007, Pages 523-537

  Bruno, Nicolas ^a   Wang, Hui ^b  

^a MICROSOFT RESEARCH   (United States)

^b UNIVERSITY OF BRITISH COLUMBIA   (Canada)

Author keywords

Query processing; Relational databases; Retrieval models; Search process

Indexed keywords

COST MODELS; EXPERIMENTAL EVALUATIONS; MEMORY REQUIREMENTS; MIDDLEWARE SYSTEMS; OPTIMIZERS; ORDERED SETS; RELATIONAL DATABASES; RELATIONAL DATUM; RETRIEVAL MODELS; SEARCH PROCESS; TERMINATION CONDITIONS; THRESHOLD ALGORITHMS; TOP-K QUERIES;

ALGORITHMS; INFORMATION RETRIEVAL; MIDDLEWARE; QUERY PROCESSING; SET THEORY;

RELATIONAL DATABASE SYSTEMS;

EID: 50249153108     PISSN: 10414347     EISSN: None     Source Type: Journal    
DOI: 10.1109/TKDE.2007.1011     Document Type: Article

References (17)

1. G. Salton, Automatic Text Processing: The Transformation, Analysis, and Retrieval of Information by Computer. Addison-Wesley, 1989.
2. D. Aksoy and M. Franklin, "RxW: A Scheduling Approach for Large-Scale On-Demand Data Broadcast," ACM Trans. Networking, vol. 7, no. 6, pp. 846-860, 1999.
3. A. Marian, N. Bruno, and L. Gravano, "Evaluating Top-k Queries over Web-Accessible Databases," ACM Trans. Database Systems (TODS), vol. 29, no. 2, pp. 319-362, 2004.
4. R. Fagin, A. Lotem, and M. Naor, "Optimal Aggregation Algorithms for Middleware," Proc. 20th ACM Symp. Principles of Database Systems, pp. 102-113, 2001.
5. I. Ilyas et al., "Rank-Aware Query Optimization," Proc. ACM lnt'1 Conf. Management of Data (SIGMOD), pp. 203-214, 2004.
6. M.J. Carey and D. Kossmann, "On Saying 'Enough Already!' in SQL," Proc. 1997 ACM Int'l Conf. Management of Data (SIGMOD), pp. 219-230, 1997.
7. N. Bruno, S. Chaudhuri, and L. Gravano, "Top-k Selection Queries over Relational Databases: Mapping Strategies and Performance Evaluation," ACM Trans. Database Systems (TODS), vol. 27, no. 2, pp. 153-187, 2002.
8. C.-M. Chen and Y. Ling, "A Sampling-Based Estimator for Top-k Query," Proc. Int'l Conf. Data Eng. (ICDE), pp. 617-627, 2002.
9. U. Güntzer, W.-T. Balke, and W. Kießling, "Optimizing Multi- Feature Queries for Image Databases," Proc. Int'l Conf. Very Large Databases, pp. 419-428, 2000.
10. S. Nepal and M.V. Ramakrishna, "Query Processing Issues in Image (Multimedia) Databases," Proc. Int'l Conf. Data Eng., pp. 22- 29, 1999.
11. K. Chang and S. won Hwang, "Minimal Probing: Supporting Expensive Predicates for Top-k Queries," Proc. ACM Int'l Conf. Management of Data (SIGMOD), pp. 346-357, 2002.
12. E. Wimmers, L. Haas, M.T. Roth, and C. Braendli, "Using Fagin's Algorithm for Merging Ranked Results in Multimedia Middle- ware," Proc. Int'l Conf. Cooperative Information Systems (CoopIS), pp. 267-278, 1999.
13. R. Fagin, "Combining Fuzzy Information from Multiple Systems," Proc. 15th ACM Symp. Principles of Database Systems (PODS '96), pp. 216-226, 1996.
14. C. Lang, Y.-C. Chang, and J. Smith, "Making the Threshold Algorithm Access Cost Aware," IEEE Trans. Knowledge and Data Eng., vol. 16, no. 10, pp. 1297-1301, Oct. 2004.
15. N. Bruno, S. Chaudhuri, and L. Gravano, "STHoles: A Multi- dimensional Workload-Aware Histogram," Proc. ACM Int'l Conf. Management of Data (SIGMOD), pp. 211-222, 2001.
16. D. Gunopulos et al., "Approximating Multi-Dimensional Aggre- gate Range Queries over Real Attributes," Proc. ACM Int'l Conf. Management of Data (SIGMOD), pp. 463-474, 2000.
17. C. Blake and C. Merz, "UCI Repository of Machine Learning Databases," 1998, ftp://ftp.ics.uci.edu/pub/machine-learning-database/ covtype.