Optimizing multiple top-k queries over joins

Proceedings of the International Conference on Scientific and Statistical Database Management, SSDBM

Volumn , Issue , 2005, Pages 195-204

  Habich, Dirk ^a   Lehner, Wolfgang ^a   Hinneburg, Alexander ^b  

^a DRESDEN UNIVERSITY OF TECHNOLOGY   (Germany)

^b MARTIN LUTHER UNIVERSITY HALLE WITTENBERG   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

CLUSTERING APPLICATIONS; DATA MINING APPLICATIONS; HASH JOIN; HIGH DIMENSIONAL FEATURE; PROJECTED CLUSTERING; RANKING CRITERION; RELATIONAL DATABASE; TOP-K QUERY;

INFORMATION RETRIEVAL; MANAGEMENT INFORMATION SYSTEMS;

OPTIMIZATION;

EID: 74849132276     PISSN: 10993371     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (13)

1. Nicolas Bruno, Suraji Chaudhuri, and Luis Gravano. Top-k selection queries over relational databases: Mapping strategies and performance evaluation. ACM Trans. Database Syst., 27(2):153-187, 2002.
2. Nicolas Bruno, Luis Gravano, and Aḿelie Marian. Evaluating top-k queries over web-accessible databases. In Proceedings of the 18th International Conference on Data Engineering, pages 369-, 2002.
3. Michael J. Carey and Donald Kossmann. On saying "enough already!" in sql. In Proceedings of the 1997 ACM SIGMOD international conference on Management of data, pages 219-230. ACM Press, 1997.
4. Michael J. Carey and Donald Kossmann. Reducing the braking distance of an sql query engine. In Proceedings of 24rd International Conference on Very Large Data Bases, pages 158-169. Morgan Kaufmann, 1998.
5. Surajit Chaudhuri and Luis Gravano. Evaluating top-k selection queries. In Proceedings of 25th International Conference on Very Large Data Bases, pages 397-410, 1999.
6. Chung-Min Chen and Yibei Ling. A sampling-based estimator for top-k query. In Proceedings of the 18th International Conference on Data Engineering, pages 617-629, 2002.
7. Donko Donjerkovic and Raghu Ramakrishnan. Probabilistic optimization of top n queries. In VLDB'99, Proceedings of 25th International Conference on Very Large Data Bases, September 7-10, 1999, Edinburgh, Scotland, UK, pages 411- 422. Morgan Kaufmann, 1999.
8. Ronald Fagin, Amnon Lotem, and Moni Naor. Optimal aggregation algorithms for middleware. In Proceedings of the Twentieth ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, 2001.
9. Vagelis Hristidis, Nick Koudas, and Yannis Papakonstantinou. Prefer: A system for the efficient execution of multiparametric ranked queries. In Proceedings of the 2001 ACM SIGMOD international conference on Management of data, pages 259-270. ACM Press, 2001.
10. Ihab F. Ilyas, Walid G. Aref, and Ahmed K. Elmagarmid. Supporting top-k join queries in relational databases. In Proceedings of 29th International Conference on Very Large Data Bases (VLDB'03, September 9-12, 2003, Berlin, Germany), pages 754-765, 2003.
11. Ihab F. Ilyas, Walid G. Aref, and Ahmed K. Elmagarmid. Supporting top-k join queries in relational databases. VLDB Journal, 13(3):207-221, 2004.
12. Deok-Hwan Kim and Chin-Wan Chung. Qcluster: relevance feedback using adaptive clustering for content-based image retrieval. In Proceedings of the 2003 ACM SIGMOD international conference on on Management of data, pages 599- 610, 2003.
13. Giedrius Slivinskas, Christian S. Jensen, and Richard T. Snodgrass. Bringing order to query optimization. SIGMOD Rec., 31(2):5-14, 2002.