Abstract
Ranking-aware queries, or top-k queries, have received much attention recently in various contexts such as web, multimedia retrieval, relational databases, and distributed systems. Top-k queries play a critical role in many decision-making related activities such as, identifying interesting objects, network monitoring, load balancing, etc. In this paper, we study the ranking aggregation problem in distributed systems. Prior research addressing this problem did not take data distributions into account, simply assuming the uniform data distribution among nodes, which is not realistic for real data sets and is, in general, inefficient. In this paper, we propose three efficient algorithms that consider data distributions in different ways. Our extensive experiments demonstrate the advantages of our approaches in terms of bandwidth consumption.
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This research was supported by the NSF grants under IIS-02-23022, CNF-04-23336, and EIA-00-80134.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Babcock, B., Olston, C.: Distributed top-k monitoring. In: Proc. of Intl. Conf. on Managment of Data (SIGMOD), pp. 563–574 (2003)
Balke, W.-T., Nejdl, W., Siberski, W., Thaden, U.: Progressive distributed top-k retrieval in peer-to-peer networks. In: Proc. of Intl. Conf. on Data Engineering, ICDE (2005) (to appear)
Bruno, N., Chaudhuri, S., Gravano, L.: Top-k selection queries over relational databases: Mapping strategies and performance evaluation. ACM Trans. on Database Systems 27(2), 153–187 (2002)
Cao, P., Wang, Z.: Efficient top-k query calculation in distributed networks. In: Proc. of Intl. Symposium on Principles Of Distributed Computing (PODC), pp. 206–215 (2004)
Chaudhuri, S., Gravano, L.: Evaluating top-k selection queries. In: Proc. of Intl. Conf. on Very Large Data Bases (VLDB), pp. 397–410 (1999)
Fagin, R.: Combining fuzzy information from multiple systems. In: Proc. of Intl. Symp. on Principles of Database Systems (PODS), pp. 216–226 (1996)
Fagin, R., Lotem, A., Naor, M.: Optimal aggregation algorithms for middleware. In: Proc. of Intl. Symposium on Principles of Database Systems (PODS), pp. 102–113 (2001)
Guntzer, U., Balke, W.-T., Kiessling, W.: Optimizing multi-feature queries in image databases. In: Proc. of Intl. Conf. on Very Large Data Bases (VLDB), pp. 419–428 (2000)
Ilyas, I.F., Aref, W.G., Elmagarmid, A.K.: Supporting top-k join queries in relational databases. In: Proc. of Intl. Conf. on Very Large Data Base (VLDB), pp. 754–765 (2003)
Ilyas, I.F., Shah, R., Aref, W.G., Vitter, J.S., Elmagarmi, A.K.: Rank-aware query optimization. In: Proc. of Intl. Conf. on Managment of Data (SIGMOD), pp. 203–214 (2004)
Nepal, S., Ramakrishna, M.V.: Query processing issues in image (multimedia) databases. In: Proc. of Intl. Conf. on Data Engineering (ICDE), pp. 22–31 (1999)
Poosala, W., Haas, P.J., Ioannidis, Y.E., Shekita, E.J.: Improved histograms for selectivity estimation of range predicates. In: Proc. of Intl. Conf. on Management of Data (SIGMOD), pp. 294–305 (1996)
Theobald, M., Weikum, G., Schenkel, R.: Top-k query evaluation with probabilistic guarantees. In: Proc. of Intl. Conf. on Very Large Data Bases (VLDB), pp. 648–659 (2004)
Tsaparas, P., Palpanas, T., Kotidis, Y., Koudas, N., Srivastava, D.: Ranked join indices. In: Proc. of Intl. Conf. on Data Engineering (ICDE), pp. 277–288 (2003)
Yi, K., Yu, H., Yang, J., Xia, G., Chen, Y.: Efficient maintenance of materialized top-k views. In: Proc. of Intl. Conf. on Data Engineering (ICDE), pp. 189–200 (2003)
Yu, H., Li, H.-G., Wu, P., Agrawal, D., El Abbadi, A.: Efficient processing of distributed top-k queries. Technical Report 2005-14, University of California at Santa Barbara (2005), http://www.cs.ucsb.edu/research/trcs/docs/2005-14.pdf
Zipf, G.K.: Human Behaviour and the Principle of Least Effort: an Introduction to Human Ecology. Addison-Wesley, Reading (1949)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Yu, H., Li, HG., Wu, P., Agrawal, D., El Abbadi, A. (2005). Efficient Processing of Distributed Top-k Queries. In: Andersen, K.V., Debenham, J., Wagner, R. (eds) Database and Expert Systems Applications. DEXA 2005. Lecture Notes in Computer Science, vol 3588. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11546924_7
Download citation
DOI: https://doi.org/10.1007/11546924_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28566-3
Online ISBN: 978-3-540-31729-6
eBook Packages: Computer ScienceComputer Science (R0)