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The state of the art in distributed query processing
Abstract
Distributed data processing is becoming a reality. Businesses want to do it for many reasons, and they often must do it in order to stay competitive. While much of the infrastructure for distributed data processing is already there (e.g., modern network technology), a number of issues make distributed data processing still a complex undertaking: (1) distributed systems can become very large, involving thousands of heterogeneous sites including PCs and mainframe server machines; (2) the state of a distributed system changes rapidly because the load of sites varies over time and new sites are added to the system; (3) legacy systems need to be integrated—such legacy systems usually have not been designed for distributed data processing and now need to interact with other (modern) systems in a distributed environment. This paper presents the state of the art of query processing for distributed database and information systems. The paper presents the “textbook” architecture for distributed query processing and a series of techniques that are particularly useful for distributed database systems. These techniques include special join techniques, techniques to exploit intraquery paralleli sm, techniques to reduce communication costs, and techniques to exploit caching and replication of data. Furthermore, the paper discusses different kinds of distributed systems such as client-server, middleware (multitier), and heterogeneous database systems, and shows how query processing works in these systems.
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Cited by
TinyDB: an acquisitional query processing system for sensor networks
Madden, S. R., Franklin, M. J., Hellerstein, J. M., & Hong, W. (2005) · ACM Transactions on Database Systems · doi:10.1145/1061318.1061322 · Cited by 1,899
Survey of research towards robust peer-to-peer networks: Search methods
Risson, J., & Moors, T. (2006) · Computer Networks · doi:10.1016/j.comnet.2006.02.001 · Cited by 386
A taxonomy of Data Grids for distributed data sharing, management, and processing
Venugopal, S., Buyya, R., & Ramamohanarao, K. (2006) · ACM Computing Surveys · doi:10.1145/1132952.1132955 · Cited by 351
Low Latency Geo-distributed Data Analytics
Pu, Q., Ananthanarayanan, G., Bodik, P., Kandula, S., Akella, A., Bahl, P., & Stoica, I. (2015) · Proceedings of the 2015 ACM Conference on Special Interest Group on Data Communication · doi:10.1145/2785956.2787505 · Cited by 246
A survey of structured P2P systems for RDF data storage and retrieval
Filali, I., Bongiovanni, F., Huet, F., & Baude, F. (2011) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-23074-5_2 · Cited by 19
Metadata
- Authors
- Kossmann, D.
- Venue
- ACM Computing Surveys
- Published
- 2000-12
- Volume
- 32
- Issue
- 4
- Pages
- 422-469
- ISSN
- 0360-0300 (ISSN-L)
- 1557-7341
- OpenAlex
- W2112101330
- Cited by
- 813
- References
- 0
- FWCI
- 32.01
- Type
- journal article
- Language
- en
- Open access
- closed
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- Kossmann, D. (2000). The state of the art in distributed query processing. ACM Computing Surveys. https://doi.org/10.1145/371578.371598
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