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Continuous queries over append-only databases
Abstract
In a database to which data is continually added, users may wish to issue a permanent query and be notified whenever data matches the query. If such continuous queries examine only single records, this can be implemented by examining each record as it arrives. This is very efficient because only the incoming record needs to be scanned. This simple approach does not work for queries involving joins or time. The Tapestry system allows users to issue such queries over a database of mail and bulletin board messages. The user issues a static query, such as “show me all messages that have been replied to by Jones,” as though the database were fixed and unchanging. Tapestry converts the query into an incremental query that efficiently finds new matches to the original query as new messages are added to the database. This paper describes the techniques used in Tapestry, which do not depend on triggers and thus be implemented on any commercial database that supports SQL. Although Tapestry is designed for filtering mail and news messages, its techniques are applicable to any append-only database.
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Cited by
Streams and Tables: Two Sides of the Same Coin
Sax, M. J., Wang, G., Weidlich, M., & Freytag, J.-C. (2018) · Proceedings of the International Workshop on Real-Time Business Intelligence and Analytics · doi:10.1145/3242153.3242155 · Cited by 51
Metadata
- Authors
- Terry, D., Goldberg, D., Nichols, D., & Oki, B.
- Venue
- Proceedings of the 1992 ACM SIGMOD international conference on Management of data
- Publisher
- ACM
- Published
- 1992-06
- Pages
- 321-330
- ISSN
- 0730-8078 (ISSN-L)
- OpenAlex
- W2002110561
- Cited by
- 399
- References
- 0
- FWCI
- 3.27
- Type
- conference paper
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Continuous queries over append-only databases. https://app.cochat.ai/papers/10.1145/130283.130333
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- Terry, D., Goldberg, D., Nichols, D., & Oki, B. (1992). Continuous queries over append-only databases. Proceedings of the 1992 ACM SIGMOD international conference on Management of data. https://doi.org/10.1145/130283.130333
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
