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Temporal Vacuuming

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Encyclopedia of Database Systems
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Synonyms

Data expiration

Definition

Transaction-time temporal databases are inherently append-only resulting, over time, in a large historical sequence of database states. Data vacuuming allows for a strategic, and irrevocable, deletion of obsolete data.

Historical Background

The term vacuuming was first used in relation to databases in the Postgres database system as a mechanism for moving old data to archival storage [10]. It was later refined by Jensen and Mark in the context of temporal databases to refer to the removal of obsolete information [4] and subsequently developed into a comprehensive and usable adjunct to temporal databases [6,8,11]. Data expiration has also been investigated in the context of data warehouses by Garcia-Molina et al. [2] and others [9].

Foundations

In many applications, data about the past needs be retained for further use. This idea can be formalized, at least on the conceptual level, in terms of an append-only transaction-time temporal database or a history...

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Recommended Reading

  1. Chomicki J. Efficient checking of temporal integrity constraints using bounded history encoding. ACM Trans. Database Syst., 20(2):149–186, 1995.

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  2. Garcia-Molina H., Labio W., and Yang J. Expiring data in a warehouse. In Proc. 24th Int. Conf. on Very Large Data Bases, 1998, pp. 500–511.

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  3. Jensen C. Vacuuming. In The TSQL2 Temporal Query Language, Chapter 23, R. Snodgrass (ed.). Kluwer, New York, 1995, pp. 451–462.

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  4. Jensen C.S. and Mark L. A framework for vacuuming temporal databases. Tech. Rep. CS-TR-2516, University of Maryland at College Park, 1990.

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  5. Schmidt A., Jensen C., and Saltenis S. Expiration times for data management. In Proc. 22nd Int. Conf. on Data Engineering, 2006, p. 36.

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  6. Skyt J. Specification-Based Techniques for the Reduction of Temporal and Multidimensional Data. Ph.D thesis, Aalborg University, Aalborg, Denmark, 2001.

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  7. Skyt J. and Jensen C.S. Vacuuming temporal databases. TimeCenter technical report TR-32, Aalborg University, 1998.

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  8. Skyt J., Jensen C.S., and Mark L. A foundation for vacuuming temporal databases. Data Knowl. Eng., 44(1):1–29, 2003.

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  9. Skyt J., Jensen C.S., and Pedersen T.B. Specification-based data reduction in dimensional data warehouses. In Proc. 18th Int. Conf. on Data Engineering, 2002, p. 278.

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  10. Stonebraker M. and Rowe L. The design of POSTGRES. In Proc. ACM SIGMOD Int. Conf. on Management of Data, 1986, pp. 340–355.

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  11. Toman D. Expiration of historical databases. In Proc. 8th Int. Symp. Temporal Representation and Reasoning, 2001, pp. 128–135.

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  12. Toman D. Logical data expiration for fixpoint extensions of temporal logics. In Proc. 8th Int. Symp. Advances in Spatial and Temporal Databases, 2003, pp. 380–393.

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  13. Toman D. On incompleteness of multi-dimensional first-order temporal logics. In Proc. 10th Int. Symp. Temporal Representation and Reasoning/4th Int. Conf. Temporal Logic, 2003, pp. 99–106.

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  14. Toman D. On construction of holistic synopses under the duplicate semantics of streaming queries. In Proc. 14th Int. Symp. Temporal Representation and Reasoning, 2007, pp. 150–162.

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© 2009 Springer Science+Business Media, LLC

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F. Roddick, J., Toman, D. (2009). Temporal Vacuuming. In: LIU, L., ÖZSU, M.T. (eds) Encyclopedia of Database Systems. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-39940-9_1045

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