Abstract
Motivated by the increasing prominence of loosely-coupled systems, such as mobile and sensor networks, the characteristics of which include intermittent connectivity and volatile data, we study the tagging of data with so-called expiration times. More specifically, when data are inserted into a database, they may be stamped with time values indicating when they expire, i.e. when they are regarded as stale or invalid and thus are no longer considered part of the database. In a number of applications, expiration times are known and can be assigned at insertion time. We present data structures and algorithms for online management of data stamped with expiration times. The algorithms are based on fully functional treaps, which are a combination of binary search trees with respect to a primary attribute and heaps with respect to a secondary attribute. The primary attribute implements primary keys, and the secondary attribute stores expiration times in a minimum heap, thus keeping a priority queue of tuples to expire. A detailed and comprehensive experimental study demonstrates the well-behavedness and scalability of the approach as well as its efficiency with respect to a number of competitors.
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Ailamaki, A., DeWitt, D., Hill, M.: Data page layouts for relational databases on deep memory hierarchies. The VLDB Journal 11, 198–215 (2002)
Arasu, A., Babu, S., Widom, J.: CQL: A Language for Continuous Queries over Streams and Relations. In: Lausen, G., Suciu, D. (eds.) DBPL 2003. LNCS, vol. 2921, pp. 1–19. Springer, Heidelberg (2004)
Bass, L., Clements, P., Kazman, R.: Software Architecture in Practice. Addison-Wesley, Reading (2003)
Bernstein, P., Hadzilacos, V., Goodman, N.: Concurrency Control and Recovery in Database Systems. Addison-Wesley, Reading (1987)
Codd, E.F.: A Relational Model of Data for Large Shared Data Banks. Comm. ACM 13, 377–387 (1970)
Diwan, A., Tarditi, D., Moss, J.: Memory System Performance of Programs with Intensive Heap Allocation. ACM TOCS 13, 244–273 (1995)
Driscoll, J., Sarnak, N., Sleator, D., Tarjan, R.: Making Data Structures Persistent. Journal of Computer and System Sciences 38, 86–124 (1989)
Garcia-Molina, H., Labio, W., Yang, J.: Expiring Data in a Warehouse. In: Proc. VLDB, pp. 500–511 (1998)
Jensen, C.S.: Vacuuming. The TSQL2 Temporal Query Language, 447–460 (1995)
Jensen, C.S., Lomet, D.: Transaction Timestamping in (Temporal) Databases. In: Proc. VLDB, pp. 441–450 (2001)
Knuth, D.: The Art of Computer Programming. Sorting and Searching, vol. 3. Addison-Wesley, Reading (1998)
Lehman, T., Carey, M.: Query Processing in Main Memory Database Management Systems. In: Proc. ACM SIGMOD, pp. 239–250 (1986)
Lomet, D., Salzberg, B.: Access Methods for Multiversion Data. In: Proc. ACM SIGMOD, pp. 315–324 (1989)
McCreight, E.: Priority Search Trees. SIAM Journal on Computing 14, 257–276 (1985)
Odersky, M., et al.: The Scala Programming Language (2005), http://scala.epfl.ch
Okasaki, C.: Purely Functional Data Structures. Cambridge University Press, Cambridge (1998)
Schmidt, A., Jensen, C.S., Šaltenis, S.: Expiration Times for Data Management. IEEE ICDE ( to appear, 2006)
Schmidt, A., Jensen, C.S.: Efficient Management of Short-Lived Data. Technical Report (2005), http://arxiv.org/abs/cs.DB/0505038
Seidel, R., Aragon, C.: Randomized Search Trees. Algorithmica 16(4/5), 464–497 (1996)
The World Wide Web Consortium. HTTP - Hypertext Transfer Protocol (2005), http://www.w3.org/Protocols/
Šaltenis, S., Jensen, C.S.: Indexing of Moving Objects for Location-Based Services. In: Proc. IEEE ICDE, pp. 463–472 (2002)
Wang, M., Chan, N., Papadimitriou, S., Faloutsos, C., Madhyastha, T.: Data Mining Meets Performance Evaluation: Fast Algorithms for Modeling Bursty Traffic. In: Proc. IEEE ICDE, pp. 507–516 (2002)
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Schmidt, A., Jensen, C.S. (2006). Efficient Maintenance of Ephemeral Data. In: Li Lee, M., Tan, KL., Wuwongse, V. (eds) Database Systems for Advanced Applications. DASFAA 2006. Lecture Notes in Computer Science, vol 3882. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11733836_12
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DOI: https://doi.org/10.1007/11733836_12
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