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Practical Algorithms for Tracking Database Join Sizes

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3821))

Abstract

We present novel algorithms for estimating the size of the natural join of two data streams that have efficient update processing times and provide excellent quality of estimates.

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References

  1. Alon, N., Gibbons, P.B., Matias, Y., Szegedy, M.: Tracking Join and Self- Join Sizes in Limited Storage. In: Proceedings of the Eighteenth ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, Philadeplphia, Pennsylvania (May 1999)

    Google Scholar 

  2. Alon, N., Matias, Y., Szegedy, M.: The Space Complexity of Approximating the Frequency Moments. In: Proceedings of the 28th Annual ACM Symposium on the Theory of Computing STOC 1996, Philadelphia, Pennsylvania, pp. 20–29 (May 1996)

    Google Scholar 

  3. Alon, N., Matias, Y., Szegedy, M.: The space complexity of approximating frequency moments. Journal of Computer Systems and Sciences 58(1), 137–147 (1998)

    Article  MathSciNet  Google Scholar 

  4. Arasu, A., Babcock, B., Babu, S., Cieslewicz, J., Datar, M., Ito, K.: STREAM: The Stanford Data Stream Management System. In: Garofalakis, M., Gehrke, J., Rastogi, R. (eds.) Data Stream Management Processing High-Speed Data Streams Series: Data-Centric Systems and Applications, Springer, Heidelberg (2006) ISBN: 3-540-28607-1

    Google Scholar 

  5. Avnur, R., Hellerstein, J.M.: Eddies: Continuously Adaptive Query Processing. In: Proceedings of the 2000 ACM SIGMOD International Conference on Management of Data, Dallas, Texas, USA (2000)

    Google Scholar 

  6. Babcock, B., Babu, S., Datar, M., Motwani, R., Widom, J.: Models and Issues in Data Stream Systems. In: Proceedings of the Twentysecond ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, Madison, Wisconsin, USA (2002)

    Google Scholar 

  7. Carney, D., Çetintemel, U., Cherniack, M., Convey, C., Lee, S., Seidman, G., Stonebraker, M., Tatbul, N., Zdonik, S.B.: Monitoring Streams - A New Class of Data Management Applications. In: Proceedings of the 28th International Conference on Very Large Data Bases, Hong Kong, China (2002)

    Google Scholar 

  8. Charikar, M., Chen, K., Farach-Colton, M.: Finding frequent items in data streams. In: Proceedings of the 29th International Colloquium on Automata Languages and Programming (2002)

    Google Scholar 

  9. Cormode, G., Muthukrishnan, S.: An improved data stream summary: The Count-Min sketch and its applications. In: Farach-Colton, M. (ed.) LATIN 2004. LNCS, vol. 2976, pp. 29–38. Springer, Heidelberg (2004) ISBN 3-540-21258- 2

    Chapter  Google Scholar 

  10. Cormode, G., Garofalakis, M.: Sketching Streams Through the Net: Distributed Approximate Query Tracking. In: Proceedings of the 31st International Conference on Very Large Data Bases (September 2005)

    Google Scholar 

  11. Dobra, A., Garofalakis, M.N., Gehrke, J., Rastogi, R.: Processing complex aggregate queries over data streams. In: Proceedings of the 2002 ACM SIGMOD International Conference on Management of Data, Madison, Wisconsin, USA (2002)

    Google Scholar 

  12. Ganguly, S., Garofalakis, M., Rastogi, R.: Processing Data Stream Join Aggregates using Skimmed Sketches. In: Proceedings of the Ninth International Conference on Extending Database Technology, Herkailon, Crete, Greece (March 2004)

    Google Scholar 

  13. Ganguly, S., Gibbons, P., Matias, Y., Silberschatz, A.: Bifocal Sampling for Skew-Resistant Join Size Estimation. In: Proceedings of the 1996 ACM SIGMOD International Conference on Management of Data, Montreal, Quebec (June 1996)

    Google Scholar 

  14. Hou, W.-C., Ozsoyoglu, G., Taneja, B.K.: Statistical estimators for relational algebra expressions. In: Proceedings of the Seventh ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, Philadelphia, Pennsylvania, March 1988, pp. 276–287 (1988)

    Google Scholar 

  15. Lipton, R., Naughton, J., Schneider, D.: Practical Selectivity Estimation Through Adaptive Sampling. In: Proceedings of the 1990 ACM SIGMOD International Conference on Management of Data, Atlantic City, NJ (1990)

    Google Scholar 

  16. Thorup, M., Zhang, Y.: Tabulation based 4-universal hashing with applications to second moment estimation. In: Proceedings of the Fifteenth ACM SIAM Symposium on Discrete Algorithms, New Orleans, Louisiana, USA, pp. 615–624 (January 2004)

    Google Scholar 

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© 2005 Springer-Verlag Berlin Heidelberg

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Ganguly, S., Kesh, D., Saha, C. (2005). Practical Algorithms for Tracking Database Join Sizes. In: Sarukkai, S., Sen, S. (eds) FSTTCS 2005: Foundations of Software Technology and Theoretical Computer Science. FSTTCS 2005. Lecture Notes in Computer Science, vol 3821. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11590156_24

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  • DOI: https://doi.org/10.1007/11590156_24

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-30495-1

  • Online ISBN: 978-3-540-32419-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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