Skip to main content

Hierarchical Heavy Hitter Mining on Streams

  • Reference work entry
  • First Online:
Encyclopedia of Database Systems
  • 15 Accesses

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 4,499.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 6,499.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Recommended Reading

  1. Cheung-Mon-Chan P, Clerot F. Finding hierarchical heavy hitters with the count min sketch. In: Proceedings of the International Workshop on Internet Rent, Simulation, Monitoring, Measurement; 2006.

    Google Scholar 

  2. Cormode G, Korn F, Muthukrishnan S, Srivastava D. Finding hierarchical heavy hitters in data streams. In: Proceedings of the 29th International Conference on Very Large Data Bases; 2003. p. 464–75.

    Chapter  Google Scholar 

  3. Cormode G, Korn F, Muthukrishnan S, Srivastava D. Diamond in the rough: finding hierarchical heavy hitters in multi-dimensional data. In: Proceedings of the ACM SIGMOD International Conference on Management of Data; 2004. p. 155–66.v

    Google Scholar 

  4. Cormode G, Korn F, Muthukrishnan S, Johnson T, Spatscheck O, Srivastava D. Holistic UDAFs at streaming speeds. In: Proceedings of the ACM SIGMOD International Conference on Management of Data; 2004. p. 35–46.

    Google Scholar 

  5. Cormode G, Korn F, Muthukrishnan S, Srivastava D Finding hierarchical heavy hitters in streaming data. ACM Trans Knowl Discov Data. 2008;1(4): 1–48.

    Article  Google Scholar 

  6. Demaine E, López-Ortiz A, and Munro JI. Frequency estimation of internet packet streams with limited space. In: Proceedings of the 10th Annual European Symposium on Algorithms; 2002. p. 348–60.

    Chapter  Google Scholar 

  7. Estan C, Savage S, Varghese G. Automatically inferring patterns of resource consumption in network traffic. In: Proceedings of the ACM International Conference on Data Communication; 2003. p. 137–48.

    Google Scholar 

  8. Estan C, Magin G. Interactive traffic analysis and visualization with Wisconsin netpy. In: Proceedings of the International Conference on Large Installation System Administration; 2005. p. 177–84.

    Google Scholar 

  9. Hershberger J, Shrivastava N, Suri S, Toth C. Space complexity of hierarchical heavy hitters in multi-dimensional data streams. In: Proceedings of the ACM SIGACT-SIGMOD Symposium on Principles of Database Systems; 2005. p. 338–347.

    Google Scholar 

  10. Manku GS, Motwani R. Approximate frequency counts over data streams. In: Proceedings of the 28th International Conference on Very Large Data Bases; 2002. p. 346–57.

    Chapter  Google Scholar 

  11. Misra J, Gries D. Finding repeated elements. Sci Comput Program. 1982;2(2):143–52.

    Article  MathSciNet  MATH  Google Scholar 

  12. Sekar V, Duffield N, Spatscheck O, van der Merwe J, Zhang H. LADS: large-scale automated DDoS detection system. In: Proceedings of the USENIX 2006 Annual Technical Conference, General Track; 2006. p. 171–84.

    Google Scholar 

  13. Zhang Y, Singh S, Sen S, Duffield N, Lund C. Online identification of hieararchical heavy hitters: algorithms, evaluation and applications. In: Proceedings of the 4th ACM SIGCOMM Conference on Internet Measurement; 2004. p. 135–48.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Flip R. Korn .

Editor information

Editors and Affiliations

Section Editor information

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Science+Business Media, LLC, part of Springer Nature

About this entry

Check for updates. Verify currency and authenticity via CrossMark

Cite this entry

Korn, F.R. (2018). Hierarchical Heavy Hitter Mining on Streams. In: Liu, L., Özsu, M.T. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8265-9_190

Download citation

Publish with us

Policies and ethics