Encyclopedia of Database Systems

2018 Edition
| Editors: Ling Liu, M. Tamer Özsu

Bloom Filters

  • Michael MitzenmacherEmail author
Reference work entry
DOI: https://doi.org/10.1007/978-1-4614-8265-9_751


Hash filter


A Bloom filter is a simple, space-efficient randomized data structure based on hashing that represents a set in a way that allows membership queries to determine whether an element is a member of the set. False positives are possible, but not false negatives. In many applications, the space savings afforded by Bloom filters outweigh the drawbacks of a small probability for a false positive. Various extensions of Bloom filters can be used to handle alternative settings, such as when elements can be inserted and deleted from the set, and more complex queries, such as when each element has an associated function value that should be returned.

Historical Background

Burton Bloom introduced what is now called a Bloom filter in his 1970 paper [1], where he described the technique as an extension of hash-coding methods for applications where error-free methods require too much space and were not strictly necessary. The specific application he considered...

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Recommended Reading

  1. 1.
    Bloom B. Space/time tradeoffs in hash coding with allowable errors. Commun ACM. 1970;13(7):422–6.zbMATHCrossRefGoogle Scholar
  2. 2.
    McIlroy MD. Development of a spelling list. IEEE Trans Commun. 1982;30(1):91–9.CrossRefGoogle Scholar
  3. 3.
    Mullin JK, Margoliash DJ. A tale of three spelling checkers. Software Pract Exp. 1990;20(6):625–30.CrossRefGoogle Scholar
  4. 4.
    Spafford EH. Opus: preventing weak password choices. Comp Sec. 1992;11(3):273–8.CrossRefGoogle Scholar
  5. 5.
    Babb E. Implementing a relational database by means of specialized hardware. ACM Trans Database Syst. 1979;4(1):1–29.CrossRefGoogle Scholar
  6. 6.
    Bratbergsengen K. Hashing methods and relational algebra operations. In: Proceedings of the 10th International Conference on Very Large Data Bases; 1984. p. 323–33.Google Scholar
  7. 7.
    Mackett LF, Lohman GM. R* optimizer validation and performance evaluation for distributed queries. In: Proceedings 27th International Conference on Very Large Data Bases; 1986. p. 149–59.Google Scholar
  8. 8.
    Cormode G, Muthukrishnan S. An improved data stream summary: the count-min sketch and its applications. J Algorithms. 2003;55(1):58–75.MathSciNetzbMATHCrossRefGoogle Scholar
  9. 9.
    Fan L, Cao P, Almeida J, Broder AZ. Summary cache: a scalable wide-area Web cache sharing protocol. IEEE/ACM Trans Network. 2000;8(3):281–93.CrossRefGoogle Scholar
  10. 10.
    Broder A, Mitzenmacher M. Network applications of Bloom filters: a survey. Internet Math. 2005;1(4):485–509.MathSciNetzbMATHCrossRefGoogle Scholar
  11. 11.
    Mullin JK. Estimating the size of a relational join. Inf Syst. 1993;18(3):189–96.CrossRefGoogle Scholar
  12. 12.
    Gremilion LL. Designing a Bloom filter for differential file access. Commun ACM. 1982;25(9):600–4.CrossRefGoogle Scholar
  13. 13.
    Mitzenmacher M. Compressed Bloom filters. IEEE/ACM Trans Network. 2002;10(5):604–12.zbMATHCrossRefGoogle Scholar
  14. 14.
    Cohen S, Matias Y. Spectral Bloom filters. In: Proceedings of the ACM SIGMOD International Conference on Management of Data; 2003. p. 241–52.Google Scholar
  15. 15.
    Chazelle B, Kilian J, Rubinfeld R, Tal A. The Bloomier filter: an efficient data structure for static support lookup tables. In: Proceedings of the 15th Annual ACM-SIAM Symposium on Discrete Algorithms; 2004. p. 30–9.Google Scholar
  16. 16.
    Bonomi F, Mitzenmacher M, Panigrahy R, Singh S, Varghese G. Beyond Bloom filters: from approximate membership checks to approximate state machines. Comput Commun Rev. 2006;36(4):315–26.CrossRefGoogle Scholar

Copyright information

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

Authors and Affiliations

  1. 1.Harvard UniversityBostonUSA

Section editors and affiliations

  • Vassilis J. Tsotras
    • 1
  1. 1.University of California-RiversideRiversideUSA