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A Bloom filter is a probabilistic data structure designed to tell, rapidly and memory-efficiently, whether an element is in the set or no.

If we can use hash tables where we have O(1) in best time, O(n) in a very bad situations. Why do we need a new abstract data structure that look-up for an element with less certainty. What are the scenarios where HashTables fails and demands the use of bloom filters?

When should bloom filters be used over hashtables and vice-versa?

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The second paragraph of the Wikipedia article on Bloom filters says the following, with a citation to Bloom's original 1970 paper.

Bloom proposed the technique for applications where the amount of source data would require an impracticably large hash area in memory if "conventional" error-free hashing techniques were applied. He gave the example of a hyphenation algorithm for a dictionary of 500,000 words, out of which 90% follow simple hyphenation rules, but the remaining 10% require expensive disk accesses to retrieve specific hyphenation patterns. With sufficient core memory, an error-free hash could be used to eliminate all unnecessary disk accesses; on the other hand, with limited core memory, Bloom's technique uses a smaller hash area but still eliminates most unnecessary accesses. For example, a hash area only 15% of the size needed by an ideal error-free hash still eliminates 85% of the disk accesses.


Burton H. Bloom, Space/Time Trade-offs in Hash Coding with Allowable Errors. Communications of the ACM 13(7): 422–426, 1970. (DOI)

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    $\begingroup$ 1970! I though it's a modern data structure. In case you know, what are the most used probabilistic data structures? $\endgroup$ – user3378649 Oct 24 '14 at 10:00
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    $\begingroup$ @user3378649 That's a separate question and should be asked as such. $\endgroup$ – David Richerby Oct 24 '14 at 10:48
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    $\begingroup$ @user3378649 In fact, most data structures in actual use, modern or not, were invented before 1980. It turns out that there seems to be only so many useful ones. (there are an infinite number of not-so-useful ones) $\endgroup$ – RBarryYoung Oct 24 '14 at 15:54

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