BloomFilter
Related Docs:
object BloomFilter
| package collection
Computes the union of two bloom filters and returns the result.
Computes the union of two bloom filters and returns the result. Note that this operation is only defined for filters of the same width. Filters which have a different value of k (different number of hash functions) can be unioned, but the result will have a higher probability of false positives than either of the operands. The k value of the resulting filter is computed to be the minimum k of the two operands. The capacity of the resulting filter is precisely the combined capacity of the operands. This of course means that for sets with intersecting items the capacity will be slightly large.
A value between 0 and 1 which estimates the accuracy of the bloom filter.
A value between 0 and 1 which estimates the accuracy of the bloom filter. This estimate is precisely the inverse of the probability function for a bloom filter of a given capacity, width and number of hash functions. The probability function given by the following expression in LaTeX math syntax:
(1 - e^{-kn/m})^k where k is the number of hash functions,
n is the number of elements in the bloom filter and m is the
width.
It is important to remember that this is only an estimate of the accuracy. Likewise, it assumes perfectly ideal hash functions, thus it is somewhat more optimistic than the reality of the implementation.
Returns the optimal value of k for a bloom filter with the current properties (width and capacity).
Returns the optimal value of k for a bloom filter with the current properties (width and capacity). Useful in reducing false-positives on sets with a limited range in capacity.