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We've observed that for very large bloom filters the expected false positive probability returns a negative value and the observed false positive probability exceeds the desired false positive probability during conditions when the number of performed insertions is relatively small as compared to the number of expected insertions.
I've been able to reproduce this behavior in the attached SSCCE. The bloom filter is constructed with an expected 150M insertions and a desired fpp of 0.0001. After 75M insertions the expected false positive probability is a negative value. The observed false positive probability is around 0.0002. Informally we have been able to reproduce the negative expected false positive probability with larger desired false positive probabilities by increasing the expected number of insertions.
The text was updated successfully, but these errors were encountered:
This seems to be related to 1119 (if not the same problem). Quiet some things still use int which gladly overflows, e.g., BloomFilterStrategies.BitArray.bitSize().
Original issue created by spie...@addthis.com on 2014-02-05 at 04:07 PM
Hi folks,
We've observed that for very large bloom filters the expected false positive probability returns a negative value and the observed false positive probability exceeds the desired false positive probability during conditions when the number of performed insertions is relatively small as compared to the number of expected insertions.
I've been able to reproduce this behavior in the attached SSCCE. The bloom filter is constructed with an expected 150M insertions and a desired fpp of 0.0001. After 75M insertions the expected false positive probability is a negative value. The observed false positive probability is around 0.0002. Informally we have been able to reproduce the negative expected false positive probability with larger desired false positive probabilities by increasing the expected number of insertions.
The text was updated successfully, but these errors were encountered: