Calculate the required bloom filter size and optimal number of hashes from the expected number of items in the collection and acceptable false-positive rate.
You can also see the breakdown of how the bloom filter size and optimal number of hashes are calculated.- Number of Items (n):
Expected number of items in the collection (n)..
- False Positive Rate (f):
Acceptable false-positive rate (fpr). 0.01 = 1%..
- Optimal Size (m):
Optimal size (number of elements in the bit array)..
- Optimal Hash Functions (k):
Optimal number of hash functions..
Bloom Filter is a space-efficient probabilistic data structure which is used to test whether an element is a member of a set or not. We may get false positive matches, but false negatives are not.
History
- Feb 16, 2019
- Calculate Number of Items and False Positive Rate
- Sep 16, 2018
- Calculation formula breakdown
- Apr 25, 2018
- Tool Launched
Comments 4
Partho Sarathi Copy Link
I've been on earth for:
Years
25
Months
4
Days
21
Hours
11
Minutes
26
Age in days
9275
Partho Sarathi Copy Link
This is a test
Partho Sarathi Copy Link
Woot
Partho Sarathi Copy Link
Bloom Filter is a space-efficient probabilistic data structure which is used to test whether an element is a member of a set or not. We may get false positive matches, but false negatives are not.