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dev.bloom-filter-sizing Calculator
Calculates Bloom filter false positive rate, bit array size, and number of hash functions for a given capacity and FPR target. A Bloom filter for 1 million items with 1% FPR requires 9.6 bits per element (1.2 MB total) — false positive rates drop exponentially with more bits.
Inputs
Expected Items
Reference formula or conversion factor shown for context.
False Positive Rate Pct
Amount per unit of time or per unit quantity. Check the denominator before interpreting.
Hash Functions
Reference formula or conversion factor shown for context.
Results
bits required (m)
Reference formula or conversion factor shown for context.
memory (MB)
Reference formula or conversion factor shown for context.
optimal hash functions (k)
The type of mathematical function or operational classification determined by the calculation.
false positive rate
The value at the specified point or condition.
m = -n ln(p) / ln(2)²
Sample size or count used in the calculation.
vs hash set
Reference formula or conversion factor shown for context.