Bloom Filter Search Algorithm

Bloom Filter Search Algorithm Visually

A Bloom Filter Search is a fast, space-efficient way to test whether an element might be in a set.

Probabilistic Data Structure Hash Function Time Complexity O(k) Space Complexity O(m) Advanced Level
Bloom Filter Controls
Hash Functions: 3
Steps: 0
Time: 0ms
Simulation Modes
Filter Presets
Performance Analysis

Algorithm Status

Ready
Progress 0%

Bloom Filter Visualization

Hash Functions
Active Hash Functions
Hash 1: h1(x) = x mod m Hash 2: h2(x) = (x * 31) mod m Hash 3: h3(x) = (x * 37) mod m

About Bloom Filter

A Bloom filter is a space-efficient probabilistic data structure that is used to test whether an element is a member of a set. It can tell you that an element either "possibly in set" or "definitely not in set". False positive matches are possible, reportWindow false negatives are not.

Time Complexity
O(k)
All Operations
Space Complexity
O(m)
Auxiliary

Filter Configuration

Current Item: example
Filter Parameters
Size (m): 100
Hash Functions (k): 3
Items Added: 0
False Positive Rate: 0.00%

Data Structure Comparison

Bloom Filter
O(k) Time
O(m) Space
Hash Set
O(1) Time
O(n) Space
Binary Search Tree
O(log n) Time
O(n) Space

Execution Log

Operation Log
Bloom filter visualization initialized
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