Key Operations in Count-Min Sketch
Initialization: Set the number of rows and columns that you want in the Count-Min Sketch.
Update: To increase an element’s count, hash it through each hash function and update the array’s associated buckets.
Query: Find the lowest count across the related buckets after hashing an element with each hash algorithm to determine its estimated frequency.
Count-Min Sketch in Python
Count-Min Sketch is a probabilistic data structure which approximates the frequency of items in a stream of data. It uses little memory while handling massive amounts of data and producing approximations of the answers. In this post, we’ll explore the idea behind the Count-Min Sketch, how it’s implemented in Python, and discuss its uses and drawbacks.
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