What is Count-Min Sketch?

Count-Min is a probabilistic data structure used to count unique items in a large stream of data. It is used to find an approximate frequency of the events on the streaming data.

The idea behind Count-Min Sketch is to use hash functions and a two-dimensional array (or matrix) to efficiently store the frequency of items. The array is made up of several rows and columns, where a bucket is represented by a column and a hash function by a row. The hash functions identify the locations in the array to increment or get counts when updating or querying the frequency of entries.

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.