Count-min Sketch to Infinity: Using Probabilistic Data Structures to Solve Counting problems in .NET
A major problem in computer science is performing element counting, distinct element counts, and presence checks on enormous streams of data, in real-time, at scale, without breaking the bank or over-complicating our apps. In this talk, we'll learn how to address these issues using probabilistic data structures. We'll learn what a probabilistic data structure is, we'll learn about the guts of the Count-Min Sketch, Bloom Filter, and HyperLogLog data structures. And finally, we'll talk about using them in our apps at scale.
Guy works for Redis as a Developer Advocate. Combining his decades of experience in writing software with a passion for sharing what he has learned, Guy goes out into developer communities and helps others build great software.