We're sorry but this page doesn't work properly without JavaScript enabled. Please enable it to continue.

When Probably is Good Enough

Formal Metadata

When Probably is Good Enough
Title of Series
Number of Parts
CC Attribution 3.0 Unported:
You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal purpose as long as the work is attributed to the author in the manner specified by the author or licensor.
Release Date2023

Content Metadata

Subject Area
Examining the probabilistic data structures that come built into Redis Stack will allow us to fully understand how, why and when they work best. We'll examine each of: count min sketch, top k, and bloom and cuckoo filters. Each of these has a distinct structure that we'll start with so we can see how they work. We'll then look at why each one is probabilistic and what the consequences are for that. Then we'll look at use cases for each to see when they would best be used in the wild. We'll wrap up with a demonstration of the space saving capabilities, for example the size difference between a bloom filter and a set with the same items added to each.