Pyramid sketch

Abstract

Sketch is a probabilistic data structure, and is used to store and query the frequency of any item in a given multiset. Due to its high memory efficiency, it has been applied to various fields in computer science, such as stream database, network traffic measurement, etc. The key metrics of sketches for data streams are accuracy, speed, and memory usage. Various sketches have been proposed, but they cannot achieve both high accuracy and high speed using limited memory, especially for skewed datasets. To address this issue, we propose a sketch framework, the Pyramid sketch, which can significantly improve accuracy as well as update and query speed. To verify the effectiveness and efficiency of our framework, we applied our framework to four typical sketches. Extensive experimental results show that the accuracy is improved up to 3.50 times, while the speed is improved up to 2.10 times. We have released our source codes at Github [1].