Achieving High Accuracy and Fast Speed for Sketch Compression
Ye Jin, Yuanchao Shan, Wenlu Zhang, Lin Li, Sitan Li, Jing Shao, Jiawei Huang · 2023
To reduce the communication overhead in distributed sketch system, it is desirable to compress sketches before uploading. However, current sketch compression approaches hardly achieve high speed of compression procedure and low error of compressed sketches at the same time. In this paper, we take a clean slate approach to design a sketch compression scheme called as Fast-Mapping that achieves both fast compression speed and high accuracy. Based on the prior statistics knowledge of bucket data distribution, Fast-Mapping compresses the similar buckets to obtain high accuracy. We also theoretically derive the compression error bound of Fast-Mapping. The experimental results show that, Fast-Mapping achieves higher speed and lower error than the-state-of-art works.