Approaching 100% Confidence in Stream Summary through ReliableSketch

TL;DR

ReliableSketch is a new data stream sketch that guarantees high-confidence, low-error approximations for all keys simultaneously, with efficient time and space complexity, and is practical for hardware implementation.

Contribution

It introduces ReliableSketch, the first sketch controlling error for all keys with low failure probability, and demonstrates its efficiency and hardware-friendliness through implementation and experiments.

Findings

Guarantees error below Λ for all keys with high probability

Achieves near-optimal throughput in experiments

Requires only small space and time overhead

Abstract

To approximate sums of values in key-value data streams, sketches are widely used in databases and networking systems. They offer high-confidence approximations for any given key while ensuring low time and space overhead. While existing sketches are proficient in estimating individual keys, they struggle to maintain this high confidence across all keys collectively, an objective that is critically important in both algorithm theory and its practical applications. We propose ReliableSketch, the first to control the error of all keys to less than $\Lambda$ with a small failure probability $\Delta$, requiring only $O(1 + \Delta\ln\ln(\frac{N}{\Lambda}))$ amortized time and $O(\frac{N}{\Lambda} + \ln(\frac{1}{\Delta}))$ space. Furthermore, its simplicity makes it hardware-friendly, and we implement it on CPU servers, FPGAs, and programmable switches. Our experiments show that under the same small space, ReliableSketch not only keeps all keys' errors below $\Lambda$ but also achieves near-optimal throughput, outperforming competitors with thousands of uncontrolled estimations. We have made our source code publicly available.