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arXiv · 2504.21175

Tight Bounds for Heavy-Hitters and Moment Estimation in the Sliding Window Model

Shiyuan Feng·William Swartworth·David P. Woodruff
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Abstract

We consider the heavy-hitters and $F_p$ moment estimation problems in the sliding window model. For $F_p$ moment estimation with $1<p\leq 2$, we show that it is possible to give a $(1\pm \epsilon)$ multiplicative approximation to the $F_p$ moment with $2/3$ probability on any given window of size $n$ using $\tilde{O}(\frac{1}{\epsilon^p}\log^2 n + \frac{1}{\epsilon^2}\log n)$ bits of space. We complement this result with a lower bound showing that our algorithm gives tight bounds up to factors of $\log\log n$ and $\log\frac{1}{\epsilon}.$ As a consequence of our $F_2$ moment estimation algorithm, we show that the heavy-hitters problem can be solved on an arbitrary window using $O(\frac{1}{\epsilon^2}\log^2 n)$ space which is tight.

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Shiyuan Feng, William Swartworth, David P. Woodruff. 2025-04-29. Tight Bounds for Heavy-Hitters and Moment Estimation in the Sliding Window Model. https://arxiv.org/abs/2504.21175

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