The article presents an efficient algorithm for maintaining sliding-window aggregations (like min, max, quantiles) where the operator lacks an inverse. Building on a technique the author previously considered only useful for min/max, the method generalizes to a broad class of aggregations using a two-stack approach, offering O(1) worst-case time per operation.
Background
Sliding-window aggregation is a common problem in real-time data processing, monitoring, and stream analytics. Traditional approaches using invertible operations like sum are limited when dealing with non-invertible operators like min or approximate distinct counts.
- Source
- Lobsters
- Published
- Oct 3, 2026 at 08:39 PM
- Score
- 7.0 / 10