Surfing Wavelets on Streams: One-Pass Summaries for Approximate Aggregate Queries

Abstract

Abstract We present techniques for computing small spacerepresentations of massive data streams. These are inspired by traditional wavelet-based approx-imations that consist of specific linear projections of the underlying data. We present general"sketch " based methods for capturing various linear projections of the data and use them to pro-vide pointwise and rangesum estimation of data streams. These methods use small amounts ofspace and per-item time while streaming through the data, and provide accurate representation asour experiments with real data streams show.