Time-series data - data arriving in time order, or a data stream - can be found in fields such as physics, finance, music, networking, and medical instrumentation. Designing fast, scalable algorithms for analyzing single or multiple time series can yield scientific discoveries, medical diagnoses, and certainly profits.High Performance Discovery in Time Series presents rapid-discovery techniques for finding portions of time series with many events (i.e., gamma-ray scatterings) and finding closely related time series (i.e., highly correlated price histories, or musical melodies). Such real-time streaming data analysis is critical for complex real-world data in telecommunications, bioinformatics, and finance databases.This new monograph provides a technical survey of concepts and techniques for describing and analyzing large-scale time-series data streams. It offers essential coverage of the topic for database and online web services researchers and professionals, as well as an ideal resource for graduates.