Incremental view-based analysis of stock market data streams

Abstract

In this paper we show the usefulness and feasibility of applying conventional SQL queries for analyzing a wide spectrum of data streams. As application area we have chosen the analysis of stock market data, mainly because this kind of application exhibits sufficiently many of those characteristics for which relational query technology can be considered a valuable instrument in a stream context. The resulting TInTo system is a tool for computing so-called technical indicators, numerical values calculated from a certain kind of stock market data, characterizing the development of stock prices over a given time period. Update propagation is used for the incremental recomputation of indicator views defined over a stream of continuously changing price data.