Scale-Up Strategies for Processing High-Rate Data Streams in System S
Henrique C. M. Andrade, Buğra Gedik, Kun‐Lung Wu, Philip S. Yu · Proceedings - International Conference on Data Engineering · 2009
High performance stream processing is critical in sense-and-respond application domains – from environmental monitoring to algorithmic trading. In this paper, we focus on language and runtime support for improving the performance of sense-and-respond applications in processing data from high rate streams. The central tenet of this work is the definition of a streaming architectural pattern for these application domains and the programming model and the code generation framework to support it. Using IBM Research's System S middleware and the SPADE language, we demonstrate how to scale up a financial trading application.