.png){kind=icon}
.png){kind=icon}
Return
Processing high data rate streams in System S
.png){kind=icon}
PRE
AI
DOI：10.1016/j.jpdc.2010.08.007.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
High-performance stream processing is critical in many 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 live streams. The central tenets of this work are the programming model, the workload splitting mechanisms, the code generation framework, and the underlying System S middleware and SPADE programming model. We demonstrate considerable scalability behavior coupled with low processing latency in a real-world financial trading application. (C) 2010 Elsevier Inc. All rights reserved.
Keywords:
Data stream processing
Scale-up strategies
Workload balancing
Split/aggregate/join architectural pattern
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
4
Papers:
3.8K
Citations:
4.8K