Alain Biem, Eric Bouillet, et al.
SIGMOD 2010
The seamless confluence of data in motion and data at rest has the potential to redefine the Big Data analytics landscape in a diverse range of domains. To make this happen, existing data intensive computing frameworks need to be repurposed and integrated at control, data, and management levels. Towards this end, we present the system level integration of IBM InfoSphere Streams with Apache YARN. Our design leverages the key differentiating features of the two frameworks to blend high throughput batch-processing with near line-rate, low latency stream-processing. In addition, both frameworks are able to share resources and offer the same interfaces that their users are accustomed to. Using two real-world examples, we illustrate how such a system can be used in production.
Alain Biem, Eric Bouillet, et al.
SIGMOD 2010
Eric Bouillet, Anand Ranganathan
MDM 2010
Fang Zheng, Chitra Venkatramani, et al.
ICDCS 2013
Eric Bouillet, Jean-François Labourdette, et al.
OFC/NFOEC 2006