Resa: realtime elastic streaming analytics in the cloud

Abstract

We propose Resa, a novel framework for robust, elastic and realtime stream processing in the cloud. In addition to traditional functionalities of streaming and cloud systems, Resa provides (i) a novel mechanism that handles dynamic additions and removals nodes in an operator, and (ii) a node re-assignment scheme that minimizes output latency using a queuing model. We have implemented Resa on top of Twitter Storm. Experiments using real data demonstrate the effectiveness and efficiency of Resa.