Architecture For A Generic Distributed Stream Processing System The architectural challenges facing the design of large scale distributed stream processing systems are described, and novel approaches for addressing load management, high availability, and federated operation issues are discussed. We demon strate how medusa handles time varying load spikes and provides high availability in the face of network partitions. we demonstrate medusa in the context of borealis, a second generation stream processing engine based on aurora and medusa.
Architecture For A Generic Distributed Stream Processing System A typical framework of distributed stream processing systems, as shown in fig. 1, includes data access layer, data cache layer, stream processing layer, and cluster service. The architectural challenges facing the design of large scale distributed stream processing systems are described, and novel approaches for addressing load management, high availability, and federated operation issues are discussed. Medusa is a distributed stream processing system built using aurora as the single site processing engine. medusa takes aurora queries and distributes them across multiple nodes. The core intuition behind medusa is to leverage the diverse signal paths and perspectives en abled by spatially distributed mimo radar arrays for “multi view sensing”, as shown in fig. 1.
Status Text Introducing S4 A Distributed Stream Medusa is a distributed stream processing system built using aurora as the single site processing engine. medusa takes aurora queries and distributes them across multiple nodes. The core intuition behind medusa is to leverage the diverse signal paths and perspectives en abled by spatially distributed mimo radar arrays for “multi view sensing”, as shown in fig. 1. Medusa’s network partition handling capabilities leverage stream versioning, time travel and revision tuples, three of the new stream processing features intro duced by borealis, the second generation distributed stream pro cessing engine developed at brown, brandeis, and mit. to show how medusa handles network partitions, we disconnect. We demonstrate how medusa handles time varying load spikes and provides high availability in the face of network partitions. we demonstrate medusa in the context of borealis, a second generation streamprocessing engine based on aurora and medusa. Medusa [3, 6] is a distributed stream processing system based on the aurora single site stream processing engine [1]. we demonstrate how medusa handles time varying load spikes and. In this paper, we first describe how the standard high availability approaches used in data management systems can be applied to distributed stream processing. we then propose a novel stream oriented approach that exploits the unique data flow nature of streaming systems.
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