Abstract
UpStream is a framework for load management over data streams with update semantics. It provides a novel storage manager architecture that can be plugged into data stream processing engines for serving streaming applications that require low-staleness results over real-time continuous queries. We propose to demonstrate the key aspects of the UpStream architecture as well as its performance using two different application scenarios: One that models a continuously updating financial market dashboard, and another one that is based on an intelligent transportation system for monitoring moving vehicles on a road traffic network. The demonstration will illustrate how UpStream can provide low-staleness query results for these applications under highly overloaded situations, by using a number of update scheduling and storage management techniques. This will be done through a number of interactive visual monitoring tools for the application interface as well as for monitoring the run-time operation of the UpStream system itself.
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