META: Middleware for Events, Transactions, and Analytics


Businesses that receive events in the shape of messages and react to them quickly will take advantage of opportunities and avoid risks as they occur. Since fast reactions are necessary, event processing middleware is a core technology in many businesses. However, the necessity to act quickly must be balanced against the requirement to act profitably, and the best action often depends on more context than just the newest event. Unfortunately, the context is usually too giant to research within the time allotted to processing an incident. Instead, out-of-band analytics can train an analytical model, against that an occasion will be quickly scored. We tend to designed middleware that combines transactional event processing with analytics, using a data store to bridge between the two. Since the mixing happens within the middleware, resolution developers would like not integrate technologies for events and analytics by hand. At the surface, our Middleware for Events, Transactions, and Analytics (META) offers a unified rule-primarily based programming model. Internally, META uses the X10 distributed programming language. A core technical challenge involved ensuring that the solutions are highly offered on unreliable commodity hardware, and continuously on the market through updates. This paper describes the programming model of META, its architecture, and its distributed runtime system.

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