Thoughts on System Design for Big Data
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In the context of computing with data, what exactly is a system? Generally speaking, a system is an aggregation of computing components (and the links between them) that collectively provide a solution to a problem. System design covers choices that system designers make regarding such components: hardware (e.g., servers, networks, sensors, etc.); software (e.g., operating systems, cluster managers, applications, etc.); data (e.g., collection, retention, processing, etc.); and other components that vary based on the nature of each solution. There’s no free lunch in system design and no silver bullet; instead, there are patterns that can jumpstart a solution; and for the most part, there will always be tradeoffs. Skilled system designers learn how to deal with novel problems and ambiguity; one of the skills they practice is decomposing a complex problem into more manageable subproblems that look analogous to ones that can be solved using known patterns, then connect those components together to solve the complex problem. In this chapter, we put on our designer hats and explore various aspects of system design in practice by creating a hypothetical big-data solution: a productivity bot.
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