"Big data" and MapReduce can often appear to be scary models that only those with Linux & Java skills, and a large budget for a server cluster, can fully understand, let alone leverage. This needn't be the case!
Do you want to process huge amounts of data (e.g. server logs) in a scalable & parallel fashion, while using your favourite tool set? Do you want to ask some questions of an interesting data set, but you feel limited to RDMS & NoSQL? Do you feel that, just because .NET is your language of choice, that you are a second-class (programming) citizen when it comes to available MapReduce tools?
In this talk Chris will discuss the pros and cons of leveraging the MapReduce programming model in a serverless cloud environment with .NET, and show a real world example -- from architecture right down to the code.
an introduction to MapReduce (no prior knowledge on big data or MapReduce is required)
a discussion on what serverless really means, and an introduction to the options available
a worked example of serverless MapReduce with .NET, aiming to answer real questions with real data.
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Serverless MapReduce with .NET
Chris Priest has been working in & around .NET for the last 15 years in a career that has spanned financial institutions, small startups, and worldwide e-commerce platforms. On a day-to-day basis, he is a hands-on Technical Lead / Architect at cloud consultancy Amido.