19–30 Aug 2013
KTH main campus
Europe/Stockholm timezone

Abstractions for processing large data sets

30 Aug 2013, 11:15
45m
E3 (KTH main campus)

E3

KTH main campus

KTH main campus Valhallavägen 79

Speaker

Jonas YNGVESSON

Description

At Google there is often a need to process very large data sets across many machines. Building efficient parallel processing programs is not trivial and to avoid the overhead of each engineer reinventing the wheel, Google has created several programming models to abstract away the complexities of parallelism and have the programmer concentrate on the core of his processing problem instead. I will talk mainly about the MapReduce model, how it works and the conceptual model the programmer has to work with when using it. I will also mention a bit about a more recent framework, Pregel, which is built for processing very large

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