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