Speaker
Jonas Yngvesson
(Google Inc.)
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, the conceptual
model the programmer get to work with and how it is
implemented under the hood. I will also mention a few
other models in use at Google, like Pregel, Dremel and
Flume.