There are many systems developed to

There are many systems developed today for the parallel processing of big data sets that
provide query languages for expressing analysis tasks over big data sets. However, these
languages are more or less aware of the physical aspects of the underlying system.
In this talk we present a high level query language for expressing analysis tasks as queries
over big data sets, independently of how the analysis is to be carried out or what are the
computing resources used by the system and what is the physical layout of data: a query in
our language is defined at the conceptual level and then mapped to a lower level evaluation
mechanism for computing its answer. We illustrate this process using MapReduce as such a
lower level evaluation mechanism.