Parallel Computing for Data Science

Chapter 9

MapReduce Computation

As the world emerged into an era of Big Data, demand grew for a comput-

ing paradigm that (a) is generally applicable and (b) works on distributed

data. The latter term means that data is physically distributed over many

chunks, possibly on different disks and maybe even different geographical

locations. Having the data stored in a distributed manner facilitates paral-

lel computation — different chunks can be read simultaneously — and also

enables us to work with data sets that are too large to fit into the memory

of a single machine. Demand for such computational capability led to the

development of various systems using ...