    Parallel Processing Using the Map Reduce Programming Model
From scripting to MapReduce:  Next, Let us assume we have a much
larger dataset with consists of all language movies and their
details. And after running the new file on the same program, we
find that it takes a lot of time. We want it to run faster.
There are two ways to go about this. One, we hack the hell out
of perl. Although this sounds promising, this might not be the
best path. Or, we can try to run parts of the program in
parallel thereby speeding up the execution. But, going this
route, we might open up a Pandora’s Box of issues that accompany
parallel processing. How many processes are we going to run? How
do we co-ordinate the processes? How are we going combine the
output of all the process? What if processes fail? How are we
going to control access to a shared resource? What if the
dataset outgrows our single machine? These are some of the
questions that need answering before we start writing parallel
programs. Although we can get th