Archive - June 5, 2019

If you are new to map-reduce, it is good to start off with a simple example and understand how the different map and reduce functions work in action. Here are the three basic steps that a MapReduce function goes through. There is no surprise in the fact that MapReduce has a map and reduce function, but there is also an intermediate shuffle sort phase between the map and reduce function Here is a diagram for an analogy of how MapReduce works, Map Function– The main goal of any MapReduce function is to allow distributed processing by using multiple cores.  In our example, we have taken the example of pulling boots instead of computing cores, and we can imagine the key being a certain political party and value donates a vote cast for that party. In the different polling stations, we will also have votes for the different parties. Basically, the[…]