MapReduce Programming - An introductory article into the concept of MapReduce Programming

 

MapReduce Programming

 * A Data Processing problem can be transformed into a MapReduce Model by the usage of MapReduce Programming

 * The very first step within the process is to visualize the processing plan of a Map and Reduce Programming problem in a step by step process

 * When a problem involving Map and Reduce Programming gets more complex , the underlying complexity within the Map and Reduce problem can be manifested and resolved in either of the two ways or a combination of two ways

 1) Having more number of MapReduce Jobs -- which would eventually increase the load present over the processors and then mitigated by parallel distribution over the servers

 2) Having more complex Map and Reduce Jobs -- under this scenario one may suppose that the number of sorting jobs and processes might get increased tremendously which might add to the complexity , otherwise complexity might also get enhanced under conditions when more and more key and values for same set of text/words are found out by the program and thus mapping their frequency to the matched key becomes more and more which would again add to the complexity of the Map-Reduce Program . Having more but simple MapReduce jobs leads to more easily maintainable Map and Reduce Programs .