Example of MapReduce

You can better understand, how MapReduce works by taking an example where we would have a text file called example.txt whose contents are:

Deer, Bear, River, Car, Car, River, Deer, Car, Bear

Now, we can perform a word count on the sample.txt using MapReduce. So, we will be finding unique words and the number of occurrences of those unique words.

1. Divide the input into three splits as shown in the diagram. This will distribute the work among all the map nodes
2. Tokenize the words in each of the mappers and give a hardcoded value (1) to each of the tokens or words
3. A list of key-value pairs is created where the key is nothing but the individual words and the value is one. So, for (Deer Bear River) we have — Deer, 1; Bear, 1; River, 1
4. Sorting and shuffling happen so that all the tuples with the same key are sent to the corresponding reducer
5. After the sorting and shuffling phase, each reducer will have a unique key and a list of values corresponding to that very key. For example, Bear, [1,1]; Car, [1,1,1]...
6. Each Reducer counts the values which are present in that list of values, and gives the final output as — Bear, 2
7. All the output key/value pairs are collected and written in the output file