Partitioner is yet another important phase that CONTROLS the partitioning of the intermediate map-reduce output keys using a hash function. The process of partitioning determines in what REDUCER, a KEY-value pair (of the map output) is sent. The number of partitions is equal to the total number of reduce jobs for the process.

Hash Partitioner is the default class available in Hadoop , which IMPLEMENTS the following function.int getPartition(K key, V value, int numReduceTasks)

The function returns the partition number using the numReduceTasks is the number of fixed reducers.

Partitioner is yet another important phase that controls the partitioning of the intermediate map-reduce output keys using a hash function. The process of partitioning determines in what reducer, a key-value pair (of the map output) is sent. The number of partitions is equal to the total number of reduce jobs for the process.

Hash Partitioner is the default class available in Hadoop , which implements the following function.int getPartition(K key, V value, int numReduceTasks)

The function returns the partition number using the numReduceTasks is the number of fixed reducers.