Partitioning is the process of determining which reducer instance will receive which intermediate keys and values. Each mapper must determine for all of its output (key, val
The default partitioner in Hadoop is the HashPartitioner
which has a method called getPartition
. It takes key.hashCode() & Integer.MAX_VALUE
and finds the modulus using the number of reduce tasks.
For example, if there are 10 reduce tasks, getPartition
will return values 0 through 9 for all keys.
Here is the code:
public class HashPartitioner<K, V> extends Partitioner<K, V> {
public int getPartition(K key, V value, int numReduceTasks) {
return (key.hashCode() & Integer.MAX_VALUE) % numReduceTasks;
}
}
To create a custom partitioner, you would extend Partitioner
, create a method getPartition
, then set your partitioner in the driver code (job.setPartitionerClass(CustomPartitioner.class);
). This is particularly helpful if doing secondary sort operations, for example.