#3164

sayanti
Participant

Mapper Job

1) Mapper maps input key/value pairs to a set of intermediate key/value pairs.
2) Maps are the individual tasks that transform input records into intermediate records. The transformed intermediate records do not need to be of the same type as the input records. A given input pair may map to zero or many output pairs.
3) The hadoop MapReduce framework spawns one map task for each Inputsplit generated by the InputFromate for the job.
4) Output pairs do not need to be of the same types as input pairs. A given input pair may map to zero or many output pairs.Output pairs are collected with calls to context write(WritableComparable, Writable).
4) Application can use the Counter to report its statistics.
5) All intermediate values associated with a given output key are subsequently grouped by the framework and passed to the Reducer to determine the final output. Users can control the grouping by specifying a Comparator via Job.setGroupingComparatorClass(Class).

Prwatech