Correct Answer : Get Lastest Questions and Answer : Explanation: The Combiner class is used in between the Map class and the Reduce class to reduce the volume of data transfer between Map and Reduce. Usually, the output of the map task is large and the data transferred to the reduce task is high
A combiner does not have a predefined interface and it must implement the Reducer interface s reduce() method.
A combiner operates on each map output key. It must have the same output key-value types as the Reducer class.
A combiner can produce summary information from a large dataset because it replaces the original Map output.
job.setCombinerClass(MyReducer.class);
Question : How can Map output compression, improves the performance of Hadoop Job ?
Correct Answer : Get Lastest Questions and Answer : Explanation: When you use compression for output of the Map tasks. It will reduce the Disk I/O and network I/O , because lesser data needs to be stored on local disk or needs to transferred over the network. ZLIB is a good codec for Compression , but it can not be always used as it needs more CPU. Output of Map tasks is always written to local disk.