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Question ID 12473

You have just executed a MapReduce job. Where is intermediate data written to after being
emitted from the Mappers map method?

Option A

 Intermediate data in streamed across the network from Mapper to the Reduce and is never written to disk.

Option B

Into in-memory buffers on the TaskTracker node running the Mapper that spill over and are written into HDFS.

Option C

 Into in-memory buffers that spill over to the local file system of the TaskTracker node running the Mapper.

Option D

Into in-memory buffers that spill over to the local file system (outside HDFS) of the TaskTracker node running the Reducer

Option E

Into in-memory buffers on the TaskTracker node running the Reducer that spill over and are written into HDFS.

Correct Answer C
Explanation Explanation: The mapper output (intermediate data) is stored on the Local file system (NOT HDFS) of each individual mapper nodes. This is typically a temporary directory location which can be setup in config by the hadoop administrator. The intermediate data is cleaned up after the Hadoop Job completes. Reference: 24 Interview Questions & Answers for Hadoop MapReduce developers, Where is the Mapper Output (intermediate kay-value data) stored ?


Question ID 12474

For each input key-value pair, mappers can emit:

Option A

As many intermediate key-value pairs as designed. There are no restrictions on the types of those key-value pairs (i.e., they can be heterogeneous).

Option B

As many intermediate key-value pairs as designed, but they cannot be of the same type as the input key-value pair.

Option C

One intermediate key-value pair, of a different type.

Option D

One intermediate key-value pair, but of the same type.

Option E

 As many intermediate key-value pairs as designed, as long as all the keys have the same types and all the values have the same type.

Correct Answer E
Explanation Explanation: Mapper maps input key/value pairs to a set of intermediate key/value pairs. 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. Reference: Hadoop Map-Reduce Tutorial

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