Learn Hadoop Developing a MapReduce Application Multiple Choice Questions and Answers with explanations. Practice Hadoop Developing a MapReduce Application MCQs Online Quiz Mock Test For Objective Interview.
1. Point out the wrong statement :
- A. The Mapper outputs are sorted and then partitioned per Reducer
- B. The total number of partitions is the same as the number of reduce tasks for the job
- C. The intermediate, sorted outputs are always stored in a simple (key-len, key, value-len, value) format
- D. None of the mentioned
Answer: Option D
Explanation:
All intermediate values associated with a given output key are subsequently grouped by the framework, and passed to the Reducer(s) to determine the final output.
2. Applications can use the ____________ to report progress and set application-level status messages
- A. Partitioner
- B. OutputSplit
- C. Reporter
- D. All of the mentioned
Answer: Option C
Explanation:
Reporter is also used to update Counters, or just indicate that they are alive.
3. The right level of parallelism for maps seems to be around _________ maps per-node
Answer: Option B
Explanation:
Task setup takes a while, so it is best if the maps take at least a minute to execute
4. Point out the wrong statement :
- A. It is legal to set the number of reduce-tasks to zero if no reduction is desired
- B. The outputs of the map-tasks go directly to the FileSystem
- C. The Mapreduce framework does not sort the map-outputs before writing them out to the FileSystem
- D. None of the mentioned
Answer: Option D
Explanation:
Outputs of the map-tasks go directly to the FileSystem, into the output path set by setOutputPath(Path).
5. __________ is the primary interface for a user to describe a MapReduce job to the Hadoop framework for execution.
- A. JobConfig
- B. JobConf
- C. JobConfiguration
- D. All of the mentioned
Answer: Option B
Explanation:
JobConf is typically used to specify the Mapper, combiner (if any), Partitioner, Reducer, InputFormat, OutputFormat and OutputCommitter implementations.
