Cloudera Hadoop Developer Certification Questions and Answer (Dumps and Practice Questions)

Question :

MapTask works at a time....


1. Multiple data blocks
2. Single Blocks
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4. All of the above

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Map tasks (the first part of the MapReduce system) work on relatively small portions of data
Typically a single block




Question :

What happens when a running task fails in the hadoop...

1. Failed task data will be lost
2. the master will detect that failure and re-assign the work to a different node on the system
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4. 2 and 3 both are correct

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These are the Hadoops Fault Tolerance feature
- If a node fails, the master will detect that failure and re-assign the
work to a different node on the system
- Restarting a task does not require communication with nodes
working on other portions of the data
- If a failed node restarts, it is automatically added back to the
system and assigned new tasks




Question :

If a node appears to be running slowly then .....

1. the master can redundantly execute another instance of the same task
2. Result from the first to finish will be used
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4. 1 and 2 are correct

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If a node appears to be running slowly, the master can
redundantly execute another instance of the same task
- Results from the first to finish will be used

Related Questions

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Question :

What happens if mapper output does not match reducer input?


1. Hadoop API will convert the data to the type that is needed by the reducer.
2. Data input/output inconsistency cannot occur. A preliminary validation check is executed prior
to the full execution of the job to ensure there is consistency.
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4. A real-time exception will be thrown and map-reduce job will fail




Question :

Can you provide multiple input paths to a map-reduce jobs?

1. Yes, but only in Hadoop 0.22+
2. No, Hadoop always operates on one input directory
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4. Yes, but the limit is currently capped at 10 input paths.




Question :

Can you assign different mappers to different input paths?


1. Yes, but only if data is identical.
2. Yes, different mappers can be assigned to different directories
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4. Yes but only in Hadoop .22+





Question : Can you suppress reducer output?


1. Yes, there is a special data type that will suppress job output
2. No, map reduce job will always generate output.
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4. Yes, but only during map execution when reducers have been set to zero




Question :Is there a map input format?


1. Yes, but only in Hadoop 0.22+
2. Yes, there is a special format for map files
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4. Both 2 and 3 are correct answers.




Question :What is the most important feature of map-reduce



1. Ability to store large amount of data
2. Ability to process data on the cluster of the machines without copying all the data over
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4. Ability to process large amounts of data in parallel