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Question ID 12511

You want to run Hadoop jobs on your development workstation for testing before you
submit them to your production cluster. Which mode of operation in Hadoop allows you to
most closely simulate a production cluster while using a single machine?

Option A

Run all the nodes in your production cluster as virtual machines on your development workstation.

Option B

Run the hadoop command with the –jt local and the –fs file:///options.

Option C

Run the DataNode, TaskTracker, NameNode and JobTracker daemons on a single machine.

Option D

Run simldooop, the Apache open-source software for simulating Hadoop clusters.

Correct Answer C
Explanation


Question ID 12512

In a MapReduce job, you want each of your input files processed by a single map task.
How do you configure a MapReduce job so that a single map task processes each input file
regardless of how many blocks the input file occupies?

Option A

 Increase the parameter that controls minimum split size in the job configuration.

Option B

Write a custom MapRunner that iterates over all key-value pairs in the entire file.

Option C

Set the number of mappers equal to the number of input files you want to process.

Option D

Write a custom FileInputFormat and override the method isSplitable to always return false.

Correct Answer D
Explanation Explanation: FileInputFormat is the base class for all file-based InputFormats. This provides a generic implementation of getSplits(JobContext). Subclasses of FileInputFormat can also override the isSplitable(JobContext, Path) method to ensure input-files are not split-up and are processed as a whole by Mappers. Reference: org.apache.hadoop.mapreduce.lib.input, Class FileInputFormat