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Cloudera Certified Developer for Apache Hadoop Sample Questions:

1. Given a Mapper, Reducer, and Driver class packaged into a jar, which is the correct way of submitting the job to the cluster?

A) hadoop jar MyJar.jar MyDriverClass inputdir outputdir
B) jar MyJar.jar
C) jar MyJar.jar MyDriverClass inputdir outputdir
D) hadoop jar class MyJar.jar MyDriverClass inputdir outputdir

2. What is the difference between a failed task attempt and a killed task attempt?

A) A failed task attempt is a task attempt that threw an unhandled exception. A killed task attempt is one that was terminated by the JobTracker.
B) A failed task attempt is a task attempt that did not generate any key value pairs. A killed task attempt is a task attempt that threw an exception, and thus killed by the execution framework.
C) A failed task attempt is a task attempt that threw a RuntimeException (i.e., the task fails). A killed task attempt is a task attempt that threw any other type of exception (e.g., IOException); the execution framework catches these exceptions and reports them as killed.
D) A failed task attempt is a task attempt that completed, but with an unexpected status value. A killed task attempt is a duplicate copy of a task attempt that was started as part of speculative execution.

3. Which of the following utilities allows you to create and run MapReduce jobs with any executable or script as the mapper and/or the reducer?

A) Hadoop Streaming
B) Flume
C) Sqoop
D) Oozie

4. When is the reduce method first called in a MapReduce job?

A) Reducers start copying intermediate key value pairs from each Mapper as soon as it has completed. The reduce method is called as soon as the intermediate key-value pairs start to arrive.
B) Reducers start copying intermediate key-value pairs from each Mapper as soon as it has completed. The reduce method is called only after all intermediate data has been copied and sorted.
C) Reducers start copying intermediate key-value pairs from each Mapper as soon as it has completed. The programmer can configure in the job what percentage of the intermediate data should arrive before the reduce method begins.
D) Reduce methods and map methods all start at the beginning of a job, in order to provide optimal performance for map-only or reduce-only jobs.

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

A) One intermediate key value pair, but of the same type.
B) One intermediate key value pair, of a different type.
C) As many intermediate key value pairs as desired, as long as all the keys have the same type and all the values have the same type.
D) As many intermediate key-value pairs as desired, but they cannot be of the same type as the input key-value pair.
E) As many intermediate key-value pairs as desired. There are no restrictions on the types of those key-value pairs (i.e., they can be heterogeneous).

Solutions: