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Cloudera Certified Developer for Apache Hadoop Sample Questions:

1. What is the preferred way to pass a small number of configuration parameters to a mapper or reducer?

A) As a custom input key-value pair passed to each mapper or reducer.
B) Using a plain text file via the Distributedcache, which each mapper or reducer reads.
C) Through a static variable in the MapReduce driver class (i.e., the class that submits the MapReduce job).
D) As key-value pairs in the jobconf object.

2. You are developing a combiner that takes as input Text keys, IntWritable values, and emits Text keys, Intwritable values. Which interface should your class implement?

A) Mapper <Text, IntWritable, Text, IntWritable>
B) Reducer <Text, IntWritable, Text, IntWritable>
C) Combiner <Text, Text, IntWritable, IntWritable>
D) Reducer <Text, Text, IntWritable, IntWritable>
E) Combiner <Text, IntWritable, Text, IntWritable>

3. 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 only after all intermediate data has been copied and sorted.
B) 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.
C) 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.
D) 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.

4. Combiners Increase the efficiency of a MapReduce program because:

A) They provide an optimization and reduce the total number of computations that are needed to execute an algorithm by a factor of n, where is the number of reducer.
B) They provide a mechanism for different mappers to communicate with each Other, thereby reducing synchronization overhead.
C) They aggregate intermediate map output horn a small number of nearby (i.e., rack-local) machines and therefore reduce the amount of data that needs to be shuffled across the network to the reducers.
D) They aggregate intermediate map output locally on each individual machine and therefore reduce the amount of data that needs to be shuffled across the network to the reducers.

5. What happens in a MapReduce job when you set the number of reducers to one?

A) Setting the number of reducers to one is invalid, and an exception is thrown.
B) Setting the number of reducers to one creates a processing bottleneck, and since the number of reducers as specified by the programmer is used as a reference value only, the MapReduce runtime provides a default setting for the number of reducers.
C) A single reducer gathers and processes all the output from all the mappers. The output is written in as many separate files as there are mappers.
D) A single reducer gathers and processes all the output from all the mappers. The output is written to a single file in HDFS.

Solutions: