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Cloudera Certified Developer for Apache Hadoop Sample Questions:

1. 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) 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.
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.

2. You've written a MapReduce job that will process 500 million input records and generate 500 million key-value pairs. The data is not uniformly distributed. Your MapReduce job will create a significant amount of intermediate data that it needs to transfer between mappers and reducers which is a potential bottleneck. A custom implementation of which of the following interfaces is most likely to reduce the amount of intermediate data transferred across the network?

A) Partitioner
B) InputFormat
C) Writable
D) Combiner
E) OutputFormat
F) WritableComparable

3. In the reducer, the MapReduce API provides you with an iterator over Writable values. Calling the next () method:

A) Returns a reference to a Writable object. The API leaves unspecified whether this is a reused object or a new object.
B) Returns a reference to a different Writable object each time.
C) Returns a reference to the same writable object each time, but populated with different data.
D) Returns a reference to the same writable object if the next value is the same as the previous value, or a new writable object otherwise.
E) Returns a reference to a Writable object from an object pool.

4. Which statement best describes the data path of intermediate key-value pairs (i.e., output of the mappers)?

A) Intermediate key-value pairs are written to the local disks of the machines running the map tasks, and then copied to the machine running the reduce tasks.
B) Intermediate key-value pairs are written to HDFS. Reducers copy the intermediate data to the local disks of the machines running the reduce tasks.
C) Intermediate key-value pairs are written to HDFS. Reducers read the intermediate data from HDFS.
D) Intermediate key-value pairs are written to the local disks of the machines running the map tasks, and are then copied to HDFS. Reducers read the intermediate data from HDFS.

5. 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) Oozie
B) Sqoop
C) Hadoop Streaming
D) Flume

Solutions: