Cloudera Certified Developer for Apache Hadoop Sample Questions:

1. You need to create a job that does frequency analysis on input data. You will do this by writing a Mapper that uses TextInputForma and splits each value (a line of text from an input file) into individual characters. For each one of these characters, you will emit the character as a key and as IntWritable as the value. Since this will produce proportionally more intermediate data than input data, which resources could you expect to be likely bottlenecks?

A) Disk I/O and network I/O
B) Processor and disk I/O
C) Processor and RAM
D) Processor and network I/O

2. During the standard sort and shuffle phase of MapReduce, keys and values are passed to reducers. Which of the following is true?

A) Keys are presented to a reducer in random order; values for a given key are sorted in ascending order.
B) Keys are presented to a reducer in soiled order; values for a given key are sorted in ascending order.
C) Keys are presented to a reducer in random order; values for a given key are not sorted.
D) Keys are presented to a reducer in sorted order; values for a given key are not sorted.

3. In a MapReduce job with 500 map tasks, how many map task attempts will there be?

A) Between 500 and 1000.
B) Exactly 500.
C) It depends on the number of reducers in the job.
D) At most 500.
E) At least 500.

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 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.
C) 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.
D) They provide a mechanism for different mappers to communicate with each Other, thereby reducing synchronization overhead.

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

A) 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.
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 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.

Solutions: