Cloudera CCD-333 : Cloudera Certified Developer for Apache Hadoop

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Cloudera Certified Developer for Apache Hadoop Sample Questions:

1. 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 locally on each individual machine and therefore reduce the amount of data that needs to be shuffled across the network to the reducers.
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 provide a mechanism for different mappers to communicate with each Other, thereby reducing synchronization overhead.

2. What is the behavior of the default partitioner?

A) The default partitioner assigns key value pairs to reducers based on an internal random number generator.
B) The default partitioner computes the hash of the key. Hash values between specific ranges are associated with different buckets, and each bucket is assigned to a specific reducer.
C) The default partitioner computes the hash of the value and takes the mod of that value with the number of reducers. The result determines the reducer assigned to process the key value pair.
D) The default partitioner computes the hash of the key and divides that value modulo the number of reducers. The result determines the reducer assigned to process the key-value pair.
E) The default partitioner implements a round robin strategy, shuffling the key value pairs to each reducer in turn. This ensures an even partition of the key space.

3. Custom programmer-defined counters in MapReduce are:

A) Lightweight devices for bookkeeping within MapReduce programs.
B) Lightweight devices for ensuring the correctness of a MapReduce program. Mappers Increment counters, and reducers decrement counters. If at the end of the program the counters read zero, then you are sure that the job completed correctly.
C) Lightweight devices for synchronization within MapReduce programs. You can use counters to coordinate execution between a mapper and a reducer.

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

A) 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.
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 a Writable object from an object pool.
E) Returns a reference to a Writable object. The API leaves unspecified whether this is a reused object or a new object.

5. In a large MapReduce job with m mappers and r reducers, how many distinct copy operations will there be in the sort/shuffle phase?

A) m+r (i.e., m plus r)
B) m
C) r
D) mxr (i.e., m multiplied by r)
E) mr (i.e., m to the power of r)

Solutions: