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Hortonworks Apache-Hadoop-Developer Exam Syllabus Topics:

Hortonworks Hadoop 2.0 Certification exam for Pig and Hive Developer Sample Questions:

1. What are the TWO main components of the YARN ResourceManager process? Choose 2 answers

A) Task Tracker
B) Applications Manager
C) Job Tracker
D) Scheduler

2. Analyze each scenario below and indentify which best describes the behavior of the default partitioner?

A) 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.
B) The default partitioner computes the hash of the key and divides that valule modulo the number of reducers. The result determines the reducer assigned to process the key-value pair.
C) 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.
D) The default partitioner implements a round-robin strategy, shuffling the key-value pairs to each reducer in turn. This ensures an event partition of the key space.
E) The default partitioner assigns key-values pairs to reduces based on an internal random number generator.

3. When can a reduce class also serve as a combiner without affecting the output of a MapReduce program?

A) Never. Combiners and reducers must be implemented separately because they serve different purposes.
B) When the types of the reduce operation's input key and input value match the types of the reducer's output key and output value and when the reduce operation is both communicative and associative.
C) When the signature of the reduce method matches the signature of the combine method.
D) Always. Code can be reused in Java since it is a polymorphic object-oriented programming language.
E) Always. The point of a combiner is to serve as a mini-reducer directly after the map phase to increase performance.

4. Which one of the following statements is true regarding a MapReduce job?

A) The job's Partitioner shuffles and sorts all (key.value) pairs and sends the output to all reducers
B) The Mapper must sort its output of (key.value) pairs in descending order based on value
C) The default Hash Partitioner sends key value pairs with the same key to the same Reducer
D) The reduce method is invoked once for each unique value

5. What is the disadvantage of using multiple reducers with the default HashPartitioner and distributing your workload across you cluster?

A) There are no concerns with this approach. It is always advisable to use multiple reduces.
B) By using multiple reducers with the default HashPartitioner, output files may not be in globally sorted order.
C) You will not be able to compress the intermediate data.
D) You will longer be able to take advantage of a Combiner.

Solutions: