Hortonworks HCAHD Apache-Hadoop-Developer

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

1. Review the following data and Pig code:

What command to define B would produce the output (M,62,95l02) when invoking the DUMP operator on B?

A) B = FILTER A BY (zip = = '95102' AND gender = = M");
B) B= FOREACH A BY (gender = = 'M' AND zip = = '95102');
C) B = JOIN A BY (gender = = 'M' AND zip = = '95102');
D) B= GROUP A BY (zip = = '95102' AND gender = = 'M');

2. You've written a MapReduce job that will process 500 million input records and generated 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 reduces which is a potential bottleneck. A custom implementation of which interface is most likely to reduce the amount of intermediate data transferred across the network?

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

3. Consider the following two relations, A and B.

What is the output of the following Pig commands?
X = GROUP A BY S1; DUMP X;

A) Option A
B) Option D
C) Option C
D) Option B

4. What types of algorithms are difficult to express in MapReduce v1 (MRv1)?

A) Algorithms that require global, sharing states.
B) Large-scale graph algorithms that require one-step link traversal.
C) Text analysis algorithms on large collections of unstructured text (e.g, Web crawls).
D) Algorithms that require applying the same mathematical function to large numbers of individual binary records.
E) Relational operations on large amounts of structured and semi-structured data.

5. What does Pig provide to the overall Hadoop solution?

A) Simple scripting language for writing MapReduce programs
B) Database table and storage management services
C) Legacy language Integration with MapReduce framework
D) C++ interface to MapReduce and data warehouse infrastructure

Solutions: