Hortonworks Apache-Hadoop-Developer Q&A - in .pdf

  • Exam Code: Apache-Hadoop-Developer
  • Exam Name: Hadoop 2.0 Certification exam for Pig and Hive Developer
  • Updated: Jun 01, 2026
  • Q & A: 110 Questions and Answers
  • PDF Price: $49.99
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Hortonworks Apache-Hadoop-Developer Q&A - Testing Engine

  • Exam Code: Apache-Hadoop-Developer
  • Exam Name: Hadoop 2.0 Certification exam for Pig and Hive Developer
  • Updated: Jun 01, 2026
  • Q & A: 110 Questions and Answers
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Hortonworks Hadoop 2.0 Certification exam for Pig and Hive Developer Sample Questions:

1. Your cluster's HDFS block size in 64MB. You have directory containing 100 plain text files, each of which is 100MB in size. The InputFormat for your job is TextInputFormat. Determine how many Mappers will run?

A) 100
B) 64
C) 640
D) 200


2. Which TWO of the following statements are true regarding Hive? Choose 2 answers

A) Allows you to define a structure for your unstructured Big Data
B) Is a relational database
C) Useful for data analysts familiar with SQL who need to do ad-hoc queries
D) Offers real-time queries and row level updates


3. Indentify which method in the Mapper you should use to implement code for reading the file and populating the associative array?

A) map
B) combine
C) init
D) configure


4. Indentify which best defines a SequenceFile?

A) A SequenceFile contains a binary encoding of an arbitrary number of WritableComparable objects, in sorted order.
B) A SequenceFile contains a binary encoding of an arbitrary number key-value pairs. Each key must be the same type. Each value must be the same type.
C) A SequenceFile contains a binary encoding of an arbitrary number of heterogeneous Writable objects
D) A SequenceFile contains a binary encoding of an arbitrary number of homogeneous Writable objects


5. You want to count the number of occurrences for each unique word in the supplied input data. You've decided to implement this by having your mapper tokenize each word and emit a literal value 1, and then have your reducer increment a counter for each literal 1 it
receives. After successful implementing this, it occurs to you that you could optimize this by specifying a combiner. Will you be able to reuse your existing Reduces as your combiner in this case and why or why not?

A) No, because the Reducer and Combiner are separate interfaces.
B) Yes, because the sum operation is both associative and commutative and the input and output types to the reduce method match.
C) Yes, because Java is a polymorphic object-oriented language and thus reducer code can be reused as a combiner.
D) No, because the sum operation in the reducer is incompatible with the operation of a Combiner.
E) No, because the Combiner is incompatible with a mapper which doesn't use the same data type for both the key and value.


Solutions:

Question # 1
Answer: D
Question # 2
Answer: A,C
Question # 3
Answer: D
Question # 4
Answer: B
Question # 5
Answer: B

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