Hortonworks HADOOP-PR000007 real exam prep : Hortonworks-Certified-Apache-Hadoop-2.0-Developer(Pig and Hive Developer)
- Exam Code: HADOOP-PR000007
- Exam Name: Hortonworks-Certified-Apache-Hadoop-2.0-Developer(Pig and Hive Developer)
- Updated: Sep 22, 2026
- Q&As: 110 Questions and Answers
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Hortonworks HADOOP-PR000007 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Data Processing with Pig | - Pig Latin fundamentals
|
| Topic 2: Hadoop Ecosystem Integration | - HDFS interaction - Data ingestion and ETL workflows - MapReduce basics |
| Topic 3: Data Warehousing with Hive | - Advanced Hive features
|
Hortonworks-Certified-Apache-Hadoop-2.0-Developer(Pig and Hive Developer) Sample Questions:
When can a reduce class also serve as a combiner without affecting the output of a MapReduce program?
- A. Always. Code can be reused in Java since it is a polymorphic object-oriented programming language.
- B. Never. Combiners and reducers must be implemented separately because they serve different purposes.
- C. 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.
- D. When the signature of the reduce method matches the signature of the combine method.
- E. Always. The point of a combiner is to serve as a mini-reducer directly after the map phase to increase performance.
Correct Answer: C 🗳️
The Hadoop framework provides a mechanism for coping with machine issues such as faulty
configuration or impending hardware failure. MapReduce detects that one or a number of machines are
performing poorly and starts more copies of a map or reduce task. All the tasks run simultaneously and
the task finish first are used. This is called:
- A. Default Partitioner
- B. Combine
- C. Speculative Execution
- D. IdentityMapper
- E. IdentityReducer
Correct Answer: C 🗳️
Indentify which best defines a SequenceFile?
- A. A SequenceFile contains a binary encoding of an arbitrary number of homogeneous Writable objects
- 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 WritableComparable objects, in
sorted order.
Correct Answer: B 🗳️
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 Combiner is incompatible with a mapper which doesn't use the same data type for
both the key and value. - B. Yes, because the sum operation is both associative and commutative and the input and output types to
the reduce method match. - C. No, because the sum operation in the reducer is incompatible with the operation of a Combiner.
- D. Yes, because Java is a polymorphic object-oriented language and thus reducer code can be reused as
a combiner. - E. No, because the Reducer and Combiner are separate interfaces.
Correct Answer: B 🗳️
MapReduce v2 (MRv2/YARN) splits which major functions of the JobTracker into separate daemons?
Select two.
- A. Job scheduling/monitoring
- B. Managing file system metadata
- C. MapReduce metric reporting
- D. Resource management
- E. Launching tasks
- F. Heath states checks (heartbeats)
- G. Job coordination between the ResourceManager and NodeManager
- H. Managing tasks
Correct Answer: A,D 🗳️
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