Hortonworks-Certified-Apache-Hadoop-2.0-Developer(Pig and Hive Developer) : HADOOP-PR000007 Exam Questions

Exam Code: HADOOP-PR000007
Exam Name: Hortonworks-Certified-Apache-Hadoop-2.0-Developer(Pig and Hive Developer)
Updated: Sep 09, 2026
Q&As: 110 Questions and Answers

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Hortonworks HADOOP-PR000007 Exam Syllabus Topics:

Section	Objectives
Topic 1: Hadoop Core Concepts	- YARN and MapReduce fundamentals - HDFS architecture and commands
Topic 2: Pig Development	- Pig Latin scripting - Pig data types and UDFs
Topic 3: Hive Development	- Hive optimization and execution - Hive table definitions and queries
Topic 4: Hadoop Ecosystem Tools	- Workflow and processing frameworks - Sqoop and data ingestion

Hortonworks-Certified-Apache-Hadoop-2.0-Developer(Pig and Hive Developer) Sample Questions:

Question #1

You have written a Mapper which invokes the following five calls to the OutputColletor.collect method:
output.collect (new Text ("Apple"), new Text ("Red") ) ;
output.collect (new Text ("Banana"), new Text ("Yellow") ) ;
output.collect (new Text ("Apple"), new Text ("Yellow") ) ;
output.collect (new Text ("Cherry"), new Text ("Red") ) ;
output.collect (new Text ("Apple"), new Text ("Green") ) ;
How many times will the Reducer's reduce method be invoked?

A. 5
B. 0
C. 6
D. 1
E. 3

Answer: E

Question #2

Assuming default settings, which best describes the order of data provided to a reducer's reduce method:

A. The keys given to a reducer aren't in a predictable order, but the values associated with those keys
always are.
B. Neither keys nor values are in any predictable order.
C. Both the keys and values passed to a reducer always appear in sorted order.
D. The keys given to a reducer are in sorted order but the values associated with each key are in no
predictable order

Answer: D

Question #3

Examine the following Pig commands:

Which one of the following statements is true?

A. The reducers will only output the first 20% of the data passed from the mappers
B. A random sample of approximately 20% of the data will be output
C. The SAMPLE command generates an "unexpected symbol" error
D. Each MapReduce task will terminate after executing for 0.2 minutes

Answer: B

Question #4

You write MapReduce job to process 100 files in HDFS. Your MapReduce algorithm uses
TextInputFormat: the mapper applies a regular expression over input values and emits key-values pairs
with the key consisting of the matching text, and the value containing the filename and byte offset.
Determine the difference between setting the number of reduces to one and settings the number of
reducers to zero.

A. There is no difference in output between the two settings.
B. With zero reducers, no reducer runs and the job throws an exception. With one reducer, instances of
matching patterns are stored in a single file on HDFS.
C. With zero reducers, all instances of matching patterns are gathered together in one file on HDFS. With
one reducer, instances of matching patterns are stored in multiple files on HDFS.
D. With zero reducers, instances of matching patterns are stored in multiple files on HDFS. With one
reducer, all instances of matching patterns are gathered together in one file on HDFS.

Answer: D

Question #5

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

A. The default partitioner assigns key-values pairs to reduces based on an internal random number
generator.
B. 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.
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 valule modulo the number of
reducers. The result determines the reducer assigned to process the key-value pair.
E. 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.