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

"Hortonworks-Certified-Apache-Hadoop-2.0-Developer(Pig and Hive Developer)", also known as HADOOP-PR000007 exam, is a Hortonworks Certification. With the complete collection of questions and answers, BraindumpsPass has assembled to take you through 110 Q&As to your HADOOP-PR000007 Exam preparation. In the HADOOP-PR000007 exam resources, you will cover every field and category in HDP Certified Developer Certification helping to ready you for your successful Hortonworks Certification.

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  • Exam Code: HADOOP-PR000007
  • Exam Name: Hortonworks-Certified-Apache-Hadoop-2.0-Developer(Pig and Hive Developer)
  • Certification Provider: Hortonworks
  • Corresponding Certification: HDP Certified Developer
  • Updated: Jul 11, 2026
  • No. of Questions: 110 Questions & Answers with Testing Engine
  • Download Limit: Unlimited

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

1. Which one of the following statements describes a Pig bag. tuple, and map, respectively?

A) Unordered collection of maps, ordered collection of tuples, ordered set of key/value pairs
B) Unordered collection of tuples, ordered set of fields, set of key value pairs
C) Ordered collection of maps, ordered collection of bags, and unordered set of key/value pairs
D) Ordered set of fields, ordered collection of tuples, ordered collection of maps


2. Which two of the following are true about this trivial Pig program' (choose Two)

A) myfile is read from the user's home directory in HDFS
B) ABC has a schema associated with it
C) The contents of myfile appear on stdout
D) Pig assumes the contents of myfile are comma delimited


3. 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) 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.
B) There is no difference in output between the two settings.
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.


4. When is the earliest point at which the reduce method of a given Reducer can be called?

A) As soon as a mapper has emitted at least one record.
B) As soon as at least one mapper has finished processing its input split.
C) Not until all mappers have finished processing all records.
D) It depends on the InputFormat used for the job.


5. You want to populate an associative array in order to perform a map-side join. You've decided to put this
information in a text file, place that file into the DistributedCache and read it in your Mapper before any
records are processed. Indentify which method in the Mapper you should use to implement code for
reading the file and populating the associative array?

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


Solutions:

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

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