Hortonworks Apache-Hadoop-Developer : Hadoop 2.0 Certification exam for Pig and Hive Developer

Apache-Hadoop-Developer real exams

Exam Code: Apache-Hadoop-Developer

Exam Name: Hadoop 2.0 Certification exam for Pig and Hive Developer

Updated: Jul 17, 2026

Q & A: 110 Questions and Answers

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Hortonworks Apache-Hadoop-Developer Exam Syllabus Topics:

SectionObjectives
Topic 1: Data Ingestion- Import data into Hadoop
  • 1. Use Flume for log and event data ingestion
  • 2. Use Sqoop for relational data import
Topic 2: Data Processing- End-to-end Hadoop workflows
  • 1. Analyze structured and semi-structured data
  • 2. Produce required output using Hadoop ecosystem tools
Topic 3: Data Analysis with Hive- Hive query development
  • 1. Create and manage databases and tables
  • 2. Write queries, joins, aggregations and partitions
Topic 4: Data Transformation with Pig- Pig Latin programming
  • 1. Load, filter, join, group and aggregate data
  • 2. Transform and process datasets

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

1. Your client application submits a MapReduce job to your Hadoop cluster. Identify the Hadoop daemon on which the Hadoop framework will look for an available slot schedule a MapReduce operation.

A) DataNode
B) NameNode
C) TaskTracker
D) JobTracker
E) Secondary NameNode


2. 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, 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.
B) 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.
C) 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.
D) There is no difference in output between the two settings.


3. Identify the MapReduce v2 (MRv2 / YARN) daemon responsible for launching application containers and monitoring application resource usage?

A) NodeManager
B) ApplicationMasterService
C) TaskTracker
D) JobTracker
E) ResourceManager
F) ApplicationMaster


4. Which best describes what the map method accepts and emits?

A) It accepts a single key-value pairs as input and can emit any number of key-value pair as output, including zero.
B) It accepts a list key-value pairs as input and can emit only one key-value pair as output.
C) It accepts a single key-value pair as input and emits a single key and list of corresponding values as output.
D) It accepts a single key-value pairs as input and can emit only one key-value pair as output.


5. For each input key-value pair, mappers can emit:

A) As many intermediate key-value pairs as designed, but they cannot be of the same type as the input key-value pair.
B) One intermediate key-value pair, but of the same type.
C) One intermediate key-value pair, of a different type.
D) As many intermediate key-value pairs as designed. There are no restrictions on the types of those key-value pairs (i.e., they can be heterogeneous).
E) As many intermediate key-value pairs as designed, as long as all the keys have the same types and all the values have the same type.


Solutions:

Question # 1
Answer: D
Question # 2
Answer: A
Question # 3
Answer: A
Question # 4
Answer: A
Question # 5
Answer: E

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