Exam Name: Hortonworks-Certified-Apache-Hadoop-2.0-Developer(Pig and Hive Developer)
Certification Provider: Hortonworks
Corresponding Certification: HDP Certified Developer
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Updated: Sep 09, 2026
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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:
Identify the tool best suited to import a portion of a relational database every day as files into HDFS, and
generate Java classes to interact with that imported data?
- A. Oozie
- B. Pig
- C. Sqoop
- D. fuse-dfs
- E. Hue
- F. Hive
- G. Flume
Examine the following Hive statements:
Assuming the statements above execute successfully, which one of the following statements is true?
- A. The output of each reducer is only the age column
- B. The SORT BY command causes only one reducer to be used
- C. Each reducer generates a file sorted by age
- D. The output is guaranteed to be a single file with all the data sorted by age
Which one of the following statements describes the relationship between the NodeManager and the
ApplicationMaster?
- A. The NodeManager requests resources from the ApplicationMaster
- B. The ApplicationMaster starts the NodeManager outside of a Container
- C. The ApplicationMaster starts the NodeManager in a Container
- D. The NodeManager creates an instance of the ApplicationMaster
What types of algorithms are difficult to express in MapReduce v1 (MRv1)?
- A. Large-scale graph algorithms that require one-step link traversal.
- B. Relational operations on large amounts of structured and semi-structured data.
- C. Algorithms that require applying the same mathematical function to large numbers of individual binary
records. - D. Algorithms that require global, sharing states.
- E. Text analysis algorithms on large collections of unstructured text (e.g, Web crawls).
When can a reduce class also serve as a combiner without affecting the output of a MapReduce program?
- A. When the signature of the reduce method matches the signature of the combine method.
- B. Always. The point of a combiner is to serve as a mini-reducer directly after the map phase to increase performance.
- C. Always. Code can be reused in Java since it is a polymorphic object-oriented programming language.
- D. 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.
- E. Never. Combiners and reducers must be implemented separately because they serve different purposes.
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