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

  • Exam Code: HADOOP-PR000007
  • Exam Name: Hortonworks-Certified-Apache-Hadoop-2.0-Developer(Pig and Hive Developer)
  • Updated: Aug 24, 2026     Q & A: 110 Questions and Answers

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Hortonworks HADOOP-PR000007 Exam Syllabus Topics:

SectionWeightObjectives
Data Ingestion & Ecosystem Integration5%- Workflow orchestration with Oozie
- Sqoop and Flume usage basics
Apache Pig Development40%- User-defined functions (UDFs) and optimization
- Data transformation, filtering, grouping, and joining
- Pig Latin syntax, data loading, and storage
- Integration with HCatalog and Hive
Apache Hive Development35%- HiveQL queries, joins, aggregations, and partitioning
- Performance tuning and indexing
- Data types, serialization, and file formats
- Hive architecture, metastore, and table management
Hadoop Fundamentals & HDFS20%- HDFS file operations, permissions, and data management
- Hadoop 2.0 architecture & YARN

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

Question 1

You want to Ingest log files Into HDFS, which tool would you use?

A. Ambari
B. HCatalog
C. Flume
D. Sqoop


Question 2

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

A. 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.
B. 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.
C. 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.
D. The default partitioner assigns key-values pairs to reduces based on an internal random number
generator.
E. 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.


Question 3

Which one of the following statements describes the relationship between the ResourceManager and the
ApplicationMaster?

A. The ApplicationMaster requests resources from the ResourceManager
B. The ApplicationMaster starts a single instance of the ResourceManager
C. The ResourceManager monitors and restarts any failed Containers of the ApplicationMaster
D. The ApplicationMaster starts an instance of the ResourceManager within each Container


Question 4

Can you use MapReduce to perform a relational join on two large tables sharing a key? Assume that the
two tables are formatted as comma-separated files in HDFS.

A. Yes.
B. Yes, so long as both tables fit into memory.
C. No, but it can be done with either Pig or Hive.
D. No, MapReduce cannot perform relational operations.
E. Yes, but only if one of the tables fits into memory


Question 5

Examine the following Hive statements:

Assuming the statements above execute successfully, which one of the following statements is true?

A. The contents of File1 are parsed as comma-delimited rows and stored in a database
B. The contents of File1 are parsed as comma-delimited rows and loaded into /user/joe/x/
C. The file named File1 is moved to to/user/joe/x/
D. Hive reformats File1 into a structure that Hive can access and moves into to/user/joe/x/


Solutions:

Question 1
Answer: C
Question 2
Answer: B
Question 3
Answer: A
Question 4
Answer: A
Question 5
Answer: C

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