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Hortonworks HADOOP-PR000007

HADOOP-PR000007

Exam Code: HADOOP-PR000007

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

Updated: Sep 22, 2026

Q & A: 110 Questions and Answers

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Hortonworks HADOOP-PR000007 Exam Syllabus Topics:

SectionWeightObjectives
Data Ingestion & Ecosystem Integration5%- Sqoop and Flume usage basics
- Workflow orchestration with Oozie
Apache Pig Development40%- User-defined functions (UDFs) and optimization
- Integration with HCatalog and Hive
- Pig Latin syntax, data loading, and storage
- Data transformation, filtering, grouping, and joining
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. HCatalog
B. Ambari
C. Sqoop
D. Flume


Question #2
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. configure
B. combine
C. init
D. map


Question #3
You want to understand more about how users browse your public website, such as which pages they
visit prior to placing an order. You have a farm of 200 web servers hosting your website. How will you
gather this data for your analysis?

A. Channel these clickstreams inot Hadoop using Hadoop Streaming.
B. Import all users' clicks from your OLTP databases into Hadoop, using Sqoop.
C. Ingest the server web logs into HDFS using Flume.
D. Sample the weblogs from the web servers, copying them into Hadoop using curl.
E. Write a MapReduce job, with the web servers for mappers, and the Hadoop cluster nodes for reduces.


Question #4
You've written a MapReduce job that will process 500 million input records and generated 500 million
key-value pairs. The data is not uniformly distributed. Your MapReduce job will create a significant
amount of intermediate data that it needs to transfer between mappers and reduces which is a potential
bottleneck. A custom implementation of which interface is most likely to reduce the amount of
intermediate data transferred across the network?

A. InputFormat
B. Writable
C. Partitioner
D. WritableComparable
E. OutputFormat
F. Combiner


Question #5
Which best describes how TextInputFormat processes input files and line breaks?

A. The input file is split exactly at the line breaks, so each RecordReader will read a series of complete
lines.
B. Input file splits may cross line breaks. A line that crosses file splits is read by the RecordReader of the
split that contains the end of the broken line.
C. Input file splits may cross line breaks. A line that crosses file splits is read by the RecordReaders of
both splits containing the broken line.
D. Input file splits may cross line breaks. A line that crosses file splits is read by the RecordReader of the
split that contains the beginning of the broken line.
E. Input file splits may cross line breaks. A line that crosses file splits is ignored.


Solutions:

Question #1
Correct Answer: D
Question #2
Correct Answer: A
Question #3
Correct Answer: C
Question #4
Correct Answer: F
Question #5
Correct Answer: D

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