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Hortonworks Apache-Hadoop-Developer

Apache-Hadoop-Developer

Exam Code: Apache-Hadoop-Developer

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

Updated: Aug 01, 2026

Q&A Number: 110 Q&As

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Hortonworks Apache-Hadoop-Developer Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Apache Hive Development25%- Use Hive functions, views, and metastore
- Create and manage Hive tables, partitions, and buckets
- Write and optimize HiveQL queries
Topic 2: Hadoop Fundamentals & Architecture20%- YARN architecture and job execution
- MapReduce concepts and job lifecycle
- HDFS operations and file management
Topic 3: Data Ingestion25%- Ingest streaming data with Flume
- Load data into HDFS from external sources
- Import/export data using Sqoop
Topic 4: Apache Pig Development30%- Data transformation, filtering, joining, and aggregation
- Debug and tune Pig jobs
- Write and optimize Pig Latin scripts

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

1. You have a directory named jobdata in HDFS that contains four files: _first.txt, second.txt, .third.txt and #data.txt. How many files will be processed by the FileInputFormat.setInputPaths () command when it's given a path object representing this directory?

A) Three, the pound sign is an invalid character for HDFS file names
B) None, the directory cannot be named jobdata
C) Four, all files will be processed
D) Two, file names with a leading period or underscore are ignored
E) One, no special characters can prefix the name of an input file


2. Your cluster's HDFS block size in 64MB. You have directory containing 100 plain text files, each of which is 100MB in size. The InputFormat for your job is TextInputFormat. Determine how many Mappers will run?

A) 640
B) 200
C) 64
D) 100


3. What types of algorithms are difficult to express in MapReduce v1 (MRv1)?

A) Algorithms that require applying the same mathematical function to large numbers of individual binary records.
B) Algorithms that require global, sharing states.
C) Relational operations on large amounts of structured and semi-structured data.
D) Text analysis algorithms on large collections of unstructured text (e.g, Web crawls).
E) Large-scale graph algorithms that require one-step link traversal.


4. Which one of the following statements describes a Hive user-defined aggregate function?

A) Operates on multiple input rows and creates a single row as output
B) Operates on a single input row and produces a table as output
C) Operates on multiple input rows and produces a table as output
D) Operates on a single input row and produces a single row as output


5. Given the following Hive commands:

Which one of the following statements Is true?

A) The file mydata.txt does not move from Its current location in HDFS
B) The file mydata.txt is moved to a subfolder of /apps/hive/warehouse
C) The file mydata.txt is copied into Hive's underlying relational database 0.
D) The file mydata.txt is copied to a subfolder of /apps/hive/warehouse


Solutions:

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

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