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Hortonworks Apache-Hadoop-Developer Exam Braindumps - in .pdf Free Demo

  • Exam Code: Apache-Hadoop-Developer
  • Exam Name: Hadoop 2.0 Certification exam for Pig and Hive Developer
  • , Last Updated: Aug 09, 2026
  • Q & A: 110 Questions and Answers
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  • Exam Code: Apache-Hadoop-Developer
  • Exam Name: Hadoop 2.0 Certification exam for Pig and Hive Developer
  • , Last Updated: Aug 09, 2026
  • Q & A: 110 Questions and Answers
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Hortonworks Apache-Hadoop-Developer Exam Syllabus Topics:

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

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

1. You want to run Hadoop jobs on your development workstation for testing before you submit them to your production cluster. Which mode of operation in Hadoop allows you to most closely simulate a production cluster while using a single machine?

A) Run the hadoop command with the -jt local and the -fs file:///options.
B) Run all the nodes in your production cluster as virtual machines on your development workstation.
C) Run simldooop, the Apache open-source software for simulating Hadoop clusters.
D) Run the DataNode, TaskTracker, NameNode and JobTracker daemons on a single machine.


2. Consider the following two relations, A and B.

Which Pig statement combines A by its first field and B by its second field?

A) C = JOIN A by al, B by b2;
B) C = DOIN B BY a1, A by b2;
C) C = JOIN A SO, B $1;
D) C = JOIN A a1, B b2;


3. In a MapReduce job, the reducer receives all values associated with same key. Which statement best describes the ordering of these values?

A) The values are arbitrary ordered, but multiple runs of the same MapReduce job will always have the same ordering.
B) The values are arbitrarily ordered, and the ordering may vary from run to run of the same MapReduce job.
C) Since the values come from mapper outputs, the reducers will receive contiguous sections of sorted values.
D) The values are in sorted order.


4. Which one of the following statements describes the relationship between the NodeManager and the ApplicationMaster?

A) The ApplicationMaster starts the NodeManager in a Container
B) The NodeManager requests resources from the ApplicationMaster
C) The NodeManager creates an instance of the ApplicationMaster
D) The ApplicationMaster starts the NodeManager outside of a Container


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


Solutions:

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

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