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Hortonworks Apache-Hadoop-Developer : Hadoop 2.0 Certification exam for Pig and Hive Developer
- Exam Code: Apache-Hadoop-Developer
- Exam Name: Hadoop 2.0 Certification exam for Pig and Hive Developer
- Updated: Oct 07, 2026
About Hortonworks Apache-Hadoop-Developer Exam
Our experts check the Apache-Hadoop-Developer content for updates every single day, and the moment anything changes, the system notifies customers immediately. On top of that, your purchase includes 365 days of free updates — through 2026 and beyond, your 110 practice questions for the Hortonworks Hadoop 2.0 Certification exam for Pig and Hive Developer never go stale.
Hortonworks Apache-Hadoop-Developer Exam Overview:
| Certification Vendor: | Hortonworks (now part of Cloudera) |
|---|---|
| Exam Name: | Apache Hadoop Developer Exam (Pig and Hive Developer Focus) |
| Exam Number: | Apache-Hadoop-Developer |
| Exam Format: | Scenario-based Questions, Multiple Choice |
| Related Certifications: | Cloudera Data Platform certifications Hortonworks Certified Apache Hadoop Administrator |
| Available Languages: | English |
| Recommended Training: | Apache Pig Documentation Apache Hive Documentation Cloudera Training Courses |
| Exam Registration: | Cloudera Certification Portal |
| Sample Questions: |  |
| Exam Way: | Online proctored exam or authorized test center (varies by provider and time period) |
| Pre Condition: | Basic understanding of Linux, SQL, and distributed computing concepts recommended. |
| Official Syllabus URL: | https://www.cloudera.com/services-and-support/certification.html |
Hortonworks Apache-Hadoop-Developer Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Apache Hive | - HiveQL Query Language
|
| Apache Pig | - Pig execution model
|
| Hadoop Ecosystem Fundamentals | - HDFS Architecture and Data Storage Concepts
|
| Data Processing and Integration | - Hadoop data formats
|
What Candidates Ask About the Hortonworks Hadoop 2.0 Certification exam for Pig and Hive Developer
Registration for the Hortonworks Hadoop 2.0 Certification exam for Pig and Hive Developer goes through these official channels:
One scheduling detail: the Apache-Hadoop-Developer exam is delivered Online proctored exam or authorized test center (varies by provider and time period) — plan accordingly when you book.
The Apache-Hadoop-Developer exam — officially the Hadoop 2.0 Certification exam for Pig and Hive Developer — is Hortonworks's certification test for professionals working with its technologies, and passing it earns the Hortonworks Certified Apache Hadoop Developer certification at the Professional level. Because it is vendor-issued and skills-based, employers can compare candidates on it directly — that is what keeps it valuable. It also connects naturally to Hortonworks Certified Apache Hadoop Administrator, Cloudera Data Platform certifications.
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The Hortonworks Hadoop 2.0 Certification exam for Pig and Hive Developer syllabus spans 4 domains, led by Apache Hive, Apache Pig, and Hadoop Ecosystem Fundamentals. The complete weighted outline is in the syllabus section above — it is the map your preparation should follow.
Basic understanding of Linux, SQL, and distributed computing concepts recommended.
Vendor criteria do change, so before scheduling, verify the latest requirements on the official Hortonworks exam page.
Hortonworks lists these training resources for the Hortonworks Hadoop 2.0 Certification exam for Pig and Hive Developer:
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Hortonworks Hadoop 2.0 Certification exam for Pig and Hive Developer Sample Questions:
Question #1
In a MapReduce job, you want each of your input files processed by a single map task. How do you configure a MapReduce job so that a single map task processes each input file regardless of how many blocks the input file occupies?
- A. Write a custom MapRunner that iterates over all key-value pairs in the entire file.
- B. Write a custom FileInputFormat and override the method isSplitable to always return false.
- C. Set the number of mappers equal to the number of input files you want to process.
- D. Increase the parameter that controls minimum split size in the job configuration.
Correct Answer: B 🗳️
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Question #2
You have written a Mapper which invokes the following five calls to the OutputColletor.collect method:
output.collect (new Text ("Apple"), new Text ("Red") ) ;
output.collect (new Text ("Banana"), new Text ("Yellow") ) ;
output.collect (new Text ("Apple"), new Text ("Yellow") ) ;
output.collect (new Text ("Cherry"), new Text ("Red") ) ;
output.collect (new Text ("Apple"), new Text ("Green") ) ;
How many times will the Reducer's reduce method be invoked?
- A. 1
- B. 3
- C. 6
- D. 0
- E. 5
Correct Answer: B 🗳️
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Question #3
Indentify which method in the Mapper you should use to implement code for reading the file and populating the associative array?
- A. configure
- B. map
- C. combine
- D. init
Correct Answer: A 🗳️
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Question #4
In Hadoop 2.0, which TWO of the following processes work together to provide automatic failover of the NameNode? Choose 2 answers
- A. JournalNode
- B. ZKFailoverController
- C. QuorumManager
- D. ZooKeeper
Correct Answer: A,B 🗳️
Question #5
You wrote a map function that throws a runtime exception when it encounters a control character in input data. The input supplied to your mapper contains twelve such characters totals, spread across five file splits. The first four file splits each have two control characters and the last split has four control characters.
Indentify the number of failed task attempts you can expect when you run the job with mapred.max.map.attempts set to 4:
- A. You will have forty-eight failed task attempts
- B. You will have five failed task attempts
- C. You will have seventeen failed task attempts
- D. You will have twelve failed task attempts
- E. You will have twenty failed task attempts
Correct Answer: E 🗳️
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