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Hortonworks APACHE-HADOOP-DEVELOPER Exam Actual Questions
Hadoop 2.0 Certification exam for Pig and Hive Developer

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  • APACHE-HADOOP-DEVELOPER Exam Questions
  • Questions: 44 Q&A
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  • Last Updated: 05 May, 2025
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Passing the Hortonworks APACHE-HADOOP-DEVELOPER (Hadoop 2.0 Certification exam for Pig and Hive Developer)

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APACHE-HADOOP-DEVELOPER Exam Objectives & Details

As the world generates more and more data every day, the need for professionals who can manage and analyze it is growing rapidly. The Apache Hadoop ecosystem has become the go-to solution for big data processing and storage, and Hortonworks is one of the leading providers of Hadoop-based products and services. To help developers demonstrate their skills in Hadoop and related technologies, Hortonworks offers the APACHE-HADOOP-DEVELOPER Hadoop 2.0 Certification for Pig and Hive Developer exam. In this guide, we will discuss the exam objectives, the exam details, the prerequisites and qualifications for taking the exam, and some recommended study materials.

Exam Objectives:

The APACHE-HADOOP-DEVELOPER Hadoop 2.0 Certification for Pig and Hive Developer exam is designed to test a developer's knowledge of Apache Pig and Hive as well as their ability to develop Hadoop-based applications. The exam objectives include:
  • Understanding the fundamentals of Hadoop and MapReduce
  • Working with HDFS and YARN
  • Creating and managing tables in Hive
  • Writing and optimizing HiveQL queries
  • Working with Pig Latin and understanding Pig's data model
  • Writing Pig Latin scripts and debugging Pig code
  • Developing MapReduce jobs in Java
  • Debugging and tuning MapReduce jobs

Exam Details:

The APACHE-HADOOP-DEVELOPER Hadoop 2.0 Certification for Pig and Hive Developer exam is a performance-based exam that is taken on a remote Hadoop cluster. The exam costs $250 USD and candidates have 2 hours to complete it. The passing score is 70% and the exam is delivered online in a proctored format.

Who Should Take the Exam?

The APACHE-HADOOP-DEVELOPER Hadoop 2.0 Certification for Pig and Hive Developer exam is designed for developers who have experience working with Hadoop and want to demonstrate their skills in developing applications using Pig and Hive. It is also suitable for software engineers, data engineers, and data analysts who want to improve their knowledge of Hadoop and big data processing.

Prerequisites and Qualifications:

To take the APACHE-HADOOP-DEVELOPER Hadoop 2.0 Certification for Pig and Hive Developer exam, candidates should have a good understanding of Hadoop fundamentals and be proficient in Java programming. Hortonworks recommends that candidates have at least 1-2 years of experience working with Hadoop and related technologies before taking the exam.

Related Books:

There are several books that can help candidates prepare for the APACHE-HADOOP-DEVELOPER Hadoop 2.0 Certification for Pig and Hive Developer exam. Some recommended titles include:
  • "Programming Hive" by Edward Capriolo, Dean Wampler, and Jason Rutherglen
  • "Hadoop: The Definitive Guide" by Tom White
  • "Apache Pig: Essential Recipes for Beginners" by Aravind Prabhakar
  • "Data Analytics with Hadoop: An Introduction for Data Scientists" by Benjamin Bengfort, Jenny Kim, and Jenny Kim
  • "Learning Spark: Lightning-Fast Big Data Analysis" by Holden Karau, Andy Konwinski, Patrick Wendell, and Matei Zaharia
In conclusion, the APACHE-HADOOP- DEVELOPER Hadoop 2.0 Certification for Pig and Hive Developer exam is a great way for developers to demonstrate their proficiency in developing Hadoop-based applications using Pig and Hive. By passing the exam, candidates can prove to employers and clients that they have the skills and knowledge needed to work with big data and Hadoop. Candidates who are interested in taking the exam should review the exam objectives, ensure they meet the prerequisites and qualifications, and study the recommended materials. With the right preparation and knowledge, passing the APACHE-HADOOP-DEVELOPER Hadoop 2.0 Certification for Pig and Hive Developer exam can be a great step towards a career in big data and Hadoop development.

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