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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
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