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HDPCD Exam Format | HDPCD Course Contents | HDPCD Course Outline | HDPCD Exam Syllabus | HDPCD Exam Objectives

Test Detail:
The Hortonworks Data Platform Certified Developer (HDPCD) exam is designed to assess a candidate's knowledge and skills in developing applications using Hortonworks Data Platform (HDP). Here is a detailed description of the test, including the number of questions and time allocation, course outline, exam objectives, and exam syllabus.

Number of Questions and Time:
The HDPCD exam typically consists of a set of hands-on coding exercises that assess a candidate's ability to develop applications using HDP components. The number of exercises may vary, but candidates are usually given a time limit of 2 to 4 hours to complete the exam. The specific number of questions and time allocation may vary depending on the exam version and administration.

Course Outline:
The course outline for the HDPCD exam covers various aspects of developing applications on the Hortonworks Data Platform. The outline may include the following key areas:

1. Hadoop Fundamentals:
- Understanding Hadoop architecture and components
- Working with Hadoop Distributed File System (HDFS)
- Managing and processing data using MapReduce

2. Data Ingestion and Processing:
- Importing and exporting data to/from HDP
- Using Apache Hive for data querying and analysis
- Implementing data transformations using Apache Pig

3. Data Storage and Management:
- Working with Apache HBase for NoSQL database operations
- Managing data using Apache Oozie workflows
- Implementing data partitioning and compression techniques

4. Data Analysis and Visualization:
- Performing data analysis using Apache Spark
- Visualizing data using Apache Zeppelin or Apache Superset
- Utilizing machine learning algorithms with Apache Spark MLlib

Exam Objectives:
The objectives of the HDPCD exam are to evaluate candidates' proficiency in developing applications on the Hortonworks Data Platform. The exam aims to assess the following key skills:

1. Understanding Hadoop fundamentals and its ecosystem components.
2. Implementing data ingestion and processing using tools like Hive and Pig.
3. Managing and analyzing data using HBase, Oozie, and Spark.
4. Demonstrating proficiency in coding with Hadoop APIs and frameworks.
5. Applying best practices for data storage, management, and analysis.

Exam Syllabus:
The exam syllabus for the HDPCD exam typically includes a set of hands-on coding exercises that test candidates' ability to solve real-world problems using HDP components. The exercises may cover topics such as data ingestion, data processing, data storage, data analysis, and data visualization. Candidates should be familiar with the syntax and usage of Hadoop APIs and tools, including MapReduce, Hive, Pig, HBase, Oozie, and Spark.

Candidates should refer to the official HDPCD exam documentation, study materials, and resources provided by Hortonworks or authorized training partners for accurate and up-to-date information on the specific topics and content covered in the exam. It is recommended to allocate sufficient time for exam preparation, including hands-on practice with HDP components and solving coding exercises.

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