HortonWorks Assessment Test

A Hortonworks Assessment Test evaluates candidates on their proficiency with Hortonworks Data Platform (HDP), a popular distribution of Apache Hadoop that includes various components for big data processing and analysis. The assessment typically covers a range of topics related to Hadoop ecosystem components, data management, and analytical capabilities provided by Hortonworks.

A Hortonworks Assessment Test evaluates candidates for:

1. Introduction to Hortonworks and Hadoop:

• Overview of Hortonworks: Understanding the purpose and features of Hortonworks Data Platform (HDP) and its role in big data processing.
• Hadoop Ecosystem: Knowledge of the Hadoop ecosystem, including core components like Hadoop Distributed File System (HDFS) and MapReduce.

2. Hadoop Architecture:

• Hadoop Architecture: Understanding the architecture of Hadoop, including NameNode, DataNode, ResourceManager, and NodeManager.
• HDFS: Knowledge of HDFS, its architecture, and how it handles storage and data replication.

3. Data Ingestion and Storage:

• Data Ingestion Tools: Familiarity with tools for data ingestion into Hadoop, such as Apache Flume, Apache Sqoop, and Apache Nifi.
• Data Storage: Skills in configuring and managing data storage within HDFS and understanding data partitioning and replication.

4. Data Processing and Analytics:

• MapReduce: Knowledge of writing and optimizing MapReduce jobs for data processing.
• Apache Hive: Understanding of Hive for SQL-like querying on Hadoop and skills in writing Hive queries.
• Apache Pig: Familiarity with Pig Latin for data transformation and analysis.
• Apache Spark: Knowledge of Spark for in-memory data processing and its integration with Hadoop.

5. Cluster Management and Configuration:

• Cluster Setup: Skills in setting up and configuring a Hadoop cluster using Hortonworks tools.
• YARN: Understanding of Yet Another Resource Negotiator (YARN) for resource management and job scheduling in Hadoop.

6. Data Management and Governance:

• Data Management: Knowledge of data management practices, including data lifecycle management and data governance.
• Apache Ranger: Familiarity with Apache Ranger for security and data access control.
• Apache Atlas: Understanding of Apache Atlas for metadata management and data lineage.

7. Performance Optimization:

• Performance Tuning: Skills in tuning Hadoop components and jobs for improved performance and efficiency.
• Monitoring: Familiarity with monitoring tools and techniques for assessing cluster health and performance.

8. Security and Compliance:

• Security Features: Knowledge of Hadoop security features, including Kerberos authentication and data encryption.
• Compliance: Understanding of compliance requirements and ensuring that Hadoop implementations meet regulatory standards.

9. Data Visualization and Reporting:

• Data Visualization: Skills in using tools for data visualization and reporting, such as Apache Zeppelin or integration with BI tools like Tableau.
• Reporting: Knowledge of generating reports and dashboards based on data stored in Hadoop.

10. Integration with Other Tools:

• Integration: Understanding of how Hortonworks integrates with other data processing and analytics tools, including data lakes, cloud services, and external databases.
• ETL Processes: Familiarity with ETL (Extract, Transform, Load) processes and tools for integrating data with Hadoop.

11. Best Practices:

• Implementation Best Practices: Knowledge of best practices for implementing and managing a Hortonworks Data Platform environment.
• Data Processing Patterns: Understanding of common data processing patterns and strategies for efficient big data processing.

Assessment Formats:

• Multiple-Choice Questions: To test theoretical knowledge of Hortonworks and Hadoop concepts, features, and functionalities.
• Practical Exercises: To assess hands-on skills in configuring Hadoop clusters, writing MapReduce jobs, and using data processing tools.
• Case Studies: To evaluate the application of Hortonworks skills in real-world scenarios, including performance optimization, security implementation, and data management.

This assessment ensures that candidates have the necessary skills to effectively use Hortonworks Data Platform for big data processing and analytics, from cluster setup and configuration to data management and performance optimization.