Apache Cassandra Practice Exam

Apache Cassandra is a distributed NoSQL database management system designed to handle large amounts of data across many commodity servers, providing high availability with no single point of failure. It offers linear scalability and fault tolerance, making it suitable for mission-critical data. Cassandra uses a decentralized architecture based on a peer-to-peer model, where all nodes in the cluster are equal and communicate with each other using a gossip protocol for discovery and coordination. It is known for its ability to handle write-heavy workloads, making it ideal for applications requiring fast writes and reads, such as IoT, real-time analytics, and messaging platforms.
Why is Apache Cassandra important?

• Scalability: Apache Cassandra is highly scalable and can handle large amounts of data across multiple nodes in a distributed cluster.
• High Availability: It offers high availability with no single point of failure, ensuring that data is accessible even if some nodes in the cluster fail.
• Performance: Cassandra is designed for high performance, especially for write-heavy workloads, making it suitable for real-time applications.
• Flexibility: It supports flexible data models, including wide columns, making it suitable for various use cases.
• Fault Tolerance: Cassandra is fault-tolerant and can automatically recover from node failures, ensuring data integrity.
• Decentralized Architecture: Its decentralized architecture allows for easy scalability and resilience to network and hardware failures.
• Ease of Operations: Cassandra's architecture and distributed nature make it relatively easy to operate and manage compared to traditional relational databases for large-scale applications.
  

Who should take the Apache Cassandra Exam?

• Database Administrators
• Database Developers
• Data Engineers
• Big Data Architects
• System Administrators
• Data Scientists
  

Skills Evaluated

The candidate taking the certification exam on Apache Cassandra is typically evaluated for the following skills:

• Understanding of Apache Cassandra
• Data Modeling
• Query Language
• Data Management
• Cluster Management
• Performance Tuning
• Monitoring and Troubleshooting
• Backup and Recovery
  

1. Introduction to Apache Cassandra

   • Overview of Apache Cassandra
   • History and evolution
   • Use cases and applications

2. Apache Cassandra Architecture

   • Distributed architecture
   • Data replication and consistency
   • Partitioning and clustering

3. Data Modeling in Apache Cassandra

   • CQL (Cassandra Query Language)
   • Data modeling best practices
   • Designing for read and write efficiency

4. Cassandra Query Language (CQL)

   • CQL basics
   • Data definition language (DDL) statements
   • Data manipulation language (DML) statements

5. Cluster Management

   • Installing and configuring Cassandra
   • Cluster setup and configuration
   • Adding and removing nodes

6. Performance Tuning and Optimization

   • Tuning for read and write performance
   • Compaction strategies
   • Caching mechanisms

7. Monitoring and Maintenance

   • Monitoring tools and metrics
   • Performance monitoring and optimization
   • Backup and restore strategies

8. Security in Apache Cassandra

   • Authentication and authorization
   • Data encryption
   • Security best practices

9. Advanced Topics

   • Multi-data center deployments
   • Batch processing
   • Using Apache Cassandra with other technologies (e.g., Spark, Kafka)

10. Best Practices and Use Cases

    • Design patterns
    • Real-world use cases
    • Lessons learned from production deployments