Course Outline
Introduction to Apache Spark
- The role of Spark in big data processing.
- Spark architecture and its components.
Setting Up Apache Spark
- Hardware and software requirements.
- Installation procedures for standalone and cluster modes.
- Configuration best practices for system administrators.
Administering Spark Clusters
- Cluster management tools and techniques.
- Monitoring Spark applications and cluster resources.
- Security configurations and user management.
Performance Tuning and Optimization
- Resource allocation and scheduling.
- Tuning Spark for optimal performance.
- Identifying and resolving common bottlenecks.
Troubleshooting and Problem-Solving
- Common Spark administration challenges.
- Diagnostic tools and techniques for troubleshooting.
- Step-by-step approach to resolving common issues.
- Best practices for maintaining a healthy Spark environment.
Advanced Administration Topics
- Integration with other big data tools.
- Ensuring high availability and disaster recovery.
- Upgrading and scaling Spark clusters.
Summary and Next Steps
Requirements
- Basic knowledge of network configuration and management.
- Familiarity with the Linux operating system and the command-line interface.
- Interest in learning about distributed computing systems and big data management.
Audience
- System administrators.
Testimonials (3)
A journey through the Spark world: a very intense course. DSL, spark sql, partitioning vs bucketing for me.
Georgiana Elisabeta
Course - Apache Spark Fundamentals
I liked that it was practical. Loved to apply the theoretical knowledge with practical examples.
Aurelia-Adriana - Allianz Services Romania
Course - Python and Spark for Big Data (PySpark)
The fact that we were able to take with us most of the information/course/presentation/exercises done, so that we can look over them and perhaps redo what we didint understand first time or improve what we already did.
