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Apache Storm

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Apache Storm

Apache Strom

Duration
45 Hours

Course Description

            An Apache Storm course typically covers the fundamentals of real-time stream processing using Apache Storm, including its architecture, components, and practical applications. Students will learn about Storm's core concepts like spouts and bolts, how to build and deploy topologies, and how to integrate Storm with other technologies like Kafka and ZooKeeper. The course also delves into advanced topics like Trident, a high-level abstraction for stateful stream processing. 

Course Outline For Apache Storm

1. Introduction to Big Data and real-time processing

  • Understanding Big Data concepts and the need for real-time processing.
  • Differentiating between batch processing (like Hadoop) and real-time stream processing (like Storm).
  • Exploring the limitations of traditional batch processing for certain use cases.
  • Use cases and benefits of real-time data processing with Apache Storm, including fraud detection, real-time analytics, and personalized recommendations. 

2. Apache Storm fundamentals

  • Introducing Apache Storm, its origin, key features, and advantages.
  • Understanding core concepts like tuples, streams, spouts, bolts, and topologies.
  • Comparison of Apache Storm with other real-time processing systems such as Apache Spark and Apache Flink. 

3. Apache Storm architecture

  • Master-slave architecture, including Nimbus (master node) and Supervisors (worker nodes).
  • Understanding the role of ZooKeeper in coordinating the cluster and maintaining state.
  • How data flows through the Storm cluster.
  • Concepts of parallelism and fault tolerance in Apache Storm. 

4. Building Storm topologies

  • Designing and creating topologies using spouts and bolts.
  • Implementing spouts for data ingestion from various sources (e.g., Kafka, APIs, files).
  • Developing bolts for data processing, including filtering, aggregation, and transformations.
  • Defining stream groupings to control how data is distributed among bolts. 

5. Apache Storm Trident

  • Introduction to Trident, a high-level abstraction for stateful stream processing with operations like joins, aggregations, and windowing, and its use for complex transformations and exactly-once processing. 

6. Installation, configuration, and management

  • Installing and setting up, configuring, and monitoring Storm clusters.
  • Troubleshooting common deployment issues. 

7. Integration with other technologies

  • Integrating Apache Storm with message queuing systems like Apache Kafka and other Big Data tools like Apache Hadoop and Apache Spark.
  • Using Apache Storm as part of a larger Big Data infrastructure. 

8. Advanced concepts and best practices

  • Exploring advanced stream grouping strategies.
  • Tuning and optimizing Storm topologies for performance.
  • Handling message reliability and fault tolerance.
  • Security aspects. 

9. Real-world projects and case studies

  • Analyzing real-world applications of Apache Storm and working on practical projects. 
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