Apache Flink Course Online

SKU: 2299
8 Lesson
|
32 Hours
igmGuru offers the best Apache Flink Training globally for learners of all levels. This comprehensive training program builds a strong foundation in Apache Flink by covering everything from stream processing fundamentals to advanced real-time data analytics and deployment techniques. This Apache Flink course covers key topics such as Flink architecture, DataStream and Table APIs, event time and windowing, state management, fault tolerance, integration with Kafka and other data sources, deployment on clusters, performance optimization, monitoring, and many more essential concepts to help you master real-time data processing with Apache Flink.

Overview

Prerequisites:

  • Familiarity with Java or Scala, as Flink uses these languages.
  • Understanding of distributed systems (e.g., fault tolerance, partitioning).
  • Knowledge of event time vs. processing time, windowing, and watermarks.
  • Proficiency with SQL for querying data streams (Flink SQL).
  • Basic understanding of tools like Hadoop and Kafka for data processing and messaging.

What You Will Learn

  1. Understand Apache Flink’s architecture and core concepts.
  2. Learn the difference between batch and stream processing.
  3. Build data pipelines using the DataStream and DataSet APIs.
  4. Work with sources, sinks, and data transformations.
  5. Implement event time processing, windowing, and watermarks.
  6. Write streaming queries using Flink SQL and Table API.
  7. Manage stateful stream processing with checkpoints and savepoints.
  8. Integrate Flink with Kafka, HDFS, databases, and other systems.
  9. Deploy and monitor Flink jobs on Standalone, YARN, or Kubernetes.
  10. Optimize Flink applications for scalability and performance.
  11. Explore advanced features like Complex Event Processing (CEP).

Latest Trends in 2025-2026

  • Flink 2.0+ Updates: New state management and materialized tables.
  • Real-Time AI Integration: ML_PREDICT for streaming AI inference.
  • Process Table Functions: Advanced SQL transformations with state.
  • Delta Join Operator: Optimized streaming joins with less state.
  • Variant Data Type: Better handling of semi-structured data.
  • Elastic Scaling: Dynamic resource and parallelism adjustments.
  • Cloud-Native Support: Improved for Kubernetes and distributed systems.
  • Privacy Enhancements: Anonymization for streaming data.
  • DataStream API V2: Cleaner API with async support.
  • Kubernetes Operator: Better autoscaling and deployment management.

Key Features

Course Curriculum

1. Overview, architecture, and key components
2. Batch vs. stream processing
3. Real-world use cases
1. DataStream and DataSet APIs
2. Sources, sinks, and transformations
3. Keyed streams and aggregations
1. Event time vs. processing time
2. Tumbling, sliding, and session windows
3. Watermarks and late event handling
1. Writing SQL queries for streams and batches
2. Table registration and joins
3. Integrating SQL with DataStream API
1. Stateful stream processing
2. Checkpoints, savepoints, and exactly-once guarantees
3. State backends (e.g., RocksDB)
1. Kafka, HDFS, JDBC, Elasticsearch connectors
2. Configuring and using custom sources/sinks
1. Standalone, YARN, and Kubernetes deployments
2. Job submission, scaling, and performance tuning
3. Monitoring via Flink Web UI and metrics
1. Complex Event Processing (CEP)
2. Performance optimization
3. Machine learning and analytics integration
4. Understanding Flink internals
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Course Fees

Online Class Room Program

US $ 799.00
100% Money Back Guarantee
  • Duration : 32 Hrs
  • Plus Self Paced

Classes Starting From

  • Fast Track Batch 25 Jun 2026
  • Weekday Batch 29 Jun 2026
  • Weekend Batch 27 Jun 2026

Corporate Training

Corporate Training
  • Customized Training Delivery Model
  • Flexible Training Schedule Options
  • Industry Experienced Trainers
  • 24x7 Support

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Apache Flink Certification

We provide a well-recognized Course Completion Certificate for the Apache Flink Training. This certificate validates your hands-on expertise in stream processing, including data transformation, state management, event time and windowing, Flink SQL and Table API, integration with Kafka and other data systems, deployment, and performance optimization using Apache Flink.

Apache Flink Certification

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