- Lessons
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GitHub repository for class labs
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Stream Processing Concepts 15 min
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Transforming a Data Stream 7 min
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Lab 1: Initial Setup 10 min
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Lab 2: Basic Data Transformations 10 min
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Streaming and the Hazelcast Platform 6 min
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Lab 3: Using the IMap for Event Processing 10 min
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Enrichment 6 min
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Lab 4: Enriching the Data Stream 10 min
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Stateful Processing and Aggregation 11 min
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Lab 5: Stateful Operations on Streams 10 min
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Lab 6: Windows, Aggregation, and Grouping 10 min
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From Development to Production
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Lab 7: Deploying Your Pipeline 15 min
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Capstone Lab: The Machine Shop 30 min
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Give us your feedback! - Post-course Survey
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Stream Processing with the Hazelcast Pipeline API
NEW COURSE! Learn to use the Pipeline API in Java to build a wide range of streaming applications
Through conceptual overviews and hands-on practice, you will learn to create stream processing applications using the Hazelcast Pipeline API in Java. By the end of the course, you will have built and run distributed streaming pipelines to transform, enhance, and aggregate streaming data. You will be able to apply these operations in a variety of use cases, from streaming ETL to real-time data analytics to event-driven applications. At the end of the course, you will create a complete event-driven application that modifies machine shop operations based on real-time telemetry.
This class is for Java programmers who want to take their first steps in understanding and working with streaming events as well as for those who are already experienced in building data processing applications and want to learn more about working with streaming data. You should be familiar with declarative programming and Java lambdas to get the most out of this course.
Recommended prerequisite:
- Hazelcast Platform Essentials