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3.4.2. Eventstreams and Event Processors
💡 First Principle: Eventstreams route events from sources to destinations, and event processors provide no-code transformations during routing. Think of it like a mail sorting facility that can also open envelopes, remove junk mail, and repackage before delivery.
Scenario: IoT sensors send data with unnecessary fields (device diagnostics). The event processor removes these columns before storing in the lakehouse, reducing storage costs.
Eventstream Sources
- Azure Event Hubs
- Azure IoT Hub
- Custom applications (SDK)
- Sample data (for testing)
Eventstream Destinations
- Lakehouse (Delta tables)
- KQL Database
- Derived Eventstream (chaining)
- Custom endpoint
Event Processor Operations
| Operation | Purpose | Use Case |
|---|---|---|
| Filter | Remove unwanted events | Drop diagnostic messages |
| Manage fields | Select/rename columns | Remove unnecessary columns |
| Aggregate | Compute statistics | Count events per minute |
| Group by | Partition events | Separate by device type |
| Union | Combine streams | Merge multiple sources |
⚠️ Exam Trap: Azure Data Factory is designed for batch orchestration, not real-time event processing. For streaming workloads, use Eventstreams. Questions mentioning "real-time" or "continuous" processing require streaming components, not ADF.
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Written byAlvin Varughese
Founder•18 professional certifications