Databricks Certified Data Engineer - Associate
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A Delta Live Table pipeline includes two datasets defined using STREAMING LIVE TABLE. Three datasets are defined against Delta Lake table sources using LIVE TABLE. The table is configured to run in Development mode using the Continuous Pipeline Mode. Assuming previously unprocessed data exists and all definitions are valid, what is the expected outcome after clicking Start to update the pipeline?
Real Exam
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KKeng
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A
All datasets will be updated once and the pipeline will shut down. The compute resources will be terminated.
B
All datasets will be updated at set intervals until the pipeline is shut down. The compute resources will persist until the pipeline is shut down.
C
All datasets will be updated once and the pipeline will persist without any processing. The compute resources will persist but go unused.
D
All datasets will be updated once and the pipeline will shut down. The compute resources will persist to allow for additional testing.
E
All datasets will be updated at set intervals until the pipeline is shut down. The compute resources will persist to allow for additional testing.
Explanation:
Explanation
In Delta Live Tables (DLT), when a pipeline is configured in Development mode with Continuous Pipeline Mode:
-
Development mode is designed for interactive development and testing, where:
- The pipeline runs continuously
- Compute resources persist after processing
- This allows for additional testing and development without restarting resources
-
Continuous Pipeline Mode means the pipeline will:
- Process data continuously at set intervals
- Keep running until manually stopped
- Monitor for new data and process it automatically
-
The pipeline includes both streaming datasets (STREAMING LIVE TABLE) and batch datasets (LIVE TABLE):
- Streaming datasets will continuously process new data
- Batch datasets will be updated based on their refresh schedule
-
The key characteristics of Development mode with Continuous Pipeline Mode are:
- Continuous processing at set intervals
- Persistent compute resources that remain available for testing
- The pipeline doesn't shut down after one execution
Therefore, option E correctly describes that:
- All datasets will be updated at set intervals (continuous processing)
- The pipeline runs until manually shut down
- Compute resources persist to allow for additional testing
This differs from Production mode where resources might be terminated after processing to save costs, and from Triggered mode where the pipeline runs once and then stops.
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