
Answer-first summary for fast verification
Answer: All datasets will be updated once and the pipeline will shut down. The compute resources will persist to allow for additional testing
Let’s break this down carefully. **Key facts from the question:** - **Pipeline mode:** Development mode - **Trigger type:** Triggered Pipeline Mode - **Table types:** - Two datasets: `STREAMING LIVE TABLE` - Three datasets: `LIVE TABLE` (against Delta Lake sources) - Previously unprocessed data exists. - All definitions are valid. --- ### 1. Understanding **Development mode** in DLT In Development mode: - The pipeline performs **one update** of the DAG and then shuts down. - Compute resources are **kept alive** for a period (default 30 minutes or so) to allow for iterative development — meaning you can start it again quickly without cluster startup time. --- ### 2. Understanding **Triggered** vs. **Continuous** in this context - **Triggered** = Run once (in Production mode, that means process available data then stop; in Dev mode, same but compute persists for developer convenience). - **Continuous** = Run forever (only available in Production mode). Since this is **Development mode** + **Triggered**, the behavior is: 1. Process all available data through the DAG once. 2. Pipeline run stops (status: **Completed**). 3. Compute **does not terminate immediately** — it stays available for the developer to run again without waiting for cluster startup. --- ### 3. Impact of mixed streaming and batch tables - `STREAMING LIVE TABLE`: In Triggered mode, these will process only new data since last run (or all data if first run). - `LIVE TABLE` (batch): In Triggered mode, these will run once. All datasets are updated **once** in a single DAG execution, then the pipeline stops. --- ### 4. Matching to options - **A**: Shuts down + compute terminated — ❌ Incorrect, because in Dev mode compute persists. - **B**: Updates at intervals until shut down — ❌ That’s Continuous mode, not Triggered. - **C**: Updates at intervals + compute persists after stop — ❌ Again, intervals imply Continuous. - **D**: Updates once, pipeline shuts down, compute persists — ✅ Matches Dev + Triggered. - **E**: Updates continuously, doesn’t shut down — ❌ That’s Continuous in Production mode. --- **Correct answer: D**
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Question 36 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 Triggered Pipeline Mode.
Assuming previously unprocessed data exists and all definitions are valid, what is the expected outcome after clicking Start to update the pipeline?
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 be deployed for the update and terminated when the pipeline is stopped.
C
All datasets will be updated at set intervals until the pipeline is shut down. The compute resources will persist after the pipeline is stopped to allow for additional testing.
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 continuously and the pipeline will not shut down. The compute resources will persist with the pipeline