DP-203 Develop data processing Practice Question
You are monitoring an Azure Synapse Pipeline that uses a Mapping Data Flow. The data flow processes 2 GB of data from a CSV source and writes to a Delta sink. The pipeline fails with a 'DataFlowException: Operation aborted' error after running for 45 minutes. The cluster is configured with 8 cores. What is the most likely cause?
⚠ Common exam trap
Many candidates confuse the TTL (a Synapse cluster lifecycle setting) with a Spark job timeout or a data volume issue, leading them to incorrectly select cluster size or malformed data as the cause.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The data flow cluster's time-to-live (TTL) is set to 45 minutes and the job exceeded it.
The error 'Operation aborted' after exactly 45 minutes aligns with the default time-to-live (TTL) setting for Azure Synapse Mapping Data Flow clusters. When the TTL expires, the cluster is terminated, and any running job is aborted. The 8-core cluster and 2 GB data volume are not inherently problematic for a 45-minute window, but the TTL default of 45 minutes causes the abort if the job runs longer than that.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The cluster size is too small for the data volume.
Why it's wrong here
2 GB with 8 cores is generally sufficient; the error is not resource-related.
- ✗
The CSV source contains malformed rows that cause parsing errors.
Why it's wrong here
Malformed rows would cause a different error, not 'Operation aborted'.
- ✓
The data flow cluster's time-to-live (TTL) is set to 45 minutes and the job exceeded it.
Why this is correct
The default TTL for data flow clusters is 60 minutes, but if custom set to 45 minutes, the cluster may be terminated during long-running jobs.
- ✗
The data flow is using the Spark cluster's default timeout setting.
Why it's wrong here
Default Spark timeout is typically higher than 45 minutes.
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