Overview
In rare cases, a workflow may fail with an error indicating that the SparkContext was shut down.
This type of failure is usually related to a temporary Spark cluster or resource issue, not to query logic or data configuration.
This article explains why this error occurs, how to recover quickly, and what to do if it happens again.
Symptoms
You may observe one or more of the following:
Daily or full workflow fails unexpectedly
Failure occurs during a domain transform or database generation step
Error message mentions SparkContext shutdown
Re-running the workflow later succeeds
No recent configuration or data changes were made
Common Error Message
You may see an error similar to:
Job cancelled because SparkContext was shut down
This means the Spark driver or cluster stopped during job execution.
Why This Happens
This error typically occurs due to a rare Spark driver or cluster interruption, such as:
Loss of executors during job startup
Temporary cluster instability
Internal resource reallocation
These failures are uncommon and are not caused by:
Query errors
Data issues
Workflow misconfiguration
How to Resolve the Issue
In most cases, the solution is simple.
Steps to Fix
Open the failed workflow
Identify the failed task
Restart the workflow or retry the failed task
Monitor the run until completion
A restart allows the workflow to run on a fresh Spark cluster, which typically resolves the issue.
Important Timing Consideration
If workflows run on a fixed schedule:
Restart failed workflows as soon as possible
This helps avoid conflicts with the next scheduled run
Early action prevents downstream delays
When to Contact Support
You should contact Support if:
The same SparkContext error happens repeatedly
Restarting the workflow does not resolve the issue
Multiple workflows fail with similar errors
Failures become frequent or consistent
Support can then investigate deeper platform-level trends.
Best Practices
Monitor workflows regularly for failures
Restart failed jobs promptly when errors appear
Avoid waiting for the next scheduled run if a failure occurs
Track rare failures to identify patterns over time
Summary
A “SparkContext was shut down” error is a rare, temporary execution issue related to Spark resources.
Restarting the failed workflow usually resolves the problem immediately.
Staying alert to workflow failures and acting quickly helps keep data pipelines running smoothly.
Applies To
Full daily workflows
Domain transforms
Database generation steps
Spark-based processing
Workflow monitoring and recovery