What causes DELTA_LIVE_TABLES_PIPELINE_FAILED?

An upstream dataset threw an unhandled exception during an update cycle. A DLT expectation set to 'fail' mode triggered on too many rows. The pipeline compute cluster ran out of memory processing a large table. A Python or SQL syntax error was introduced in a new pipeline version

How do I fix DELTA_LIVE_TABLES_PIPELINE_FAILED?

Step 1: Open the DLT pipeline in the Databricks UI and click the failed update to view dataset-level error details.. Step 2: Check the event log for the root dataset that first failed — downstream datasets inherit the failure.. Step 3: Fix the underlying code or data issue, then click 'Start' to trigger a full or triggered update.. Step 4: If memory-related, increase the cluster worker count or move to a larger instance type under Pipeline Settings.. Step 5: Add expectation monitoring to surface data quality issues before they cause terminal failures.

Critical severityexecution

Power BI Refresh Error:
DELTA_LIVE_TABLES_PIPELINE_FAILED

What does this error mean?

A Delta Live Tables pipeline stopped with a terminal failure, meaning one or more datasets could not be computed and the pipeline must be restarted manually.

Common causes

1An upstream dataset threw an unhandled exception during an update cycle
2A DLT expectation set to 'fail' mode triggered on too many rows
3The pipeline compute cluster ran out of memory processing a large table
4A Python or SQL syntax error was introduced in a new pipeline version

How to fix it

1Step 1: Open the DLT pipeline in the Databricks UI and click the failed update to view dataset-level error details.
2Step 2: Check the event log for the root dataset that first failed — downstream datasets inherit the failure.
3Step 3: Fix the underlying code or data issue, then click 'Start' to trigger a full or triggered update.
4Step 4: If memory-related, increase the cluster worker count or move to a larger instance type under Pipeline Settings.
5Step 5: Add expectation monitoring to surface data quality issues before they cause terminal failures.

Frequently asked questions

Will DLT retry automatically after a terminal failure?

No. Terminal failures require a manual restart from the Databricks pipeline UI or API. Continuous pipelines stop; triggered pipelines remain in a failed state.

How do I find which dataset caused the pipeline failure?

In the DLT pipeline event log, filter for 'FAILED' events. The first dataset to fail is the root cause; all others fail because their upstream dependency failed.