Databricks Certified Data Engineer - Associate

Ultimate access to all questions.

Explanation:

Explanation

In Delta Live Tables (DLT), when you define a constraint with ON VIOLATION DROP ROW, the behavior is:

Records that violate the constraint are dropped from the target dataset - they are not included in the final output table.
The violation is recorded in the event log - DLT tracks these violations for monitoring and debugging purposes.
No quarantine table is automatically created - Option A is incorrect because DLT doesn't automatically load dropped rows into a quarantine table unless explicitly configured to do so.
Records are not added with flags - Option B is incorrect because the DROP ROW action specifically removes the rows, rather than adding them with flags.

Key Points:

ON VIOLATION DROP ROW means violating rows are excluded from the target dataset
Violations are logged in the DLT event log for observability
This is different from ON VIOLATION FAIL UPDATE which would fail the pipeline, or custom handling that might route to quarantine tables
The event log provides visibility into data quality issues without storing the bad data in the main dataset

Explanation:

In Delta Live Tables (DLT), when you define a constraint with ON VIOLATION DROP ROW, the behavior is:

Records that violate the constraint are dropped from the target dataset - they are not included in the final output table.
The violation is recorded in the event log - DLT tracks these violations for monitoring and debugging purposes.
No quarantine table is automatically created - Option A is incorrect because DLT doesn't automatically load dropped rows into a quarantine table unless explicitly configured to do so.
Records are not added with flags - Option B is incorrect because the DROP ROW action specifically removes the rows, rather than adding them with flags.

Key Points:

ON VIOLATION DROP ROW means violating rows are excluded from the target dataset
Violations are logged in the DLT event log for observability
This is different from ON VIOLATION FAIL UPDATE which would fail the pipeline, or custom handling that might route to quarantine tables
The event log provides visibility into data quality issues without storing the bad data in the main dataset

No comments yet.

A dataset has been defined using Delta Live Tables and includes an expectations clause:

CONSTRAINT valid_timestamp EXPECT (timestamp > '2020-01-01') ON VIOLATION DROP ROW

CONSTRAINT valid_timestamp EXPECT (timestamp > '2020-01-01') ON VIOLATION DROP ROW

What is the expected behavior when a batch of data containing data that violates these constraints is processed?

Real Exam

Community

KKeng

Last updated: January 13, 2026 at 09:03

Records that violate the expectation are dropped from the target dataset and loaded into a quarantine table.

0.0%

Records that violate the expectation are added to the target dataset and flagged as invalid in a field added to the target dataset.

0.0%

Records that violate the expectation are dropped from the target dataset and recorded as invalid in the event log.

100.0%