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Satisfies Expression Troubleshooting

Common problems when creating and running a Satisfies Expression check, their causes, and how to resolve them.

Validation Fails When Creating the Check

Clicking Validate returns an error instead of a success message.

Cause: The rule could not run against the selected data. The most common reasons are an invalid Expression, an invalid Filter Clause, or a container that failed to load.

Resolution:

  1. Review the error message: it explains what needs attention.
  2. Check the Filter Clause for typos: it must be a valid SQL WHERE expression for the selected container.
  3. If the message says the container is marked as Unloadable, the container was skipped after repeated operation failures. Follow the steps in Unloadable Container Error.

Rows With an Empty Column Are All Reported

The check fires on every record where a referenced column is empty.

Cause: A SQL comparison involving an empty value returns nothing rather than false, and a row passes only when the expression is definitely true. Rows where it returns nothing are reported.

Resolution: State the intent explicitly: col IS NULL OR <condition> to let empty values pass, or col IS NOT NULL AND <condition> to keep reporting them on purpose.

A CASE Statement Reports Rows That Match No Branch

Records that none of the WHEN clauses cover are flagged.

Cause: Without an ELSE, a CASE returns nothing for those rows, and a row that does not evaluate to true fails.

Resolution: Add an explicit ELSE TRUE (or ELSE FALSE) so every row gets a definite verdict.

Validation Fails on the Expression

Clicking Validate returns an error instead of a success message.

Cause: The expression is not valid Spark SQL for this container: a misspelled column, an unbalanced parenthesis, a function the source does not provide, or an expression that returns a value instead of a condition.

Resolution: Read the error message, then check the column names against the container and confirm the expression evaluates to true or false rather than to a value.

The Check Is Slow

The scan takes noticeably longer than other checks on the same container.

Cause: The expression runs once per row. A subquery inside it runs in that context too, which is far more expensive than a plain comparison.

Resolution: Add a Filter Clause so fewer rows reach the expression, simplify the condition, or move the heavy part into a Computed Field and check that instead.

The Anomaly Highlights Several Cells

The Source Records view marks more than one column on the violating record.

Cause: The check's field list is derived from the expression, so every column the expression names is highlighted, not only the value that made the row fail.

Resolution: Read the expression quoted in the message against the highlighted values. Keeping expressions short makes this quick.

An Edited Check Keeps Behaving the Old Way

You changed the configuration but the anomaly list did not change.

Cause: Edits take effect on the next Scan. Saving the check does not re-evaluate the data, and anomalies raised under the previous configuration are not modified.

Resolution: Run a Scan on the container (or wait for the scheduled one). Old anomalies stay open until you triage them or a Full scan with Auto Resolve clears them. See What Happens to Existing Anomalies.

No Anomalies Although the Data Looks Wrong

A Scan ran, the data clearly breaks the rule, but nothing was reported.

Cause: One of these configurations is excluding the violations:

  • The check is in Draft status: Draft checks are not evaluated by Scans.
  • The Filter Clause excludes those rows before the evaluation runs.
  • Coverage is below 100% and the failing fraction stayed within the tolerance, so the check passed.

Resolution: Confirm the check is Active and test the filter expression against the offending rows. Then review the coverage setting; see Coverage and Tolerance.

Expected One Anomaly per Row, Got a Single Rolled-Up One

Many rows failed, but the scan reported one Shape Anomaly instead of per-row Record Anomalies.

Cause: When the number of failing rows exceeds the scan's rollup threshold, the per-row findings are grouped into one rolled-up Shape Anomaly.

Resolution: This is expected behavior; the rolled-up anomaly carries sampled source records. To change the threshold, see Maximum Record Anomalies per Check.