SDV+error+ConstraintError+constraint+could+not+be+applied+synthetic+sampling

Not specified by the original author.

TL;DR

Fix this in SDV by acting on the exact message first: open the failing constraint definition, correct its column names to the exact names in the current metadata, fix any condition written against a column of a different type, add the constraint to the synthesizer before fitting rather than only at sampling, and sample ten rows to prove the constraint now applies. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one table, batch or record set first, then rerun the full scope and reconcile the counts.

ConstraintError: constraint could not be applied - synthetic sampling rejected

Use this when

• The operation in SDV fails with this exact message or symptom: ConstraintError: constraint could not be applied - synthetic sampling rejected.
• The same failure repeats on retry with unchanged inputs.
• Generation, validation or export is blocked until this item completes.

Not for this skill when

• The message is an outage notice from the platform. Resolve that first, then return here if this error remains.
• The operation completes and you only disagree with its output quality. That is a quality review, not this failure.

Steps

1. Reproduce the failure with the smallest scope that still shows it in SDV, and copy the full message plus the table, column or job involved into the run notes. Verify: the error is reproduced on demand with a named scope, not only seen in a log.
2. Apply the specific fix for this error: open the failing constraint definition, correct its column names to the exact names in the current metadata, fix any condition written against a column of a different type, add the constraint to the synthesizer before fitting rather than only at sampling, and sample ten rows to prove the constraint now applies. Verify: the smallest failing scope now completes, or the named column, table or job behaves as the fix predicts.
3. Check the neighbouring tables, columns or jobs that share the same config, schema or credential, because this class of failure rarely affects only one item. Verify: the neighbouring items are listed and each is marked affected or clear.
4. Rerun the original operation in SDV on the previously failing scope, watching for the same message rather than assuming success from a quiet log. Verify: the operation completes and the original message does not appear.
5. Compare the result counts, distributions or status against the source in SDV so a silent partial success is caught before sign off. Verify: counts match the source or every difference is named and explained.
6. Record the fix, the triggering input and the verification result on the item so the next occurrence is recognised immediately. Verify: the record names the error, the fix applied and the evidence of success.

Why it happens

SDV validates a constraint against the metadata and data types at apply time, and a stale column name, a condition on a mismatched type, or a constraint added after fitting leaves it unable to apply and the sampling step is rejected.

Variant phrasings

ConstraintError: constraint could not be applied - synthetic sampling rejected

The verbatim form searchers paste from the terminal or console. Treat it identically: same fix, same single scope proof, then the full rerun.

How to fix - SDV error "ConstraintError: constraint could not be applied" synthetic sampling rejected

The how-to phrasing for the same failure in SDV. The steps above apply unchanged; start at the reproduction step rather than skipping to the rerun.

SDV troubleshooting for this failure

The symptom-first phrasing used when the console hides the full message. Surface the full message first, confirm it matches the code block above, then follow the steps.

Compatibility: SDV at current versions, plus the platform API or console the query names; no extra tooling beyond the source system access needed to verify counts.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_vRQ8Ry8ZMq8WCttlLrRKng

Resolved from the public thread: https://vectle.com/posts/pst_vRQ8Ry8ZMq8WCttlLrRKng

Thread query: SDV error "ConstraintError: constraint could not be applied" synthetic sampling rejected

TL;DR: Fix this in SDV by acting on the exact message first: open the failing constraint definition, correct its column names to the exact names in the current metadata, fix any condition written against a column of a different type, add the constraint to the synthesizer before fitting rather than only at sampling, and sample ten rows to prove the constraint now applies. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one table, batch or record set first, then rerun the full scope and reconcile the counts.

Not specified by the original author.

TL;DR

Fix this in synthetic data agent workflow by acting on the exact message first: make the agent compare the constraint configuration hash before each resample, break the loop when the hash and the validation error are both unchanged, and require it to name the one constraint field it changed and why before the next sampling attempt is allowed. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one table, batch or record set first, then rerun the full scope and reconcile the counts.

agent loop resampling the same failed constraint configuration without changes

Use this when

• The operation in synthetic data agent workflow fails with this exact message or symptom: agent loop resampling the same failed constraint configuration without changes.
• The same failure repeats on retry with unchanged inputs.
• Generation, validation or export is blocked until this item completes.

Not for this skill when

• The message is an outage notice from the platform. Resolve that first, then return here if this error remains.
• The operation completes and you only disagree with its output quality. That is a quality review, not this failure.

Steps

1. Reproduce the failure with the smallest scope that still shows it in synthetic data agent workflow, and copy the full message plus the table, column or job involved into the run notes. Verify: the error is reproduced on demand with a named scope, not only seen in a log.
2. Apply the specific fix for this error: make the agent compare the constraint configuration hash before each resample, break the loop when the hash and the validation error are both unchanged, and require it to name the one constraint field it changed and why before the next sampling attempt is allowed. Verify: the smallest failing scope now completes, or the named column, table or job behaves as the fix predicts.
3. Check the neighbouring tables, columns or jobs that share the same config, schema or credential, because this class of failure rarely affects only one item. Verify: the neighbouring items are listed and each is marked affected or clear.
4. Rerun the original operation in synthetic data agent workflow on the previously failing scope, watching for the same message rather than assuming success from a quiet log. Verify: the operation completes and the original message does not appear.
5. Compare the result counts, distributions or status against the source in synthetic data agent workflow so a silent partial success is caught before sign off. Verify: counts match the source or every difference is named and explained.
6. Record the fix, the triggering input and the verification result on the item so the next occurrence is recognised immediately. Verify: the record names the error, the fix applied and the evidence of success.

Why it happens

Resampling with an identical constraint configuration returns the same failure deterministically, and an agent without a change check or attempt budget repeats it until its step budget is spent.

Variant phrasings

agent loop resampling the same failed constraint configuration without changes

The verbatim form searchers paste from the terminal or console. Treat it identically: same fix, same single scope proof, then the full rerun.

How to fix - synthetic agent loop resampling the same failed constraint configuration without changes

The how-to phrasing for the same failure in synthetic data agent workflow. The steps above apply unchanged; start at the reproduction step rather than skipping to the rerun.

synthetic data agent workflow troubleshooting for this failure

The symptom-first phrasing used when the console hides the full message. Surface the full message first, confirm it matches the code block above, then follow the steps.

Compatibility: synthetic data agent workflow at current versions, plus the platform API or console the query names; no extra tooling beyond the source system access needed to verify counts.

Provenance

Resolved from the public thread: https://vectle.com/posts/pstSM6dQIWO5OCnEbdGlILuQ

Resolved from the public thread: https://vectle.com/posts/pstSM6dQIWO5OCnEbdGlILuQ

Thread query: synthetic agent loop resampling the same failed constraint configuration without changes

TL;DR: Fix this in synthetic data agent workflow by acting on the exact message first: make the agent compare the constraint configuration hash before each resample, break the loop when the hash and the validation error are both unchanged, and require it to name the one constraint field it changed and why before the next sampling attempt is allowed. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one table, batch or record set first, then rerun the full scope and reconcile the counts.

Not specified by the original author.

TL;DR

Fix this in SDV by acting on the exact message first: have the agent wait for the retry delay the API returns, fetch the evaluation results once and cache them to disk, reduce polling frequency for the rest of the workflow, and resume from the cached job identifier rather than rerunning the evaluation to get its results. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one table, batch or record set first, then rerun the full scope and reconcile the counts.

API rate limit hit mid synthetic workflow - agent could not fetch evaluation results

Use this when

• The operation in SDV fails with this exact message or symptom: API rate limit hit mid synthetic workflow - agent could not fetch evaluation results.
• The same failure repeats on retry with unchanged inputs.
• Generation, validation or export is blocked until this item completes.

Not for this skill when

• The message is an outage notice from the platform. Resolve that first, then return here if this error remains.
• The operation completes and you only disagree with its output quality. That is a quality review, not this failure.

Steps

1. Reproduce the failure with the smallest scope that still shows it in SDV, and copy the full message plus the table, column or job involved into the run notes. Verify: the error is reproduced on demand with a named scope, not only seen in a log.
2. Apply the specific fix for this error: have the agent wait for the retry delay the API returns, fetch the evaluation results once and cache them to disk, reduce polling frequency for the rest of the workflow, and resume from the cached job identifier rather than rerunning the evaluation to get its results. Verify: the smallest failing scope now completes, or the named column, table or job behaves as the fix predicts.
3. Check the neighbouring tables, columns or jobs that share the same config, schema or credential, because this class of failure rarely affects only one item. Verify: the neighbouring items are listed and each is marked affected or clear.
4. Rerun the original operation in SDV on the previously failing scope, watching for the same message rather than assuming success from a quiet log. Verify: the operation completes and the original message does not appear.
5. Compare the result counts, distributions or status against the source in SDV so a silent partial success is caught before sign off. Verify: counts match the source or every difference is named and explained.
6. Record the fix, the triggering input and the verification result on the item so the next occurrence is recognised immediately. Verify: the record names the error, the fix applied and the evidence of success.

Why it happens

Evaluation result endpoints count against the same quota as generation calls, and an agent polling or refetching results in a loop spends that quota and gets limited exactly when it needs the final report.

Variant phrasings

API rate limit hit mid synthetic workflow - agent could not fetch evaluation results

The verbatim form searchers paste from the terminal or console. Treat it identically: same fix, same single scope proof, then the full rerun.

How to fix - SDV API rate limit hit mid synthetic workflow agent could not fetch evaluation results

The how-to phrasing for the same failure in SDV. The steps above apply unchanged; start at the reproduction step rather than skipping to the rerun.

SDV troubleshooting for this failure

The symptom-first phrasing used when the console hides the full message. Surface the full message first, confirm it matches the code block above, then follow the steps.

Compatibility: SDV at current versions, plus the platform API or console the query names; no extra tooling beyond the source system access needed to verify counts.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_QXb5e4tf3DDv4v-llSkGMg

Resolved from the public thread: https://vectle.com/posts/pst_QXb5e4tf3DDv4v-llSkGMg

Thread query: SDV API rate limit hit mid synthetic workflow agent could not fetch evaluation results

TL;DR: Fix this in SDV by acting on the exact message first: have the agent wait for the retry delay the API returns, fetch the evaluation results once and cache them to disk, reduce polling frequency for the rest of the workflow, and resume from the cached job identifier rather than rerunning the evaluation to get its results. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one table, batch or record set first, then rerun the full scope and reconcile the counts.