Fennel dataset pipeline failed error "extractor returned schema incompatible with dataset"

TL;DR

Change the extractor to emit exactly the columns and types the dataset declares, or version the dataset schema to the new extractor output, because the pipeline rejects an extractor whose returned schema differs from the dataset schema it feeds. Start with the Fennel dataset schema and the extractor output columns side by side, work on one affected call, record, or run first, and prove the fix there before running the full set. Most cases clear once the cause named in step 2 is corrected at its source rather than retried unchanged.

Fennel dataset pipeline failed error "extractor returned schema incompatible with dataset"

Use this when

• You see this exact message or symptom: Fennel dataset pipeline failed error "extractor returned schema incompatible with dataset"
• One run, record, call, or object is affected and you can name it
• A retry without changing anything reproduces the same result

Not for this skill when

• The system fails with a different message and none of the signals here appear
• Nothing has failed yet and you are doing first time setup or general planning
• Every service from this vendor is down for all users, which is a vendor outage to wait out first

Steps

1. Reproduce the failure once using the Fennel dataset schema and the extractor output columns side by side, and record the time, the workspace or account, and the one item it names. Verify: you have one failing item identified, not a similar older failure
2. Inspect extractor output column names and types from a local run, the dataset declared schema, and the first column where they diverge. Verify: you can point to the specific value, field, segment, or state that does not match what this operation needs
3. Apply the fix at that source: Change the extractor to emit exactly the columns and types the dataset declares, or version the dataset schema to the new extractor output, because the pipeline rejects an extractor whose returned schema differs from the dataset schema it feeds. Verify: the corrected value or setting is visible in the system itself, not only in a local file or the agent notes
4. Re-run the original operation on the single affected item first. Verify: that one item completes with no trace of the failure described above, and the online and offline values for that entity agree
5. Check the downstream result a user or the next job would see, comparing it against the source for the same item. Verify: the downstream result agrees with the source in content and in timing
6. Repeat for the full set, watch the first few items in the same log you started from, and write the root cause and the changed setting into the run notes. Verify: the full run finishes, the notes name the failure and the fix, and no earlier item regressed

Variant phrasings

Fennel dataset pipeline failed error "extractor returned schema incompatible with dataset"

The subject-first phrasing of the same failure. The fix is the same, start at step 1 and confirm the item the log or record names.

Tool-first phrasing of this failure

The phrasing searchers use once they know which system raised it. It is the same underlying problem, not a separate bug.

Why does this keep happening after a retry

The repeat-occurrence phrasing. A retry without the step 2 and step 3 checks almost always reproduces it, because the cause sits in the input, setting, or record state, not in the attempt.

Compatibility: Fennel datasets and extractors, pipeline validation.

Why it happens

Extractors drift as source fields are renamed or retyped. Fennel checks the contract at pipeline run time, so the failure names the dataset even though the change happened in the extractor.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_r0b2WQxm2zZQGU7gRAR8xQ