apache/beam · error · ValueError

Invalid model update

Error message

Invalid model update: {key} appears in the original configuration, but not the update.

What it means

Raised by update_model_paths when a key present in the handler's original configuration is missing from the update. Every originally configured key must receive exactly one updated path, so the update must be complete.

Solutions

1. Provide an update entry for every key in the original configuration.
2. Enumerate the handler's configured keys and assert the update covers all of them before calling.
3. If only some models changed, still supply their existing paths as the updated paths for unchanged keys.

Example fix

// before
handler.update_model_paths([UpdateModelPath(keys=['k1'], update_path='gs://b/m2', model_id='m2')])  # k2 missing
// after
handler.update_model_paths([
    UpdateModelPath(keys=['k1'], update_path='gs://b/m2', model_id='m2'),
    UpdateModelPath(keys=['k2'], update_path='gs://b/m1', model_id='m1')])

missing = set(handler._key_to_id_map) - {k for u in updates for k in u.keys}
if missing:
    raise ValueError(f'keys missing from update: {missing}')

When it happens

Trigger: Calling update_model_paths with updates covering only a subset of the keys used at handler construction (e.g. updating k1 but omitting k2 which was in the original config).

Common situations: Assuming updates are partial/partially-applicable; generating the update list from a filtered config; a cohort's update entry was dropped by an earlier validation or merge step.

Understand the failure class

Background: "missing required argument" and "the following required arguments were not provided": what required-argument errors mean and how to fix them — this error's family across 20 libraries.

Related errors

• Cannot make make an unkeyed model handler with pre or…
• Cannot override RemoteModelHandler.load_model, implement…
• Cannot override RemoteModelHandler.run_inference, implement…
• Cannot use an unkeyed model handler with pre or…
• Empty list maps to model handler

AI-assisted analysis of apache/beam@12126d8942 (2026-09-13). Data as JSON: /api/errors/7528ea3b1a057489. Report an issue: GitHub.

Appendix: source

Thrown at sdks/python/apache_beam/ml/inference/base.py:994

      for key in keys:
        if key in seen_keys:
          raise ValueError(
              f'Invalid model update: {key} appears in multiple '
              'update lists. A single model update must provide exactly one '
              'updated path per key.')
        seen_keys.add(key)
        if key not in self._key_to_id_map:
          raise ValueError(
              f'Invalid model update: {key} appears in '
              'update, but not in the original configuration.')
        key_modelid_mapping[key] = model_id
        cohort_id = self._key_to_id_map[key]
        if cohort_id not in cohort_path_mapping:
          cohort_path_mapping[cohort_id] = defaultdict(list)
        cohort_path_mapping[cohort_id][update_path].append(key)
    for key in self._key_to_id_map:
      if key not in seen_keys:
        raise ValueError(
            f'Invalid model update: {key} appears in the '
            'original configuration, but not the update.')

    # We now have our new set of cohorts. For each one, update our local model
    # handler configuration and send the results to the ModelManager
    for old_cohort_id, path_key_mapping in cohort_path_mapping.items():
      for updated_path, keys in path_key_mapping.items():
        cohort_id = old_cohort_id
        if old_cohort_id not in keys:
          # Create new cohort
          cohort_id = keys[0]
          for key in keys:
            self._key_to_id_map[key] = cohort_id
          mh = self._id_to_mh_map[old_cohort_id]
          self._id_to_mh_map[cohort_id] = deepcopy(mh)
        self._id_to_mh_map[cohort_id].update_model_path(updated_path)
        model.update_model_handler(cohort_id, updated_path, old_cohort_id)
        model_id = key_modelid_mapping[cohort_id]

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