apache/beam · error · ValueError

Only const and zipf distributions are supported for…

Error message

Only const and zipf distributions are supported for determining sizes of bundles produced by initial splitting. Received: %s

What it means

SyntheticSource.__init__ supports only 'const' and 'zipf' distributions for the bundle sizes produced by initial splitting; anything else raises ValueError. It reads input_spec['bundleSizeDistribution']['type'] (defaulting to 'const' when absent).

Solutions

Set bundleSizeDistribution.type to 'const' or 'zipf'
Remove the bundleSizeDistribution key entirely to get the default 'const' behavior
Fix casing/typos — values must match exactly

Example fix

// before
"bundleSizeDistribution": {"type": "uniform", "seed": 7}
// after
"bundleSizeDistribution": {"type": "zipf", "seed": 7}

Defensive patterns

Strategy: validation

Validate before calling

t = input_spec.get('bundleSizeDistribution', {}).get('type', 'const')
if t not in ('const', 'zipf'):
    raise ValueError(f'unsupported bundleSizeDistribution type: {t}')

Type guard

def is_supported_splitting(t):
    return t in ('const', 'zipf')

Try / catch

try:
    source = SyntheticSource(spec)
except ValueError as e:
    _LOGGER.error('%s; falling back to const splitting', e)
    spec.pop('bundleSizeDistribution', None)
    source = SyntheticSource(spec)

Prevention

Only emit const/zipf in spec generators
Normalize type strings (lowercase/strip) at load time
Validate the parse-spec JSON against a schema before running

When it happens

Trigger: Passing a pipeline parse spec where bundleSizeDistribution.type is 'uniform', 'normal', or any other unsupported name.

Common situations: Reusing a spec JSON written for another synthetic generator with more distribution options; typo ('Zipf', 'constant'); experimenting with distributions not implemented in this module.

Understand the failure class

Background: Invalid enum value errors: "Unknown type", "Invalid scope", "must be one of" — when a string is not on the library's allowed list — this error's family across 23 libraries.

Related errors

AI-assisted analysis of apache/beam@12126d8942 (2026-09-13). Data as JSON: /api/errors/60192ed252d47025. Report an issue: GitHub.

Appendix: source

Thrown at sdks/python/apache_beam/testing/synthetic_pipeline.py:361

    Raises:
      ValueError: if input parameters are invalid.
    """
    def maybe_parse_byte_size(s):
      return parse_byte_size(s) if isinstance(s, str) else int(s)

    self._num_records = input_spec['numRecords']
    self._key_size = maybe_parse_byte_size(input_spec.get('keySizeBytes', 1))
    self._hot_key_fraction = input_spec.get('hotKeyFraction', 0)
    self._num_hot_keys = input_spec.get('numHotKeys', 0)

    self._value_size = maybe_parse_byte_size(
        input_spec.get('valueSizeBytes', 1))
    self._total_size = self.element_size * self._num_records
    self._initial_splitting = (
        input_spec['bundleSizeDistribution']['type']
        if 'bundleSizeDistribution' in input_spec else 'const')
    if self._initial_splitting != 'const' and self._initial_splitting != 'zipf':
      raise ValueError(
          'Only const and zipf distributions are supported for determining '
          'sizes of bundles produced by initial splitting. Received: %s',
          self._initial_splitting)
    self._initial_splitting_num_bundles = (
        input_spec['forceNumInitialBundles']
        if 'forceNumInitialBundles' in input_spec else 0)
    if self._initial_splitting == 'zipf':
      self._initial_splitting_distribution_parameter = (
          input_spec['bundleSizeDistribution']['param'])
      if self._initial_splitting_distribution_parameter < 1:
        raise ValueError(
            'Parameter for a Zipf distribution must be larger than 1. '
            'Received %r.',
            self._initial_splitting_distribution_parameter)
    else:
      self._initial_splitting_distribution_parameter = 0
    self._dynamic_splitting = (
        'none' if (

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