apache_beam.io.external.generate_sequence module

class apache_beam.io.external.generate_sequence.GenerateSequence(start, stop=None, elements_per_period=None, max_read_time=None, expansion_service=None)

Bases: apache_beam.transforms.external.ExternalTransform

An external PTransform which provides a bounded or unbounded stream of integers.

Note: To use this transform, you need to start the Java expansion service. Please refer to the portability documentation on how to do that. The expansion service address has to be provided when instantiating this transform. During pipeline translation this transform will be replaced by the Java SDK’s GenerateSequence.

If you start Flink’s job server, the expansion service will be started on port 8097. This is also the configured default for this transform. For a different address, please set the expansion_service parameter.

For more information see: - https://beam.apache.org/documentation/runners/flink/ - https://beam.apache.org/roadmap/portability/

Note: Runners need to support translating Read operations in order to use this source. At the moment only the Flink Runner supports this.

Experimental; no backwards compatibility guarantees.

URN = 'beam:external:java:generate_sequence:v1'

annotations() → Dict[str, Union[bytes, str, google.protobuf.message.Message]]

default_label()

default_type_hints()

display_data()

Returns the display data associated to a pipeline component.

It should be reimplemented in pipeline components that wish to have static display data.

Returns:A dictionary containing key:value pairs. The value might be an integer, float or string value; a DisplayDataItem for values that have more data (e.g. short value, label, url); or a HasDisplayData instance that has more display data that should be picked up. For example:

{
  'key1': 'string_value',
  'key2': 1234,
  'key3': 3.14159265,
  'key4': DisplayDataItem('apache.org', url='http://apache.org'),
  'key5': subComponent
}

Return type:Dict[str, Any]

expand(pvalueish)

classmethod from_runner_api(proto, context)

classmethod get_local_namespace()

get_type_hints()

Gets and/or initializes type hints for this object.

If type hints have not been set, attempts to initialize type hints in this order: - Using self.default_type_hints(). - Using self.__class__ type hints.

get_windowing(inputs)

Returns the window function to be associated with transform’s output.

By default most transforms just return the windowing function associated with the input PCollection (or the first input if several).

infer_output_type(unused_input_type)

label

classmethod outer_namespace(namespace)

pipeline = None

classmethod register_urn(urn, parameter_type, constructor=None)

runner_api_requires_keyed_input()

side_inputs = ()

to_runner_api(context, has_parts=False, **extra_kwargs)

to_runner_api_parameter(unused_context)

to_runner_api_pickled(unused_context)

to_runner_api_transform(context, full_label)

type_check_inputs(pvalueish)

type_check_inputs_or_outputs(pvalueish, input_or_output)

type_check_outputs(pvalueish)

with_input_types(input_type_hint)

Annotates the input type of a PTransform with a type-hint.

Parameters:input_type_hint (type) – An instance of an allowed built-in type, a custom class, or an instance of a TypeConstraint. Raises:TypeError – If input_type_hint is not a valid type-hint. See apache_beam.typehints.typehints.validate_composite_type_param() for further details. Returns:A reference to the instance of this particular PTransform object. This allows chaining type-hinting related methods. Return type:PTransform

with_output_types(type_hint)

Annotates the output type of a PTransform with a type-hint.

Parameters:type_hint (type) – An instance of an allowed built-in type, a custom class, or a TypeConstraint. Raises:TypeError – If type_hint is not a valid type-hint. See validate_composite_type_param() for further details. Returns:A reference to the instance of this particular PTransform object. This allows chaining type-hinting related methods. Return type:PTransform