apache_beam.io.flink.flink_streaming_impulse_source module

A PTransform that provides an unbounded, streaming source of empty byte arrays.

This can only be used with the flink runner.

class apache_beam.io.flink.flink_streaming_impulse_source.FlinkStreamingImpulseSource(label=None)

Bases: apache_beam.transforms.ptransform.PTransform

URN = 'flink:transform:streaming_impulse:v1'

config = {}

expand(pbegin)

get_windowing(inputs)

infer_output_type(unused_input_type)

to_runner_api_parameter(context)

set_interval_ms(interval_ms)

Sets the interval (in milliseconds) between messages in the stream.

set_message_count(message_count)

If non-zero, the stream will produce only this many total messages. Otherwise produces an unbounded number of messages.

static from_runner_api_parameter(_ptransform, spec_parameter, _context)

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]

classmethod from_runner_api(proto, context)

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.

label

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_pickled(unused_context)

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