Is it possible to have a non parallel step in an Apache Beam / Dataflow job?

Question

Suppose I have a python dataflow job in GCP that does the following 2 things:

• Fetches some data from BigQuery

• Calls an external API in order to get a certain value and filters the data from BigQuery based on the fetched value

I am able to do this, however for the second step the only way I figured out how to implement it was to have it as a class that extends DoFn and call it in a parallel way later:

class CallExternalServiceAndFilter(beam.DoFn):
    def to_runner_api_parameter(self, unused_context):
        pass

    def process(self, element, **kwargs):
        # here I have to make the http call and figure out whether to yield the element or not,
        # however this happens for each element of the set, as expected.
        if element['property'] < response_body_parsed['some_other_property']:
            logging.info("Yielding element")
            yield element
        else:
            logging.info("Not yielding element")

with beam.Pipeline(options=PipelineOptions(), argv=argv) as p:
    rows = p | 'Read data' >> beam.io.Read(beam.io.BigQuerySource(
        dataset='test',
        project=PROJECT,
        query='Select * from test.table'
    ))

    rows = rows | 'Calling external service and filtering items' >> beam.ParDo(CallExternalServiceAndFilter())

    # ...

Is there any way that I can make the API call only once and then use the result in the parallel filtering step?

Answer 1

Use the __init__ function.

class CallExternalServiceAndFilter(beam.DoFn):
    def __init__():
        self.response_body_parsed = call_api()

    def to_runner_api_parameter(self, unused_context):
        pass

    def process(self, element, **kwargs):
        # here I have to make the http call and figure out whether to yield the element or not,
        # however this happens for each element of the set, as expected.
        if element['property'] < self.response_body_parsed['some_other_property']:
            logging.info("Yielding element")
            yield element
        else:
            logging.info("Not yielding element")

Or better yet, just call your API beforehand (on your local machine that builds the pipeline), and assign the values in __init__ .

reponse_body_parsed = call_api()

class CallExternalServiceAndFilter(beam.DoFn):
    def __init__():
        self.response_body_parsed = reponse_body_parsed

    def to_runner_api_parameter(self, unused_context):
        pass

    def process(self, element, **kwargs):
        # here I have to make the http call and figure out whether to yield the element or not,
        # however this happens for each element of the set, as expected.
        if element['property'] < self.response_body_parsed['some_other_property']:
            logging.info("Yielding element")
            yield element
        else:
            logging.info("Not yielding element")

You said that using setup still does multiple calls. Is this still the case with __init__ (if you do the API call in the DoFn, and not beforehand)? The difference between __init__ and setup is still unclear to me.