等待时间后取消功能会引发错误，它似乎是无害的。
为了证明这一点，我设法使用 python 3.5 从我的虚拟机中重现了您的确切问题。该模板是在给定路径中创建的--template_location，可用于运行作业。请注意，我需要对您的代码进行一些更改才能使其在 Dataflow 中实际工作。
如果它对你有用，我最终使用了这个管道代码
from apache_beam.options.pipeline_options import PipelineOptions
from google.cloud import pubsub_v1
from google.cloud import bigquery
import apache_beam as beam
import logging
import argparse
import datetime
# Fill this values in order to have them by default
# Note that the table in BQ needs to have the column names message_body and publish_time
Table = 'projectid:datasetid.tableid'
schema = 'ex1:STRING, ex2:TIMESTAMP'
TOPIC = "projects/<projectid>/topics/<topicname>"
class AddTimestamps(beam.DoFn):
def process(self, element, publish_time=beam.DoFn.TimestampParam):
"""Processes each incoming element by extracting the Pub/Sub
message and its publish timestamp into a dictionary. `publish_time`
defaults to the publish timestamp returned by the Pub/Sub server. It
is bound to each element by Beam at runtime.
"""
yield {
"message_body": element.decode("utf-8"),
"publish_time": datetime.datetime.utcfromtimestamp(
float(publish_time)
).strftime("%Y-%m-%d %H:%M:%S.%f"),
}
def main(argv=None):
parser = argparse.ArgumentParser()
parser.add_argument("--input_topic", default=TOPIC)
parser.add_argument("--output_table", default=Table)
args, beam_args = parser.parse_known_args(argv)
# save_main_session needs to be set to true due to modules being used among the code (mostly datetime)
# Uncomment the service account email to specify a custom service account
p = beam.Pipeline(argv=beam_args,options=PipelineOptions(save_main_session=True,
region='us-central1'))#, service_account_email='email'))
(p
| 'ReadData' >> beam.io.ReadFromPubSub(topic=args.input_topic).with_output_types(bytes)
| "Add timestamps to messages" >> beam.ParDo(AddTimestamps())
| 'WriteToBigQuery' >> beam.io.WriteToBigQuery(args.output_table, schema=schema, write_disposition=beam.io.BigQueryDisposition.WRITE_APPEND)
)
result = p.run()
#Warning: Cancel does not work properly in a template
result.wait_until_finish(duration=3000)
result.cancel() # Cancel the streaming pipeline after a while to avoid consuming more resources
if __name__ == '__main__':
logger = logging.getLogger().setLevel(logging.INFO)
main()
之后我运行命令：
# Fill accordingly
PROJECT="MYPROJECT-ID"
BUCKET="MYBUCKET"
TEMPLATE_NAME="TRIAL"
# create the template
python3 -m templates.template-pubsub-bigquery \
--runner DataflowRunner \
--project $PROJECT \
--staging_location gs://$BUCKET/staging \
--temp_location gs://$BUCKET/temp \
--template_location gs://$BUCKET/templates/$TEMPLATE_NAME \
--streaming
创建管道（这会产生您提到的错误但仍会创建模板）。和
# Fill job-name and gcs location accordingly
# Uncomment and fill the parameters should you want to use your own
gcloud dataflow jobs run <job-name> \
--gcs-location "gs://<MYBUCKET>/dataflow/templates/mytemplate"
# --parameters input_topic="", output_table=""
运行管道。
正如我所说，模板已正确创建并且管道正常工作。
编辑
实际上，取消功能在模板中无法正常工作。它似乎是一个问题，它需要模板创建时的作业 ID，它当然不存在，因此它省略了该功能。
我发现this other post处理提取管道上的作业ID。我尝试了一些调整以使其在模板代码本身中工作，但我认为没有必要。鉴于您想安排他们的执行，我会选择更简单的选项并在特定时间（例如 9:01 GMT）执行流式管道模板并使用脚本取消管道
import logging, re,os
from googleapiclient.discovery import build
from oauth2client.client import GoogleCredentials
def retrieve_job_id():
#Fill as needed
project = '<project-id>'
job_prefix = "<job-name>"
location = '<location>'
logging.info("Looking for jobs with prefix {} in region {}...".format(job_prefix, location))
try:
credentials = GoogleCredentials.get_application_default()
dataflow = build('dataflow', 'v1b3', credentials=credentials)
result = dataflow.projects().locations().jobs().list(
projectId=project,
location=location,
).execute()
job_id = "none"
for job in result['jobs']:
if re.findall(r'' + re.escape(job_prefix) + '', job['name']):
job_id = job['id']
break
logging.info("Job ID: {}".format(job_id))
return job_id
except Exception as e:
logging.info("Error retrieving Job ID")
raise KeyError(e)
os.system('gcloud dataflow jobs cancel {}'.format(retrieve_job_id()))
在另一个时间（例如格林威治标准时间 9:05）。此脚本假定您每次都使用相同的作业名称运行脚本，并采用名称的最新外观并取消它。我试了几次，效果很好。