[
https://issues.apache.org/jira/browse/BEAM-8372?focusedWorklogId=327106&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-327106
]
ASF GitHub Bot logged work on BEAM-8372:
----------------------------------------
Author: ASF GitHub Bot
Created on: 11/Oct/19 22:44
Start Date: 11/Oct/19 22:44
Worklog Time Spent: 10m
Work Description: ibzib commented on pull request #9775: [BEAM-8372] Job
server submitting UberJars directly to Flink Runner.
URL: https://github.com/apache/beam/pull/9775#discussion_r334164163
##########
File path:
sdks/python/apache_beam/runners/portability/flink_uber_jar_job_server.py
##########
@@ -0,0 +1,233 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements. See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+"""A job server submitting portable pipelines as uber jars to Flink."""
+
+from __future__ import absolute_import
+from __future__ import print_function
+
+import logging
+import os
+import shutil
+import tempfile
+import time
+import zipfile
+
+from google.protobuf import json_format
+import grpc
+import requests
+from concurrent import futures
+
+from apache_beam.portability.api import beam_artifact_api_pb2_grpc
+from apache_beam.portability.api import beam_job_api_pb2
+from apache_beam.portability.api import endpoints_pb2
+from apache_beam.runners.portability import abstract_job_service
+from apache_beam.runners.portability import artifact_service
+from apache_beam.runners.portability import job_server
+
+
+class FlinkUberJarJobServer(abstract_job_service.AbstractJobServiceServicer):
+
+ def __init__(self, master_url, executable_jar=None):
+ super(FlinkUberJarJobServer, self).__init__()
+ self._master_url = master_url
+ self._executable_jar = executable_jar
+ self._temp_dir = tempfile.mkdtemp(prefix='apache-beam-flink')
+
+ def start(self):
+ return self
+
+ def stop(self):
+ pass
+
+ def executable_jar(self):
+ return self._executable_jar or job_server.JavaJarJobServer.local_jar(
+ job_server.JavaJarJobServer.path_to_beam_jar(
+ 'runners:flink:%s:job-server:shadowJar' % self.flink_version()))
+
+ def flink_version(self):
+ full_version = requests.get(
+ '%s/v1/config' % self._master_url).json()['flink-version']
+ # Only return up to minor version.
+ return '.'.join(full_version.split('.')[:2])
+
+ def create_beam_job(self, job_id, job_name, pipeline, options):
+ return FlinkBeamJob(
+ self._master_url,
+ self.executable_jar(),
+ job_id,
+ job_name,
+ pipeline,
+ options)
+
+
+class FlinkBeamJob(abstract_job_service.AbstractBeamJob):
+
+ # These must agree with those defined in PortablePipelineJarUtils.java.
+ PIPELINE_FOLDER_PATH = "BEAM-PIPELINE"
+ PIPELINE_PATH = PIPELINE_FOLDER_PATH + "/pipeline.json"
+ PIPELINE_OPTIONS_PATH = PIPELINE_FOLDER_PATH + "/pipeline-options.json"
+ ARTIFACT_STAGING_FOLDER_PATH = "BEAM-ARTIFACT-STAGING"
+ ARTIFACT_MANIFEST_PATH = (
+ ARTIFACT_STAGING_FOLDER_PATH + "/artifact-manifest.json")
+
+ def __init__(
+ self, master_url, executable_jar, job_id, job_name, pipeline, options):
+ super(FlinkBeamJob, self).__init__(job_id, job_name, pipeline, options)
+ self._master_url = master_url
+ self._executable_jar = executable_jar
+ self._jar_uploaded = False
+
+ def prepare(self):
+ # Copy the executable jar, injecting the pipeline and options as resources.
+ with tempfile.NamedTemporaryFile(suffix='.jar') as tout:
+ self._jar = tout.name
+ shutil.copy(self._executable_jar, self._jar)
+ with zipfile.ZipFile(self._jar, 'a', compression=zipfile.ZIP_DEFLATED) as
z:
+ with z.open(self.PIPELINE_PATH, 'w') as fout:
+ fout.write(json_format.MessageToJson(
+ self._pipeline_proto).encode('utf-8'))
+ with z.open(self.PIPELINE_OPTIONS_PATH, 'w') as fout:
+ fout.write(json_format.MessageToJson(
+ self._pipeline_options).encode('utf-8'))
+ self._start_artifact_service(self._jar)
+
+ def _start_artifact_service(self, jar):
+ self._artifact_staging_service = artifact_service.ZipFileArtifactService(
+ jar)
+ self._artifact_staging_server = grpc.server(futures.ThreadPoolExecutor())
+ port = self._artifact_staging_server.add_insecure_port('[::]:0')
+ beam_artifact_api_pb2_grpc.add_ArtifactStagingServiceServicer_to_server(
+ self._artifact_staging_service, self._artifact_staging_server)
+ self._artifact_staging_endpoint = endpoints_pb2.ApiServiceDescriptor(
+ url='localhost:%d' % port)
+ self._artifact_staging_server.start()
+ logging.info('Artifact server started on port %s', port)
+ return port
+
+ def _stop_artifact_service(self):
+ self._artifact_staging_server.stop(1)
+ self._artifact_staging_service.close()
+ self._artifact_manifest_location = (
+ self._artifact_staging_service.retrieval_token(self._job_id))
+
+ def artifact_staging_endpoint(self):
+ return self._artifact_staging_endpoint
+
+ def request(self, method, path, expected_status=200, **kwargs):
+ response = method('%s/%s' % (self._master_url, path), **kwargs)
+ if response.status_code != expected_status:
+ raise RuntimeError(response.text)
+ if response.text:
+ return response.json()
+
+ def get(self, path, **kwargs):
+ return self.request(requests.get, path, **kwargs)
+
+ def post(self, path, **kwargs):
+ return self.request(requests.post, path, **kwargs)
+
+ def delete(self, path, **kwargs):
+ return self.request(requests.delete, path, **kwargs)
+
+ def run(self):
+ self._stop_artifact_service()
+ # Move the artifact manifest to the expected location.
+ with zipfile.ZipFile(self._jar, 'a', compression=zipfile.ZIP_DEFLATED) as
z:
+ with z.open(self._artifact_manifest_location) as fin:
+ manifest_contents = fin.read()
+ with z.open(self.ARTIFACT_MANIFEST_PATH, 'w') as fout:
+ fout.write(manifest_contents)
+
+ # Upload the jar and start the job.
+ with open(self._jar, 'rb') as jar_file:
+ self._flink_jar_id = self.post(
+ 'v1/jars/upload',
+ files={'jarfile': ('beam.jar', jar_file)})['filename'].split('/')[-1]
+ self._jar_uploaded = True
+ self._flink_job_id = self.post(
+ 'v1/jars/%s/run' % self._flink_jar_id,
+ json={
+ 'entryClass': 'org.apache.beam.runners.flink.FlinkPipelineRunner'
+ })['jobid']
+ os.unlink(self._jar)
+ logging.info('Started Flink job as %s' % self._flink_job_id)
+
+ def cancel(self):
+ self.post('v1/%s/stop' % self._flink_job_id, expected_status=202)
+ self.delete_jar()
+
+ def delete_jar(self):
+ if self._jar_uploaded:
+ self._jar_uploaded = False
+ try:
+ self.delete('v1/jars/%s' % self._flink_jar_id)
+ except Exception:
+ logging.info(
+ 'Error deleting jar %s' % self._flink_jar_id, exc_info=True)
+
+ def get_state(self):
+ # For just getting the status, execution-result seems cheaper.
+ flink_status = self.get(
+ 'v1/jobs/%s/execution-result' % self._flink_job_id)['status']['id']
+ if flink_status == 'COMPLETED':
+ flink_status = self.get('v1/jobs/%s' % self._flink_job_id)['state']
+ beam_state = {
+ 'CREATED': beam_job_api_pb2.JobState.STARTING,
+ 'RUNNING': beam_job_api_pb2.JobState.RUNNING,
+ 'FAILING': beam_job_api_pb2.JobState.RUNNING,
+ 'FAILED': beam_job_api_pb2.JobState.FAILED,
+ 'CANCELLING': beam_job_api_pb2.JobState.RUNNING,
+ 'CANCELED': beam_job_api_pb2.JobState.CANCELLED,
+ 'FINISHED': beam_job_api_pb2.JobState.DONE,
+ 'RESTARTING': beam_job_api_pb2.JobState.RUNNING,
+ 'SUSPENDED': beam_job_api_pb2.JobState.RUNNING,
+ 'RECONCILING': beam_job_api_pb2.JobState.RUNNING,
+ 'IN_PROGRESS': beam_job_api_pb2.JobState.RUNNING,
+ 'COMPLETED': beam_job_api_pb2.JobState.DONE,
+ }.get(flink_status, beam_job_api_pb2.JobState.DONE)
+ if beam_state in abstract_job_service.TERMINAL_STATES:
+ self.delete_jar()
+ return beam_state
+
+ def get_state_stream(self):
+ sleep_secs = 1.0
+ current_state = self.get_state()
+ yield current_state
+ while current_state not in abstract_job_service.TERMINAL_STATES:
+ sleep_secs = min(60, sleep_secs * 1.2)
+ time.sleep(sleep_secs)
+ previous_state, current_state = current_state, self.get_state()
+ if previous_state != current_state:
+ yield current_state
+
+ def get_message_stream(self):
+ for state in self.get_state_stream():
+ if state in abstract_job_service.TERMINAL_STATES:
+ response = requests.get(
+ '%s/v1/jobs/%s/exceptions' % (self._master_url,
self._flink_job_id))
+ if response.status_code != 200:
+ print(response.content)
Review comment:
Why use `print` instead of `logging` here?
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Issue Time Tracking
-------------------
Worklog Id: (was: 327106)
> Allow submission of Flink UberJar directly to flink cluster.
> ------------------------------------------------------------
>
> Key: BEAM-8372
> URL: https://issues.apache.org/jira/browse/BEAM-8372
> Project: Beam
> Issue Type: New Feature
> Components: sdk-py-core
> Reporter: Robert Bradshaw
> Assignee: Robert Bradshaw
> Priority: Major
> Time Spent: 0.5h
> Remaining Estimate: 0h
>
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