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https://issues.apache.org/jira/browse/BEAM-7980?focusedWorklogId=297757&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-297757
]
ASF GitHub Bot logged work on BEAM-7980:
----------------------------------------
Author: ASF GitHub Bot
Created on: 20/Aug/19 10:49
Start Date: 20/Aug/19 10:49
Worklog Time Spent: 10m
Work Description: mxm commented on pull request #9371: [WIP] [BEAM-7980]
External environment with containerized worker pool
URL: https://github.com/apache/beam/pull/9371#discussion_r315619517
##########
File path: sdks/python/apache_beam/runners/worker/worker_pool_main.py
##########
@@ -0,0 +1,150 @@
+#
+# 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.
+#
+"""Worker pool entry point."""
+
+from __future__ import absolute_import
+
+import argparse
+import atexit
+import logging
+import subprocess
+import sys
+import threading
+import time
+from concurrent import futures
+
+import grpc
+
+from apache_beam.portability.api import beam_fn_api_pb2
+from apache_beam.portability.api import beam_fn_api_pb2_grpc
+from apache_beam.runners.worker import sdk_worker
+
+
+class BeamFnExternalWorkerPoolServicer(
+ beam_fn_api_pb2_grpc.BeamFnExternalWorkerPoolServicer):
+
+ def __init__(self, worker_threads, use_process=False,
+ container_executable=None):
+ self._worker_threads = worker_threads
+ self._use_process = use_process
+ self._container_executable = container_executable
+ self._worker_processes = {}
+
+ @classmethod
+ def start(cls, worker_threads=1, use_process=False, port=0,
+ container_executable=None):
+ worker_server = grpc.server(futures.ThreadPoolExecutor(max_workers=10))
+ worker_address = 'localhost:%s' % worker_server.add_insecure_port(
+ '[::]:%s' % port)
+ beam_fn_api_pb2_grpc.add_BeamFnExternalWorkerPoolServicer_to_server(
+ cls(worker_threads,
+ use_process=use_process,
+ container_executable=container_executable),
+ worker_server)
+ worker_server.start()
+ return worker_address, worker_server
+
+ def StartWorker(self, start_worker_request, unused_context):
+ try:
+ if self._use_process:
+ command = ['python', '-c',
+ 'from apache_beam.runners.worker.sdk_worker '
+ 'import SdkHarness; '
+ 'SdkHarness("%s",worker_count=%d,worker_id="%s").run()' % (
+ start_worker_request.control_endpoint.url,
+ self._worker_threads,
+ start_worker_request.worker_id)]
+ if self._container_executable:
+ # command as per container spec
+ command = [self._container_executable,
+ '--id=%s' % start_worker_request.worker_id,
+ '--logging_endpoint=%s'
+ % start_worker_request.logging_endpoint.url,
+ '--artifact_endpoint=%s'
+ % start_worker_request.artifact_endpoint.url,
+ '--provision_endpoint=%s'
+ % start_worker_request.provision_endpoint.url,
+ '--control_endpoint=%s'
+ % start_worker_request.control_endpoint.url,
+ ]
+
+ logging.warn("Starting worker with command %s" % command)
+ worker_process = subprocess.Popen(command, stdout=subprocess.PIPE)
+ self._worker_processes[start_worker_request.worker_id] = worker_process
+
+ # Register to kill the subprocess on exit.
+ atexit.register(worker_process.kill)
+ else:
+ worker = sdk_worker.SdkHarness(
+ start_worker_request.control_endpoint.url,
+ worker_count=self._worker_threads,
+ worker_id=start_worker_request.worker_id)
+ worker_thread = threading.Thread(
+ name='run_worker_%s' % start_worker_request.worker_id,
+ target=worker.run)
+ worker_thread.daemon = True
+ worker_thread.start()
+
+ return beam_fn_api_pb2.StartWorkerResponse()
+ except Exception as exn:
+ return beam_fn_api_pb2.StartWorkerResponse(error=str(exn))
+
+ def StopWorker(self, stop_worker_request, unused_context):
+ worker_process = self._worker_processes.pop(stop_worker_request.worker_id)
+ if worker_process:
+ logging.info("Stopping worker %s" % stop_worker_request.worker_id)
+ threading.Timer(1, lambda: worker_process.kill()).start()
+ worker_process.communicate()
Review comment:
Why the timer in the previous line, if we wait afterwards for the process to
quit?
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Issue Time Tracking
-------------------
Worklog Id: (was: 297757)
Time Spent: 1h (was: 50m)
> External environment with containerized worker pool
> ---------------------------------------------------
>
> Key: BEAM-7980
> URL: https://issues.apache.org/jira/browse/BEAM-7980
> Project: Beam
> Issue Type: Improvement
> Components: sdk-py-harness
> Reporter: Thomas Weise
> Assignee: Thomas Weise
> Priority: Major
> Time Spent: 1h
> Remaining Estimate: 0h
>
> Augment Beam Python docker image and boot.go so that it can be used to launch
> BeamFnExternalWorkerPoolServicer.
> [https://docs.google.com/document/d/1z3LNrRtr8kkiFHonZ5JJM_L4NWNBBNcqRc_yAf6G0VI/edit#heading=h.lnhm75dhvhi0]
>
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