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https://issues.apache.org/jira/browse/BEAM-2855?focusedWorklogId=116756&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-116756
]
ASF GitHub Bot logged work on BEAM-2855:
----------------------------------------
Author: ASF GitHub Bot
Created on: 28/Jun/18 04:03
Start Date: 28/Jun/18 04:03
Worklog Time Spent: 10m
Work Description: aaltay commented on a change in pull request #5738:
[BEAM-2855] Add Python Nexmark suite
URL: https://github.com/apache/beam/pull/5738#discussion_r198701197
##########
File path:
sdks/python/apache_beam/testing/benchmarks/nexmark/nexmark_launcher.py
##########
@@ -0,0 +1,243 @@
+#
+# 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.
+#
+
+"""Nexmark launcher.
+
+The Nexmark suite is a series of queries (streaming pipelines) performed
+on a simulation of auction events. The launcher orchestrates the generation
+and parsing of streaming events and the running of queries.
+
+Model
+ - Person: Author of an auction or a bid.
+ - Auction: Item under auction.
+ - Bid: A bid for an item under auction.
+
+Events
+ - Create Person
+ - Create Auction
+ - Create Bid
+
+Queries
+ - Query0: Pass through (send and receive auction events).
+
+Usage
+ - DirectRunner
+ python nexmark_launcher.py \
+ --query/q <query number> \
+ --project <project id> \
+ --loglevel=DEBUG (optional) \
+ --streaming
+
+ - DataflowRunner
+ python nexmark_launcher.py \
+ --query/q <query number> \
+ --project <project id> \
+ --loglevel=DEBUG (optional) \
+ --streaming \
+ --sdk_location <apache_beam tar.gz> \
+ --staging_location=gs://... \
+ --temp_location=gs://
+
+"""
+
+from __future__ import absolute_import
+from __future__ import print_function
+
+import argparse
+import logging
+import sys
+import uuid
+
+from google.cloud import pubsub
+
+import apache_beam as beam
+from apache_beam.options.pipeline_options import GoogleCloudOptions
+from apache_beam.options.pipeline_options import PipelineOptions
+from apache_beam.options.pipeline_options import SetupOptions
+from apache_beam.options.pipeline_options import StandardOptions
+from apache_beam.options.pipeline_options import TestOptions
+from apache_beam.testing.benchmarks.nexmark.nexmark_util import Command
+from apache_beam.testing.benchmarks.nexmark.queries import query0
+
+
+class NexmarkLauncher(object):
+ def __init__(self):
+ self.parse_args()
+ self.uuid = str(uuid.uuid4())
+ self.topic_name = self.args.topic_name + self.uuid
+ self.subscription_name = self.args.subscription_name + self.uuid
+
+ def parse_args(self):
+ parser = argparse.ArgumentParser()
+
+ parser.add_argument('--query', '-q',
+ type=int,
+ action='append',
+ required=True,
+ choices=[0, 1, 2],
+ help='Query to run')
+
+ parser.add_argument('--subscription_name',
+ type=str,
+ help='Pub/Sub subscription to read from')
+
+ parser.add_argument('--topic_name',
+ type=str,
+ help='Pub/Sub topic to read from')
+
+ parser.add_argument('--loglevel',
+ choices=['DEBUG', 'INFO', 'WARNING',
+ 'ERROR', 'CRITICAL'],
+ default='INFO',
+ help='Set logging level to debug')
+ parser.add_argument('--input',
+ type=str,
+ required=True,
+ help='Path to the data file containing nexmark
events.')
+
+ self.args, self.pipeline_args = parser.parse_known_args()
+ logging.basicConfig(level=getattr(logging, self.args.loglevel, None),
+ format='(%(threadName)-10s) %(message)s')
+
+ self.pipeline_options = PipelineOptions(self.pipeline_args)
+ logging.debug('args, pipeline_args: %s, %s', self.args, self.pipeline_args)
+
+ # Usage with Dataflow requires a project to be supplied.
+ self.project = self.pipeline_options.view_as(GoogleCloudOptions).project
+ if self.project is None:
+ parser.print_usage()
+ print(sys.argv[0] + ': error: argument --project is required')
+ sys.exit(1)
+
+ # Pub/Sub is currently available for use only in streaming pipelines.
+ self.streaming = self.pipeline_options.view_as(StandardOptions).streaming
+ if self.streaming is None:
+ parser.print_usage()
+ print(sys.argv[0] + ': error: argument --streaming is required')
+ sys.exit(1)
+
+ # wait_until_finish ensures that the streaming job is canceled.
+ self.wait_until_finish_duration = (
Review comment:
`--wait_until_finish_duration` is missing from the usage example. (Not a
blocker for merging this PR.)
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Issue Time Tracking
-------------------
Worklog Id: (was: 116756)
Time Spent: 10h 50m (was: 10h 40m)
> Implement a python version of the nexmark queries
> -------------------------------------------------
>
> Key: BEAM-2855
> URL: https://issues.apache.org/jira/browse/BEAM-2855
> Project: Beam
> Issue Type: Improvement
> Components: examples-nexmark, sdk-py-core, testing
> Reporter: Ismaël Mejía
> Assignee: María GH
> Priority: Minor
> Labels: newbie, nexmark, starter
> Time Spent: 10h 50m
> Remaining Estimate: 0h
>
> Currently we have a Java only implementation of Nexmark, a python based
> implementation would be nice to have to validate the direct and dataflow
> runners, but also to validate the new support of multiple SDKs in multiple
> runners via the runner/fn API.
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