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https://issues.apache.org/jira/browse/BEAM-2855?focusedWorklogId=114996&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-114996
]
ASF GitHub Bot logged work on BEAM-2855:
----------------------------------------
Author: ASF GitHub Bot
Created on: 23/Jun/18 01:39
Start Date: 23/Jun/18 01:39
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_r197598008
##########
File path:
sdks/python/apache_beam/testing/benchmarks/nexmark/nexmark_launcher.py
##########
@@ -0,0 +1,199 @@
+#
+# 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> \
+ --streaming \
+
+- DataflowRunner
+python nexmark_launcher.py \
+ --query/q <query number> \
+ --project <project id> \
+ --streaming \
+ --sdk_location <apache_beam tar.gz> \
+ --staging_location=gs://... \
+ --temp_location=gs://
+
+"""
+from __future__ import print_function
+
+import argparse
+import logging
+import sys
+
+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 nexmark_util import Command
+from queries import query0
+
+logging.basicConfig(level=logging.INFO,
+ format='(%(threadName)-10s) %(message)s')
+
+# Reserved configuration to run these benchmark suite.
+PUBSUB_PROJECT = 'google.com:clouddfe'
+PUBSUB_SUBSCRIPTION = 'nexmark-benchmark'
+PUBSUB_TOPIC = 'nexmark-benchmark'
+
+# TODO(mariagh): Make comprehensive and large
+EVENT_COUNT_PER_TYPE = 3
+PERSON_EVENT =
'p12345,maria,ma...@maria.com,1234-5678-9012-3456,sunnyvale,CA,1528098831536' #
pylint: disable=line-too-long
+AUCTION_EVENT = 'a12345,car,2012 hyundai
elantra,20K,15K,1528098831536,20180630,maria,vehicle' # pylint:
disable=line-too-long
+BID_EVENT = 'b12345,maria,354,1528098831536'
+
+
+def parse_args():
+ parser = argparse.ArgumentParser()
+
+ parser.add_argument('--query', '-q',
+ type=int,
+ action='append',
+ required=True,
+ choices=[0, 1],
+ help='Query to run')
+
+ parser.add_argument('--subscription',
+ type=str,
+ help='Pub/Sub subscription to read from')
+
+ parser.add_argument('--topic',
+ type=str,
+ help='Pub/Sub topic to read from')
+
+ args, pipeline_args = parser.parse_known_args()
+ options = PipelineOptions(pipeline_args)
+ print('args, pipeline_args:', args, pipeline_args)
+
+ # Usage with Dataflow requires a project to be supplied.
+ if options.view_as(GoogleCloudOptions).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.
+ if options.view_as(StandardOptions).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.
+ if options.view_as(TestOptions).wait_until_finish_duration is None:
+ parser.print_usage()
+ print(sys.argv[0] + ': error: argument --wait_until_finish_duration is
required') # pylint: disable=line-too-long
+ sys.exit(1)
+
+ # We use the save_main_session option because one or more DoFn's in this
+ # workflow rely on global context (e.g., a module imported at module level).
+ options.view_as(SetupOptions).save_main_session = True
+ return args, options
+
+
+def generate_events(pipeline, args, pipeline_options):
+ from google.cloud import pubsub
+ publish_client = pubsub.Client(project=PUBSUB_PROJECT)
+ topic = publish_client.topic(PUBSUB_TOPIC)
+ sub = topic.subscription(PUBSUB_SUBSCRIPTION)
+ assert topic.exists()
+ assert sub.exists()
+
+ logging.info('Generating %d auction events to topic %s',
+ EVENT_COUNT_PER_TYPE*3, topic.name)
+ for _ in xrange(EVENT_COUNT_PER_TYPE):
+ topic.publish(PERSON_EVENT)
+ topic.publish(AUCTION_EVENT)
+ topic.publish(BID_EVENT)
+
+ logging.info('Finished event generation.')
+
+ # Read from PubSub into a PCollection.
+ if args.subscription:
+ raw_events = pipeline | 'ReadPubSub' >> beam.io.ReadFromPubSub(
+ subscription=args.subscription)
+ else:
+ raw_events = pipeline | 'ReadPubSub' >> beam.io.ReadFromPubSub(
+ topic=args.topic)
+
+ return raw_events
+
+
+def run_query(query, args, pipeline_options):
+ try:
+ pipeline = beam.Pipeline(options=pipeline_options)
+ raw_events = generate_events(pipeline, args, pipeline_options)
+ query.load(raw_events)
+ result = pipeline.run()
+ job_duration =
pipeline_options.view_as(TestOptions).wait_until_finish_duration # pylint:
disable=line-too-long
+ if pipeline_options.view_as(StandardOptions).runner == 'DataflowRunner':
+ result.wait_until_finish(duration=job_duration)
+ result.cancel()
+ else:
+ result.wait_until_finish()
+ except NotImplementedError as exp:
Review comment:
What would throw NotImplementedError in the above code?
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Issue Time Tracking
-------------------
Worklog Id: (was: 114996)
Time Spent: 1h 50m (was: 1h 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: 1h 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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