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https://issues.apache.org/jira/browse/BEAM-9085?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17029222#comment-17029222
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Valentyn Tymofieiev commented on BEAM-9085:
-------------------------------------------
Somewhat faster way to obtain the same information is to pass: --profile_cpu
--profile_sample_rate=1 --profile_location=/tmp
Full command:
{noformat}
python setup.py nosetests --nocapture --test-pipeline-options=" --iterations=10
--number_of_counters=1 --number_of_counter_operations=1 --profile_cpu
--profile_sample_rate=1 --profile_location=/tmp --project=big-query-project
--publish_to_big_query=false --metrics_dataset=python_load_tests
--metrics_table=pardo --input_options='{ \"num_records\": 100000, \"key_size\":
10, \"value_size\":90, \"bundle_size_distribution_type\": \"const\",
\"bundle_size_distribution_param\": 1, \"force_initial_num_bundles\": 0 }'"
--tests apache_beam.testing.load_tests.pardo_test
{noformat}
> Investigate performance difference between Python 2/3 on Dataflow
> -----------------------------------------------------------------
>
> Key: BEAM-9085
> URL: https://issues.apache.org/jira/browse/BEAM-9085
> Project: Beam
> Issue Type: Bug
> Components: sdk-py-core
> Reporter: Kamil Wasilewski
> Assignee: Valentyn Tymofieiev
> Priority: Major
>
> Tests show that the performance of core Beam operations in Python 3.x on
> Dataflow can be a few time slower than in Python 2.7. We should investigate
> what's the cause of the problem.
> Currently, we have one ParDo test that is run both in Py3 and Py2 [1]. A
> dashboard with runtime results can be found here [2].
> [1] sdks/python/apache_beam/testing/load_tests/pardo_test.py
> [2] https://apache-beam-testing.appspot.com/explore?dashboard=5678187241537536
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