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new a13749fd529 [Python] Allow users to pass service name for profiler
(#26220)
a13749fd529 is described below
commit a13749fd5296452a65969e0a277aab4554d11dc1
Author: Ritesh Ghorse <riteshgho...@gmail.com>
AuthorDate: Wed May 3 10:38:11 2023 -0400
[Python] Allow users to pass service name for profiler (#26220)
* handle service name for profiler
* add debug messages
* remove logs
* move import statement and logs
* rm unnecessary check
* add helper to GCloudOption
* rm lint
* added new helper and unit test
* separate functions
* updated unit tests
* refactored plus check for envvar
* updated changes.md
---
CHANGES.md | 1 +
.../python/apache_beam/options/pipeline_options.py | 16 ++++++
.../apache_beam/runners/worker/data_sampler.py | 1 -
.../apache_beam/runners/worker/sdk_worker_main.py | 58 +++++++++++++---------
.../runners/worker/sdk_worker_main_test.py | 29 +++++++++++
5 files changed, 80 insertions(+), 25 deletions(-)
diff --git a/CHANGES.md b/CHANGES.md
index bcd74f7dd51..85b3d03c146 100644
--- a/CHANGES.md
+++ b/CHANGES.md
@@ -66,6 +66,7 @@
## New Features / Improvements
+* Allow passing service name for google-cloud-profiler (Python)
([#26280](https://github.com/apache/beam/issues/26280)).
* Dead letter queue support added to RunInference in Python
([#24209](https://github.com/apache/beam/issues/24209)).
* Support added for defining pre/postprocessing operations on the RunInference
transform ([#26308](https://github.com/apache/beam/issues/26308))
diff --git a/sdks/python/apache_beam/options/pipeline_options.py
b/sdks/python/apache_beam/options/pipeline_options.py
index a602912cd97..283c2caa49d 100644
--- a/sdks/python/apache_beam/options/pipeline_options.py
+++ b/sdks/python/apache_beam/options/pipeline_options.py
@@ -22,6 +22,7 @@
import argparse
import json
import logging
+import os
from typing import Any
from typing import Callable
from typing import Dict
@@ -876,6 +877,21 @@ class GoogleCloudOptions(PipelineOptions):
return errors
+ def get_cloud_profiler_service_name(self):
+ _ENABLE_GOOGLE_CLOUD_PROFILER = 'enable_google_cloud_profiler'
+ if self.dataflow_service_options:
+ if _ENABLE_GOOGLE_CLOUD_PROFILER in self.dataflow_service_options:
+ return os.environ["JOB_NAME"]
+ for option_name in self.dataflow_service_options:
+ if option_name.startswith(_ENABLE_GOOGLE_CLOUD_PROFILER + '='):
+ return option_name.split('=', 1)[1]
+
+ experiments = self.view_as(DebugOptions).experiments or []
+ if _ENABLE_GOOGLE_CLOUD_PROFILER in experiments:
+ return os.environ["JOB_NAME"]
+
+ return None
+
class AzureOptions(PipelineOptions):
"""Azure Blob Storage options."""
diff --git a/sdks/python/apache_beam/runners/worker/data_sampler.py
b/sdks/python/apache_beam/runners/worker/data_sampler.py
index 2b37d008040..7cc8152693d 100644
--- a/sdks/python/apache_beam/runners/worker/data_sampler.py
+++ b/sdks/python/apache_beam/runners/worker/data_sampler.py
@@ -29,7 +29,6 @@ from typing import Dict
from typing import Iterable
from typing import List
from typing import Optional
-from typing import Tuple
from typing import Union
from apache_beam.coders.coder_impl import CoderImpl
diff --git a/sdks/python/apache_beam/runners/worker/sdk_worker_main.py
b/sdks/python/apache_beam/runners/worker/sdk_worker_main.py
index b643034899d..e0545e1f007 100644
--- a/sdks/python/apache_beam/runners/worker/sdk_worker_main.py
+++ b/sdks/python/apache_beam/runners/worker/sdk_worker_main.py
@@ -173,32 +173,42 @@ def create_harness(environment, dry_run=False):
return fn_log_handler, sdk_harness, sdk_pipeline_options
+def _start_profiler(gcp_profiler_service_name, gcp_profiler_service_version):
+ try:
+ import googlecloudprofiler
+ if gcp_profiler_service_name and gcp_profiler_service_version:
+ googlecloudprofiler.start(
+ service=gcp_profiler_service_name,
+ service_version=gcp_profiler_service_version,
+ verbose=1)
+ _LOGGER.info('Turning on Google Cloud Profiler.')
+ else:
+ raise RuntimeError('Unable to find the job id or job name from envvar.')
+ except Exception as e: # pylint: disable=broad-except
+ _LOGGER.warning(
+ 'Unable to start google cloud profiler due to error: %s. For how to '
+ 'enable Cloud Profiler with Dataflow see '
+ 'https://cloud.google.com/dataflow/docs/guides/profiling-a-pipeline.'
+ 'For troubleshooting tips with Cloud Profiler see '
+ 'https://cloud.google.com/profiler/docs/troubleshooting.' % e)
+
+
+def _get_gcp_profiler_name_if_enabled(sdk_pipeline_options):
+ gcp_profiler_service_name = sdk_pipeline_options.view_as(
+ GoogleCloudOptions).get_cloud_profiler_service_name()
+
+ return gcp_profiler_service_name
+
+
def main(unused_argv):
"""Main entry point for SDK Fn Harness."""
- fn_log_handler, sdk_harness, sdk_pipeline_options =
create_harness(os.environ)
- experiments = sdk_pipeline_options.view_as(DebugOptions).experiments or []
- dataflow_service_options = (
- sdk_pipeline_options.view_as(GoogleCloudOptions).dataflow_service_options
- or [])
- if (_ENABLE_GOOGLE_CLOUD_PROFILER in experiments) or (
- _ENABLE_GOOGLE_CLOUD_PROFILER in dataflow_service_options):
- try:
- import googlecloudprofiler
- job_id = os.environ["JOB_ID"]
- job_name = os.environ["JOB_NAME"]
- if job_id and job_name:
- googlecloudprofiler.start(
- service=job_name, service_version=job_id, verbose=1)
- _LOGGER.info('Turning on Google Cloud Profiler.')
- else:
- raise RuntimeError('Unable to find the job id or job name from
envvar.')
- except Exception as e: # pylint: disable=broad-except
- _LOGGER.warning(
- 'Unable to start google cloud profiler due to error: %s. For how to '
- 'enable Cloud Profiler with Dataflow see '
- 'https://cloud.google.com/dataflow/docs/guides/profiling-a-pipeline.'
- 'For troubleshooting tips with Cloud Profiler see '
- 'https://cloud.google.com/profiler/docs/troubleshooting.' % e)
+ (fn_log_handler, sdk_harness,
+ sdk_pipeline_options) = create_harness(os.environ)
+
+ gcp_profiler_name = _get_gcp_profiler_name_if_enabled(sdk_pipeline_options)
+ if gcp_profiler_name:
+ _start_profiler(gcp_profiler_name, os.environ["JOB_ID"])
+
try:
_LOGGER.info('Python sdk harness starting.')
sdk_harness.run()
diff --git a/sdks/python/apache_beam/runners/worker/sdk_worker_main_test.py
b/sdks/python/apache_beam/runners/worker/sdk_worker_main_test.py
index c7ec4220850..00e09840787 100644
--- a/sdks/python/apache_beam/runners/worker/sdk_worker_main_test.py
+++ b/sdks/python/apache_beam/runners/worker/sdk_worker_main_test.py
@@ -21,6 +21,7 @@
import io
import logging
+import os
import unittest
from hamcrest import all_of
@@ -205,6 +206,34 @@ class SdkWorkerMainTest(unittest.TestCase):
sdk_worker_main._set_log_level_overrides(overrides)
self.assertIn(expected, cm.output[0])
+ def test_gcp_profiler_uses_provided_service_name_when_specified(self):
+ options = PipelineOptions(
+ ['--dataflow_service_options=enable_google_cloud_profiler=sample'])
+ gcp_profiler_name = sdk_worker_main._get_gcp_profiler_name_if_enabled(
+ options)
+ sdk_worker_main._start_profiler = unittest.mock.MagicMock()
+ sdk_worker_main._start_profiler(gcp_profiler_name, "version")
+ sdk_worker_main._start_profiler.assert_called_with("sample", "version")
+
+ @unittest.mock.patch.dict(os.environ, {"JOB_NAME": "sample_job"}, clear=True)
+ def test_gcp_profiler_uses_job_name_when_service_name_not_specified(self):
+ options = PipelineOptions(
+ ['--dataflow_service_options=enable_google_cloud_profiler'])
+ gcp_profiler_name = sdk_worker_main._get_gcp_profiler_name_if_enabled(
+ options)
+ sdk_worker_main._start_profiler = unittest.mock.MagicMock()
+ sdk_worker_main._start_profiler(gcp_profiler_name, "version")
+ sdk_worker_main._start_profiler.assert_called_with("sample_job", "version")
+
+ @unittest.mock.patch.dict(os.environ, {"JOB_NAME": "sample_job"}, clear=True)
+ def test_gcp_profiler_uses_job_name_when_enabled_as_experiment(self):
+ options = PipelineOptions(['--experiment=enable_google_cloud_profiler'])
+ gcp_profiler_name = sdk_worker_main._get_gcp_profiler_name_if_enabled(
+ options)
+ sdk_worker_main._start_profiler = unittest.mock.MagicMock()
+ sdk_worker_main._start_profiler(gcp_profiler_name, "version")
+ sdk_worker_main._start_profiler.assert_called_with("sample_job", "version")
+
if __name__ == '__main__':
logging.getLogger().setLevel(logging.INFO)
