tvalentyn commented on code in PR #28702: URL: https://github.com/apache/beam/pull/28702#discussion_r1340457757
########## website/www/site/content/en/documentation/sdks/python-unrecoverable-errors.md: ########## @@ -0,0 +1,56 @@ +--- +type: languages +title: "Unrecoverable Errors in Beam Python" +--- +<!-- +Licensed 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. +--> + +# Unrecoverable Errors in Beam Python + +## What is an Unrecoverable Error? + +An unrecoverable error is an issue at job start-up time that will +prevent a job from ever running successfully, usually due to some kind +of misconfiguration. Solving these issues when they occur is key to +successfully running a Beam Python pipeline. + +## Common Unrecoverable Errors + +### Job Submission/Runtime Python Version Mismatch + +If the Python version used for job submission does not match the +Python version used to build the worker container, the job will not +execute. Ensure that the Python version being used for job submission +and the container Python version match. + +### PIP Dependency Resolution Failures + +During worker start-up, dependencies are checked and installed in +the worker container before accepting work. If there’s an issue during +this process (e.g. a dependency version cannot be found) the worker +will restart and try again up to four times before outright failing. Review Comment: > the worker will restart and try again up to four times This is a dataflow behavior, not Beam behavior. ########## website/www/site/content/en/documentation/sdks/python-unrecoverable-errors.md: ########## @@ -0,0 +1,56 @@ +--- +type: languages +title: "Unrecoverable Errors in Beam Python" +--- +<!-- +Licensed 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. +--> + +# Unrecoverable Errors in Beam Python + +## What is an Unrecoverable Error? + +An unrecoverable error is an issue at job start-up time that will +prevent a job from ever running successfully, usually due to some kind +of misconfiguration. Solving these issues when they occur is key to +successfully running a Beam Python pipeline. + +## Common Unrecoverable Errors + +### Job Submission/Runtime Python Version Mismatch + +If the Python version used for job submission does not match the +Python version used to build the worker container, the job will not +execute. Ensure that the Python version being used for job submission +and the container Python version match. + +### PIP Dependency Resolution Failures + +During worker start-up, dependencies are checked and installed in Review Comment: When pipeline requires additional dependencies, and these dependencies are not already available in runtime environment, these dependencies will be installed at worker startup time. ########## website/www/site/content/en/documentation/sdks/python-unrecoverable-errors.md: ########## @@ -0,0 +1,56 @@ +--- +type: languages +title: "Unrecoverable Errors in Beam Python" +--- +<!-- +Licensed 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. +--> + +# Unrecoverable Errors in Beam Python + +## What is an Unrecoverable Error? + +An unrecoverable error is an issue at job start-up time that will +prevent a job from ever running successfully, usually due to some kind +of misconfiguration. Solving these issues when they occur is key to +successfully running a Beam Python pipeline. + +## Common Unrecoverable Errors + +### Job Submission/Runtime Python Version Mismatch + +If the Python version used for job submission does not match the +Python version used to build the worker container, the job will not +execute. Ensure that the Python version being used for job submission +and the container Python version match. + +### PIP Dependency Resolution Failures + +During worker start-up, dependencies are checked and installed in +the worker container before accepting work. If there’s an issue during +this process (e.g. a dependency version cannot be found) the worker +will restart and try again up to four times before outright failing. +Ensure that dependency versions provided in your requirements.txt file +exist and can be installed locally before submitting jobs. + +### Dependency Verision Mismatches + +When additional dependencies like torch, transformers, etc are not +specified via requirements_file or preinstalled with a custom container +then the worker may go into a restart loop trying to install dependencies Review Comment: Mismatch happens after installation, when worker already started; at this point we won't attempt more installations. ########## website/www/site/content/en/documentation/sdks/python-unrecoverable-errors.md: ########## @@ -0,0 +1,56 @@ +--- +type: languages +title: "Unrecoverable Errors in Beam Python" +--- +<!-- +Licensed 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. +--> + +# Unrecoverable Errors in Beam Python + +## What is an Unrecoverable Error? + +An unrecoverable error is an issue at job start-up time that will +prevent a job from ever running successfully, usually due to some kind +of misconfiguration. Solving these issues when they occur is key to +successfully running a Beam Python pipeline. + +## Common Unrecoverable Errors + +### Job Submission/Runtime Python Version Mismatch + +If the Python version used for job submission does not match the +Python version used to build the worker container, the job will not +execute. Ensure that the Python version being used for job submission +and the container Python version match. + +### PIP Dependency Resolution Failures + +During worker start-up, dependencies are checked and installed in +the worker container before accepting work. If there’s an issue during +this process (e.g. a dependency version cannot be found) the worker +will restart and try again up to four times before outright failing. +Ensure that dependency versions provided in your requirements.txt file +exist and can be installed locally before submitting jobs. + +### Dependency Verision Mismatches Review Comment: To avoid mismatches, see tips submission and runtime environment should be compatible with each other. For more information, see: https://beam.apache.org/documentation/sdks/python-pipeline-dependencies/#control-dependencies ########## website/www/site/content/en/documentation/sdks/python-unrecoverable-errors.md: ########## @@ -0,0 +1,56 @@ +--- +type: languages +title: "Unrecoverable Errors in Beam Python" +--- +<!-- +Licensed 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. +--> + +# Unrecoverable Errors in Beam Python + +## What is an Unrecoverable Error? + +An unrecoverable error is an issue at job start-up time that will +prevent a job from ever running successfully, usually due to some kind +of misconfiguration. Solving these issues when they occur is key to +successfully running a Beam Python pipeline. + +## Common Unrecoverable Errors + +### Job Submission/Runtime Python Version Mismatch + +If the Python version used for job submission does not match the +Python version used to build the worker container, the job will not +execute. Ensure that the Python version being used for job submission +and the container Python version match. + +### PIP Dependency Resolution Failures + +During worker start-up, dependencies are checked and installed in +the worker container before accepting work. If there’s an issue during +this process (e.g. a dependency version cannot be found) the worker Review Comment: or worker doesn't have a connection to PyPI -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. 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