Azure / Azure/MachineLearningNotebooks

Error when using `to_pandas_dataframe` method on input datatsets ot a Run

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Beschreibung

Hi,

I am passing a `DatasetConsumptionConfig` (Dataset.as_named_input()) object as one of the inputs to my `CommandStep`. In the script file that runs on the compute target, when I try to get the `dataframe` from the dataset using `run.input_datasets['name_of_dataset'].to_pandas_dataframe()`, I get the following error:

```
Traceback (most recent call last):
File "/home/app/pyenv/lib/python3.8/site-packages/azureml/data/dataset_error_handling.py", line 101, in _try_execute
return action()
File "/home/app/pyenv/lib/python3.8/site-packages/azureml/data/tabular_dataset.py", line 168, in
df = _try_execute(lambda: dataflow.to_pandas_dataframe(on_error=on_error,
File "/home/app/pyenv/lib/python3.8/site-packages/azureml/dataprep/api/_loggerfactory.py", line 210, in wrapper
return func(*args, **kwargs)
File "/home/app/pyenv/lib/python3.8/site-packages/azureml/dataprep/api/dataflow.py", line 696, in to_pandas_dataframe
return get_dataframe_reader().to_pandas_dataframe(self,
File "/home/app/pyenv/lib/python3.8/site-packages/azureml/dataprep/api/_dataframereader.py", line 295, in to_pandas_dataframe
return to_pandas_feather()
File "/home/app/pyenv/lib/python3.8/site-packages/azureml/dataprep/api/_dataframereader.py", line 231, in to_pandas_feather
dataflow._engine_api.execute_anonymous_activity(
File "/home/app/pyenv/lib/python3.8/site-packages/azureml/dataprep/api/_aml_helper.py", line 38, in wrapper
return send_message_func(op_code, message, cancellation_token)
File "/home/app/pyenv/lib/python3.8/site-packages/azureml/dataprep/api/engineapi/api.py", line 120, in execute_anonymous_activity
response = self._message_channel.send_message('Engine.ExecuteActivity', message_args, cancellation_token)
File "/home/app/pyenv/lib/python3.8/site-packages/azureml/dataprep/api/engineapi/engine.py", line 291, in send_message
raise_engine_error(response['error'])
File "/home/app/pyenv/lib/python3.8/site-packages/azureml/dataprep/api/errorhandlers.py", line 10, in raise_engine_error
raise ExecutionError(error_response)
azureml.dataprep.api.errorhandlers.ExecutionError:
Error Code: ScriptExecution.DatastoreResolution.Unexpected
Failed Step: 3fba0a5d-426b-476e-9efd-9a6a2271b5a7
Error Message: ScriptExecutionException was caused by DatastoreResolutionException.
DatastoreResolutionException was caused by UnexpectedException.
Unexpected failure making request to fetching info for Datastore 'workspaceblobstore' in subscription: Using base service url: https://eastus2.experiments.azureml.net. HResult: 0x80131501.
The SSL connection could not be established, see inner exception.
| session_id=

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "data_cleaning/clean_orders.py", line 20, in
orders_df = run.input_datasets['raw_orders'].to_pandas_dataframe()
File "/home/app/pyenv/lib/python3.8/site-packages/azureml/data/_loggerfactory.py", line 129, in wrapper
return func(*args, **kwargs)
File "/home/app/pyenv/lib/python3.8/site-packages/azureml/data/tabular_dataset.py", line 168, in to_pandas_dataframe
df = _try_execute(lambda: dataflow.to_pandas_dataframe(on_error=on_error,
File "/home/app/pyenv/lib/python3.8/site-packages/azureml/data/dataset_error_handling.py", line 104, in _try_execute
_dataprep_error_handler(e, message, is_dprep_exception)
File "/home/app/pyenv/lib/python3.8/site-packages/azureml/data/dataset_error_handling.py", line 156, in _dataprep_error_handler
raise AzureMLException(message, inner_exception=e)
azureml._common.exceptions.AzureMLException: AzureMLException:
Message: Execution failed in operation 'to_pandas_dataframe' for Dataset(id='', name='raw_orders', version=1, error_code=ScriptExecution.DatastoreResolution.Unexpected,error_message=ScriptExecutionException was caused by DatastoreResolutionException.
DatastoreResolutionException was caused by UnexpectedException.
Unexpected failure making request to fetching info for Datastore 'workspaceblobstore' in subscription: Using base service url: https://eastus2.experiments.azureml.net. HResult: 0x80131501.
Failed due to inner exception of type: HttpRequestException
| session_id=) ErrorCode: ScriptExecution.DatastoreResolution.Unexpected
InnerException
Error Code: ScriptExecution.DatastoreResolution.Unexpected
Failed Step: 3fba0a5d-426b-476e-9efd-9a6a2271b5a7
Error Message: ScriptExecutionException was caused by DatastoreResolutionException.
DatastoreResolutionException was caused by UnexpectedException.
Unexpected failure making request to fetching info for Datastore 'workspaceblobstore' in subscription:. Using base service url: https://eastus2.experiments.azureml.net. HResult: 0x80131501.
The SSL connection could not be established, see inner exception.
| session_id=
ErrorResponse
{
"error": {
"message": "Execution failed in operation 'to_pandas_dataframe' for Dataset(id='', name='raw_orders', version=1, error_code=ScriptExecution.DatastoreResolution.Unexpected,error_message=ScriptExecutionException was caused by DatastoreResolutionException.\n DatastoreResolutionException was caused by UnexpectedException.\n Unexpected failure making request to fetching info for Datastore 'workspaceblobstore' in subscription: '. Using base service url: https://eastus2.experiments.azureml.net. HResult: 0x80131501.\n Failed due to inner exception of type: HttpRequestException\n| session_id=) ErrorCode: ScriptExecution.DatastoreResolution.Unexpected"
}
}
```

Can you please tell me why this error occurs? Serached online for this but wasn't able to figure out the issue.

TIA.

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Rechercherichtung

Lies data_cleaning/clean_orders.py in Zeile 20 und reproduziere den CommandStep-Eingabepfad mithilfe von DatasetConsumptionConfig; untersuche den Aufruf von to_pandas_dataframe und dessen vollständigen Traceback. Als abgeschlossen gilt die Dokumentation einer reproduzierbaren Ursache und einer bestätigten Lösung für den DatastoreResolution/SSL-Fehler.

Vom Indexierungsmodell aus dem Issue-Text verfasst.

Bewertung

Tech-Stack
azure, python
Bereich
cloud, machine-learning
Issue-Typ
Bug
Schwierigkeit
4/5
Geschätzter Aufwand
3-5 Tage
Aktivitätsstatus
Veraltet
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Muss geklärt werden
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25/100

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