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@@ -86,9 +86,19 @@ Binary classification charts (precision-recall, ROC, gain curve etc.) shown in a
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## Datasets and Data Preparation
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These are known issues for Azure Machine Learning Datasets.
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### Fail to read Parquet file from HTTP or ADLS Gen 2
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There is a known issue in AzureML DataPrep SDK version 1.1.25 that causes a failure when creating a dataset by reading Parquet files from HTTP or ADLS Gen 2. To fix this issue, please upgrade to a version higher than 1.1.26, or downgrade to a version lower than 1.1.24.
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There is a known issue in AzureML DataPrep SDK version 1.1.25 that causes a failure when creating a dataset by reading Parquet files from HTTP or ADLS Gen 2. It will fail with `Cannot seek once reading started.`. To fix this issue, please upgrade `azureml-dataprep` to a version higher than 1.1.26, or downgrade to a version lower than 1.1.24.
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```python
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pip install --upgrade azureml-dataprep
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```
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### TypeError: mount() got an unexpected keyword argument 'invocation_id'
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This error occurs if you have an incompatible version between `azureml-core` and `azureml-dataprep`. If you see this error, upgrade `azureml-dataprep` package to a newer version (greater than or equal to 1.1.29).
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```python
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pip install --upgrade azureml-dataprep
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If you see a `FailToSendFeather` error when reading data on Azure Databricks cluster, refer to the following solutions:
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* Upgrade `azureml-sdk[automl]` package to the latest version.
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* Add `azure-dataprep` version 1.1.8 or above.
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* Add `azureml-dataprep` version 1.1.8 or above.
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* Add `pyarrow` version 0.11 or above.
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## Datasets
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These are known issues for Azure Machine Learning Datasets.
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+**Failed to read parquet files on Azure Data Lake Storage Gen2**
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Reading parquet files from Azure Data Lake Storage Gen2 datastores does not work if you have `azureml-dataprep==1.1.25` installed. It will fail with `Cannot seek once reading started.`. If you see this error, you can either install `azureml-dataprep<=1.1.24` or install `azureml-dataprep>=1.1.26`.
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## Azure portal
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If you go directly to view your workspace from a share link from the SDK or the portal, you will not be able to view the normal Overview page with subscription information in the extension. You will also not be able to switch into another workspace. If you need to view another workspace, the workaround is to go directly to [Azure Machine Learning studio](https://ml.azure.com) and search for the workspace name.
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