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articles/machine-learning/resource-known-issues.md

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@@ -78,10 +78,20 @@ Learn about the [resource quotas](how-to-manage-quotas.md) you might encounter w
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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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* **Pip Installation: Dependecies are not guaranteed to be consistent with single line installation**: This is a known limiation of pip as it does not have a functioning dependency resolver when you install as a single line. The first unique dependency is the only one it looks at. For example, if you notice that package 1 has version X > 1.0 and another package requires version X < 1.2, if the latest version X is 1.3 everything gets upgraded to 1.3 even though the 2nd package needs an older version. Refer to the following solution to upgrade the required packages:
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* Instead of pip installing the Azure ML SDK as a single line, users should "pip install azure-ml datadrift; pip install azureml-train-automl" separately. The order does not matter.
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* **Pip Installation: Dependecies are not guaranteed to be consistent with single line installation**: This is a known limitation of pip as it does not have a functioning dependency resolver when you install as a single line. The first unique dependency is the only one it looks at. For example, if you are installing azure-ml-datadrift which requires version > 1.0 and azureml-train-automl which requires version < 1.2 and if the latest version is 1.3, when the user installs the packages in a single line as shown below, everything gets upgraded to 1.3 even though the azureml-train-automl package requires an older version.
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* You will see inconsistent dependecies with single line installation.
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```python
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pip install azure-ml-datadrift, azureml-train-automl
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```
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* To ensure the appropriate versions are installed for your packages, install using multiple lines like in the following code. Order doesn't matter here.
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```python
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pip install azure-ml-datadrift
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pip install azureml-train-automl
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```
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## Create and manage workspaces
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> [!WARNING]

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