Azure Machine Learning - Access uri_folder dataset (ML v2) from notebook (not job)

G Cocci 191 Reputation points Microsoft Employee

Hi all,

I've registered in Azure Machine Learning a Data Lake Gen2 datastore that point to a container with a hierarchy of folders that contain avro files and on top of it I registered a folder_uri dataset (ML v2).

Now I want to access to these folders from a notebook, convert them in a pandas dataframe in order to do some data exploration.

I search on the documentation, and I only found examples that run job and using this type of dataset as input, but I need to be able to explore it using notebook.

Is it possible? How can I do it?


Azure Data Lake Storage
Azure Data Lake Storage
An Azure service that provides an enterprise-wide hyper-scale repository for big data analytic workloads and is integrated with Azure Blob Storage.
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Azure Machine Learning
Azure Machine Learning
An Azure machine learning service for building and deploying models.
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Accepted answer
  1. Ramr-msft 16,066 Reputation points

    @G Cocci Thanks for the question. Currently it's not supported to access the avro files. Here is the document for accessing the datastore using folder_uri dataset.

    Mapping Data Flow supports AVRO as a source type

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