# Azure Storage

{% hint style="danger" %}
Databricks-Specific Functionality
{% endhint %}

## Mounting Blob Storage

Once you create your blob storage account in Azure, you will need to grab a couple bits of information from the Azure Portal before you mount your storage.

* You can find your Storage Account Name (which will go in  below) and your Key (which will go in  below) under **Access Keys** in your Storage Account resource in Azure.

![](https://1150130598-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-LbIjUyYyn8XW78ocYcy%2F-Lq7OCKIAzjWpC1tqNC7%2F-Lq7ODRL6lNN5ScPvA34%2Fmountblob_1.png?generation=1569951379799672\&alt=media)

* Go into your Storage Account resource in Azure and click on **Blobs**. Here, you will find all of your containers. Pick the one you want to mount and copy  its name into  below.

![](https://1150130598-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-LbIjUyYyn8XW78ocYcy%2F-Lq7OCKIAzjWpC1tqNC7%2F-Lq7ODRNOQ3nZnLtYy8K%2Fmountblob_2.png?generation=1569951379483059\&alt=media)

* As for the mount point (`/mnt/<FOLDERNAME>` below), you can name this whatever you'd like, but it will help you in the long run to name it something useful along the lines of `storageaccount_container`.

Once you have the required bits of information, you can use the following code to mount the storage location inside the Databricks environment

```python
dbutils.fs.mount(
  source = "wasbs://<CONTAINERNAME>@<STORAGEACCOUNT>.blob.core.windows.net",
  mount_point = "/mnt/<FOLDERNAME>/",
  extra_configs = {"fs.azure.account.key.<STORAGEACCOUNT>.blob.core.windows.net":"<KEYGOESHERE>"})
```

You can then test to see if you can list the files in your mounted location

```python
display(dbutils.fs.ls("/mnt/<FOLDERNAME>"))
```

### Resources:

* To learn how to create an Azure Storage service, visit <https://docs.microsoft.com/en-us/azure/storage/>

## Mounting Data Lake Storage

For finer-grained access controls on your data, you may opt to use Azure Data Lake Storage. In Databricks, you can connect to your data lake in a similar manner to blob storage. Instead of an access key, your user credentials will be passed through, therefore only showing you data that you specifically have access to.

### Pass-through Azure Active Directory Credentials

To pass in your Azure Active Directory credentials from Databricks to Azure Data Lake Store, you will need to enable this feature in Databricks under **New Cluster** > **Advanced Options**.

Note: If you create a *High Concurrency* cluster, multiple users can use the same cluster. The *Standard* cluster mode will only allow a single user's credential at a time.

![](https://1150130598-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-LbIjUyYyn8XW78ocYcy%2F-MGn3h_SEbon55g4Rip3%2F-MGn6EUaD3gt-OscGOwe%2Fdbx_cred_passthrough.png?alt=media\&token=e538189a-153e-46c5-bd07-85c7dd6ae120)

```python
configs = {
  "fs.azure.account.auth.type": "CustomAccessToken",
  "fs.azure.account.custom.token.provider.class": spark.conf.get("spark.databricks.passthrough.adls.gen2.tokenProviderClassName")
}
```

```python
dbutils.fs.mount(
  source = "abfss://<CONTAINERNAME>@<STORAGEACCOUNT>.dfs.core.windows.net/",
  mount_point = "/mnt/<FOLDERNAME>",
  extra_configs = configs)
```