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.

• 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.

• 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

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

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.

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

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