Error : No parent external location found while creating a dataframe and saving as table in ADLS on azuredatabricks free trial

I have received the same ERROR below are the ERROR details:

Error[NO_PARENT_EXTERNAL_LOCATION_FOR_PATH] No parent external location was found for path 'abfss://[email protected]/Customer.csv. Please create an external location on one of the parent paths and then retry the query or command again.

The above ERROR indicates that the system cannot find the specified path

I have tried the below approach:

I have mounted my ADLS using the below script:

configs = { 'fs.azure.account.auth.type': 'OAuth', 'fs.azure.account.oauth.provider.type': 'org.apache.hadoop.fs.azurebfs.oauth2.ClientCredsTokenProvider', 'fs.azure.account.oauth2.client.id': '< YOUR CLIENT ID> ', 'fs.azure.account.oauth2.client.secret': dbutils.secrets.get(scope='dbxsecretscope', key='kvsecretname'), 'fs.azure.account.oauth2.client.endpoint': 'https://login.microsoftonline.com/< YOUR TENANT ID >/token' }

dbutils.fs.mount(source='abfss://[email protected]/', mount_point='/mnt/raw', extra_configs=configs)

Note: When you are mounting your ADLS to azure databricks you will need to add Storage Blob Data Contributor role to you ADLS & Key Vault Administrator role to Key Vault.

The below will let you to list your mount point:

display(dbutils.fs.mounts())

Know more about how to mount ADLS to Azure databricks using the SPN,Azure Key Vault

"Next, I created an external table from a single CSV file in Azure Databricks as an example."

%sql
CREATE  TABLE  IF  NOT  EXISTS  hive_metastore.default.cust USING csv OPTIONS (path  "/mnt/raw/new/Customer.csv", inferSchema=True, header=True)

Results:

df = spark.read.format("csv") \
.option("header", "true") \
.option("inferSchema", "true") \
.load("dbfs:/mnt/raw/new/Customer.csv")
df.show()

+--------------+
|          Col1|
+--------------+
|123,456@1234_1|
+--------------+