Reading Json file from Azure datalake as a file using Json.load in Azure databricks /Synapse notebooks

Question

I am trying to parse Json data with multi nested level. I am using the approach is giving filename and using open(File-name) to load the data. when I am providing datalake path, it is throwing error that file path not found. I am able to read data in dataframes but How can I read file from data lake without converting to dataframes and reading it as a file and open it?

Current code approach on local machine which is working:

f = open(File_Name.Json)
data = json.load(f)

Failing scenario when provding datalake path:

f = open(Datalake path/File_Name.Json)
data = json.load(f)

Answer 1

You need to mount the data lake folder to a location in dbfs (in Databricks), although mounting is a security risk. Anyone with access to Databricks resource will have access to all mounted locations.
Documentation on mounting to dbfs: https://docs.databricks.com/data/databricks-file-system.html#mount-object-storage-to-dbfs

Answer 2

The open function works only with local files, not understanding (out of box) the cloud file paths. You can of course try to mount the cloud storage, but as it was mentioned by @ARCrow, it would be a security risk (until you create so-called passthrough mount that will control access on the cloud storage level).

But if you're able to read file into dataframe, then it means that cluster has all necessary settings for accessing the cloud storage - in this case you can just use dbutils.fs.cp command to copy file from the cloud storage to local disk, and then open it with open function. Something like this:

dbutils.fs.cp("Datalake path/File_Name.Json", "file:///tmp/File_Name.Json")
with open("/tmp/File_Name.Json", "r") as f:
  data = json.load(f)