How can I upload a .parquet file from my local machine to Azure Storage Data Lake Gen2?

Question

I have a set of .parquet files in my local machine that I am trying to upload to a container in Data Lake Gen2.

I cannot do the following:

def upload_file_to_directory():
    try:

        file_system_client = service_client.get_file_system_client(file_system="my-file-system")

        directory_client = file_system_client.get_directory_client("my-directory")
        
        file_client = directory_client.create_file("uploaded-file.parquet")
        local_file = open("C:\\file-to-upload.parquet",'r')

        file_contents = local_file.read()

        file_client.append_data(data=file_contents, offset=0, length=len(file_contents))

        file_client.flush_data(len(file_contents))

    except Exception as e:
      print(e)

because the .parquet file cannot read by the .read() function.

When I try do this:

def upload_file_to_directory():

     file_system_client = service_client.get_file_system_client(file_system="my-file-system")

     directory_client = file_system_client.get_directory_client("my-directory")
        
     file_client = directory_client.create_file("uploaded-file.parquet")
     file_client.upload_file("C:\\file-to-upload.txt",'r')

I get the following error:

AttributeError: 'DataLakeFileClient' object has no attribute 'upload_file'

Any suggestions?

Answer 1

You are receiving this because you have imported DataLakeFileClient module. Try installing DataLakeServiceClient since it has upload_file method.

pip install DataLakeServiceClient

However, to read the .parquet file, one of the workarounds is to use pandas . Below is the code that worked for me.

storage_account_name='<ACCOUNT_NAME>'
storage_account_key='ACCOUNT_KEY'

service_client = DataLakeServiceClient(account_url="{}://{}.dfs.core.windows.net".format(
            "https", storage_account_name), credential=storage_account_key)
    
file_system_client = service_client.get_file_system_client(file_system="container")

directory_client = file_system_client.get_directory_client(directory="directory")
        
file_client = directory_client.create_file("uploaded-file.parquet")

local_file = pd.read_parquet("<YOUR_FILE_NAME>.parquet")
df = pd.DataFrame(local_file).to_parquet()

file_client.upload_data(data=df,overwrite=True) #Either of the lines works
#file_client.append_data(data=df, offset=0, length=len(df)) 
file_client.flush_data(len(df))

and you may be required to import DataLakeFileClient library to make this work:

from azure.storage.filedatalake import DataLakeServiceClient
import pandas as pd

RESULTS: