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Upload data to the Azure ADLS Gen2 from on-premise using Python or Java


Upload data to the Azure ADLS Gen2 from on-premise using Python or Java

By : Jeen
Date : December 01 2020, 04:50 PM
it should still fix some issue According to the offical tutorial Quickstart: Upload, download, and list blobs with Python, as below, you can not directly use Azure Storage SDK for Python to do any operations in Azure Data Lake Store Gen 2 if you have not enrolled in the public preview of multi-protocol access on Data Lake Storage.
code :
import requests
import json

def auth(tenant_id, client_id, client_secret):
    print('auth')
    auth_headers = {
        "Content-Type": "application/x-www-form-urlencoded"
    }
    auth_body = {
        "client_id": client_id,
        "client_secret": client_secret,
        "scope" : "https://storage.azure.com/.default",
        "grant_type" : "client_credentials"
    }
    resp = requests.post(f"https://login.microsoftonline.com/{tenant_id}/oauth2/v2.0/token", headers=auth_headers, data=auth_body)
    return (resp.status_code, json.loads(resp.text))

def mkfs(account_name, fs_name, access_token):
    print('mkfs')
    fs_headers = {
        "Authorization": f"Bearer {access_token}"
    }
    resp = requests.put(f"https://{account_name}.dfs.core.windows.net/{fs_name}?resource=filesystem", headers=fs_headers)
    return (resp.status_code, resp.text)

def mkdir(account_name, fs_name, dir_name, access_token):
    print('mkdir')
    dir_headers = {
        "Authorization": f"Bearer {access_token}"
    }
    resp = requests.put(f"https://{account_name}.dfs.core.windows.net/{fs_name}/{dir_name}?resource=directory", headers=dir_headers)
    return (resp.status_code, resp.text)

def touch_file(account_name, fs_name, dir_name, file_name, access_token):
    print('touch_file')
    touch_file_headers = {
        "Authorization": f"Bearer {access_token}"
    }
    resp = requests.put(f"https://{account_name}.dfs.core.windows.net/{fs_name}/{dir_name}/{file_name}?resource=file", headers=touch_file_headers)
    return (resp.status_code, resp.text)

def append_file(account_name, fs_name, path, content, position, access_token):
    print('append_file')
    append_file_headers = {
        "Authorization": f"Bearer {access_token}",
        "Content-Type": "text/plain",
        "Content-Length": f"{len(content)}"
    }
    resp = requests.patch(f"https://{account_name}.dfs.core.windows.net/{fs_name}/{path}?action=append&position={position}", headers=append_file_headers, data=content)
    return (resp.status_code, resp.text)

def flush_file(account_name, fs_name, path, position, access_token):
    print('flush_file')
    flush_file_headers = {
        "Authorization": f"Bearer {access_token}"
    }
    resp = requests.patch(f"https://{account_name}.dfs.core.windows.net/{fs_name}/{path}?action=flush&position={position}", headers=flush_file_headers)
    return (resp.status_code, resp.text)

def mkfile(account_name, fs_name, dir_name, file_name, local_file_name, access_token):
    print('mkfile')
    status_code, result = touch_file(account_name, fs_name, dir_name, file_name, access_token)
    if status_code == 201:
        with open(local_file_name, 'rb') as local_file:
            path = f"{dir_name}/{file_name}"
            content = local_file.read()
            position = 0
            append_file(account_name, fs_name, path, content, position, access_token)
            position = len(content)
            flush_file(account_name, fs_name, path, position, access_token)
    else:
        print(result)


if __name__ == '__main__':
    tenant_id = '<your tenant id>'
    client_id = '<your client id>'
    client_secret = '<your client secret>'

    account_name = '<your adls account name>'
    fs_name = '<your filesystem name>'
    dir_name = '<your directory name>'
    file_name = '<your file name>'
    local_file_name = '<your local file name>'

    # Acquire an Access token
    auth_status_code, auth_result = auth(tenant_id, client_id, client_secret)
    access_token = auth_status_code == 200 and auth_result['access_token'] or ''
    print(access_token)

    # Create a filesystem
    mkfs_status_code, mkfs_result = mkfs(account_name, fs_name, access_token)
    print(mkfs_status_code, mkfs_result)

    # Create a directory
    mkdir_status_code, mkdir_result = mkdir(account_name, fs_name, dir_name, access_token)
    print(mkdir_status_code, mkdir_result)

    # Create a file from local file
    mkfile(account_name, fs_name, dir_name, file_name, local_file_name, access_token)


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Azure ADLS Gen2 not available

Azure ADLS Gen2 not available


By : koops
Date : March 29 2020, 07:55 AM
will be helpful for those in need You can now specifiy that you want to use a hierarchical namespace at the creation of the storage account (via the portal in the advanced tab).
At the time the question has been raised it was in a gated preview, see the following documentation. You had to fill out a preview survey to get your subscription whitelisted for this feature.
Timeline for availablity of azure search indexing on ADLS Gen2

Timeline for availablity of azure search indexing on ADLS Gen2


By : SomeshMudgal
Date : March 29 2020, 07:55 AM
will be helpful for those in need It is correct that we do not currently support ADLS Gen2 as a source for our Azure Search indexer. This is in the works, however we do not have a timeline I can provide yet.
In the meantime, you can use our PUSH api to programmatically send content from it to Azure Search.
Will Azure Data Lake Analytics support ADLS Gen2?

Will Azure Data Lake Analytics support ADLS Gen2?


By : Fred125
Date : March 29 2020, 07:55 AM
will be helpful for those in need 1.As of now, ADLA does not support ADLS Gen2, there is already a user voice here. You can upvote for it.
2.For ADLS Gen1 will be discounted or not, there is a link about this as following:
Intermittent HTTP error when loading files from ADLS Gen2 in Azure Databricks

Intermittent HTTP error when loading files from ADLS Gen2 in Azure Databricks


By : user3066030
Date : December 24 2020, 06:01 AM
I wish did fix the issue. This has been resolved now. The underlying issue was due to a change at Microsoft end. This is the RCA I got from Microsoft Support:
There was a storage configuration that is turned on incorrectly during the latest storage tenant upgrade. This type of error would only show up for the namespace enabled account on the latest upgraded tenant. The mitigation for this issue is to turn off the configuration on the specific tenant, and we had kicked off the super sonic configuration rollout for the all the tenants. We have since added additional Storage upgrade validation for ADLS Gen 2 to help cover this type of scenario.
Azure Data Factory: Using ORC file as source or sink in data flow with ADLS gen2?

Azure Data Factory: Using ORC file as source or sink in data flow with ADLS gen2?


By : user3571069
Date : March 29 2020, 07:55 AM
Hope this helps Data Flow doesn't support ORC format file now.
You could reference the doucument Supported source connectors in mapping data flow:
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