Question

我想做的事

我尝试创建一个azure数据工厂管道，将文件从blob复制并粘贴到Blob或blob到数据湖。

我做了什么

我刚刚关注微软网站上的教程，我已经有了ADF和blob，所以我没有再创建它，我现在正在尝试创建一个Azure链接服务，所以我使用此代码：

function convertStringToCamelCase(str_original){
    var str = str_original.toLowerCase();
    return str.split(' ').map(function(item, index){
        return index !== 0 
            ? item.charAt(0).toUpperCase() + item.substr(1) 
            : item.charAt(0).toLowerCase() + item.substr(1);
    }).join('');

但是当我运行它时，我得到了这个错误：

# Create an Azure Storage linked service
ls_name = 'storageLinkedService'

# IMPORTANT: specify the name and key of your Azure Storage account.
storage_string = SecureString('DefaultEndpointsProtocol=https;AccountName=<storageaccountname>;AccountKey=<storageaccountkey>')

ls_azure_storage = AzureStorageLinkedService(connection_string=storage_string)
ls = adf_client.linked_services.create_or_update(rg_name, df_name, ls_name, ls_azure_storage)
print_item(ls)

我不知道为什么会收到此错误。有没有人有想法？

更新

我尝试跳过此步骤并尝试使用此命令在blob中创建和归档：Traceback (most recent call last): File "<ipython-input-173-cabc65dd11b9>", line 4, in <module> ls = adf_client.linked_services.create_or_update(rg_name, df_name, ls_name, ls_azure_storage) File "C:\ProgramData\Anaconda3\lib\site-packages\azure\mgmt\datafactory\operations\linked_services_operations.py", line 170, in create_or_update raise models.ErrorResponseException(self._deserialize, response) ErrorResponseException: Operation returned an invalid status code 'Not Found'

我得到了同样的错误adf_client.datasets.create_or_update(rg_name, df_name, ds_name, ds_azure_blob)，这让我觉得这个问题可能与blob有关。

Answer 1

我尝试重现您的问题，但失败了。

我没有ADF所以我按照官方教程创建了数据工厂和链接服务，没有发生错误。

主要功能

def main():

    # Azure subscription ID
    subscription_id = '***'

    # This program creates this resource group. If it's an existing resource group, comment out the code that creates the resource group
    rg_name = '***'

    # The data factory name. It must be globally unique.
    df_name = '***'

    # Specify your Active Directory client ID, client secret, and tenant ID
    credentials = ServicePrincipalCredentials(client_id='***', secret='***', tenant='***')
    resource_client = ResourceManagementClient(credentials, subscription_id)
    adf_client = DataFactoryManagementClient(credentials, subscription_id)

    rg_params = {'location':'eastus'}
    df_params = {'location':'eastus'}

    # create the resource group
    # comment out if the resource group already exits
     resource_client.resource_groups.create_or_update(rg_name, rg_params)

     Create a data factory
     df_resource = Factory(location='eastus')
     df = adf_client.factories.create_or_update(rg_name, df_name, df_resource)
     print_item(df)
     while df.provisioning_state != 'Succeeded':
         df = adf_client.factories.get(rg_name, df_name)
         time.sleep(1)

    # Create an Azure Storage linked service
    ls_name = 'storageLinkedService'

    # IMPORTANT: specify the name and key of your Azure Storage account.
    storage_string = SecureString('DefaultEndpointsProtocol=https;AccountName=***;AccountKey=***')

    ls_azure_storage = AzureStorageLinkedService(connection_string=storage_string)
    ls = adf_client.linked_services.create_or_update(rg_name, df_name, ls_name, ls_azure_storage)
    print_item(ls)