快速入门：使用 .NET SDK 创建数据工厂和管道Quickstart: Create a data factory and pipeline using .NET SDK

适用于：是 Azure 数据工厂否 Azure Synapse Analytics（预览版）APPLIES TO: yesAzure Data Factory noAzure Synapse Analytics (Preview)

此快速入门介绍了如何使用 .NET SDK 创建一个 Azure 数据工厂。This quickstart describes how to use .NET SDK to create an Azure data factory. 在此数据工厂中创建的管道会将数据从 Azure Blob 存储中的一个文件夹复制到另一个文件夹。The pipeline you create in this data factory copies data from one folder to another folder in an Azure blob storage. 有关如何使用 Azure 数据工厂转换数据的教程，请参阅教程：使用 Spark 转换数据。For a tutorial on how to transform data using Azure Data Factory, see Tutorial: Transform data using Spark.

Note

本文不提供数据工厂服务的详细介绍。This article does not provide a detailed introduction of the Data Factory service. 有关 Azure 数据工厂服务的介绍，请参阅 Azure 数据工厂简介。For an introduction to the Azure Data Factory service, see Introduction to Azure Data Factory.

先决条件Prerequisites

Azure 订阅Azure subscription

如果没有 Azure 订阅，可在开始前创建一个 1 元人民币试用帐户。If you don't have an Azure subscription, create a 1rmb trial account before you begin.

Azure 角色Azure roles

若要创建数据工厂实例，用于登录到 Azure 的用户帐户必须属于参与者或所有者角色，或者是 Azure 订阅的管理员。 To create Data Factory instances, the user account that you use to sign in to Azure must be a member of the contributor or owner role, or an administrator of the Azure subscription. 若要查看你在订阅中拥有的权限，请转到 Azure 门户，在右上角选择你的用户名，然后选择“...” 图标以显示更多选项，然后选择“我的权限” 。To view the permissions that you have in the subscription, go to the Azure portal, select your username in the upper-right corner, select "..." icon for more options, and then select My permissions. 如果可以访问多个订阅，请选择相应的订阅。If you have access to multiple subscriptions, select the appropriate subscription.

若要为数据工厂创建和管理子资源（包括数据集、链接服务、管道、触发器和集成运行时），以下要求适用：To create and manage child resources for Data Factory - including datasets, linked services, pipelines, triggers, and integration runtimes - the following requirements are applicable:

  • 若要在 Azure 门户中创建和管理子资源，你必须属于资源组级别或更高级别的数据工厂参与者角色。To create and manage child resources in the Azure portal, you must belong to the Data Factory Contributor role at the resource group level or above.
  • 若要使用 PowerShell 或 SDK 创建和管理子资源，资源级别或更高级别的参与者角色已足够。To create and manage child resources with PowerShell or the SDK, the contributor role at the resource level or above is sufficient.

有关如何将用户添加到角色的示例说明，请参阅添加角色一文。For sample instructions about how to add a user to a role, see the Add roles article.

有关详细信息，请参阅以下文章：For more info, see the following articles:

Azure 存储帐户Azure Storage account

在本快速入门中，使用常规用途的 Azure 存储帐户（具体的说就是 Blob 存储）作为源 和目标 数据存储。You use a general-purpose Azure Storage account (specifically Blob storage) as both source and destination data stores in this quickstart. 如果没有常规用途的 Azure 存储帐户，请参阅创建存储帐户创建一个。If you don't have a general-purpose Azure Storage account, see Create a storage account to create one.

获取存储帐户名称Get the storage account name

在本快速入门中，将需要 Azure 存储帐户的名称。You will need the name of your Azure Storage account for this quickstart. 以下过程提供的步骤用于获取存储帐户的名称：The following procedure provides steps to get the name of your storage account:

  1. 在 Web 浏览器中，转到 Azure 门户并使用你的 Azure 用户名和密码登录。In a web browser, go to the Azure portal and sign in using your Azure username and password.
  2. 从 Azure 门户菜单中，选择“所有服务”，然后选择“存储” > “存储帐户” 。From the Azure portal menu, select All services, then select Storage > Storage accounts. 此外，也可以在任何页面中搜索和选择“存储帐户” 。You can also search for and select Storage accounts from any page.
  3. 在“存储帐户”页中，筛选你的存储帐户（如果需要），然后选择它 。In the Storage accounts page, filter for your storage account (if needed), and then select your storage account.

此外，也可以在任何页面中搜索和选择“存储帐户” 。You can also search for and select Storage accounts from any page.

创建 Blob 容器Create a blob container

本部分介绍如何在 Azure Blob 存储中创建名为 adftutorial 的 Blob 容器。In this section, you create a blob container named adftutorial in Azure Blob storage.

  1. 在“存储帐户”页上，选择“概述” > “容器”。 From the storage account page, select Overview > Containers.

  2. 在 <Account name> - “容器”页的工具栏中，选择“容器” 。On the <Account name> - Containers page's toolbar, select Container.

  3. 在“新建容器” 对话框中，输入 adftutorial 作为名称，然后选择“确定” 。In the New container dialog box, enter adftutorial for the name, and then select OK. <Account name> - “容器”页已更新为在容器列表中包含“adftutorial” 。The <Account name> - Containers page is updated to include adftutorial in the list of containers.

    容器列表

为 Blob 容器添加输入文件夹和文件Add an input folder and file for the blob container

在此部分中，在刚创建的容器中创建名为“input”的文件夹，再将示例文件上传到 input 文件夹 。In this section, you create a folder named input in the container you just created, and then upload a sample file to the input folder. 在开始之前，打开文本编辑器（如记事本），并创建包含以下内容的名为“emp.txt”的文件 ：Before you begin, open a text editor such as Notepad, and create a file named emp.txt with the following content:

John, Doe
Jane, Doe

将此文件保存在 C:\ADFv2QuickStartPSH 文件夹中 。Save the file in the C:\ADFv2QuickStartPSH folder. （如果此文件夹不存在，则创建它。）然后返回到 Azure 门户并执行以下步骤：(If the folder doesn't already exist, create it.) Then return to the Azure portal and follow these steps:

  1. 在上次离开的 <Account name> - “容器”页中，选择已更新的容器列表中的“adftutorial” 。In the <Account name> - Containers page where you left off, select adftutorial from the updated list of containers.

    1. 如果关闭了窗口或转到其他页，请再次登录到 Azure 门户。If you closed the window or went to another page, sign in to the Azure portal again.
    2. 从 Azure 门户菜单中，选择“所有服务”，然后选择“存储” > “存储帐户” 。From the Azure portal menu, select All services, then select Storage > Storage accounts. 此外，也可以在任何页面中搜索和选择“存储帐户” 。You can also search for and select Storage accounts from any page.
    3. 选择存储帐户，然后选择“容器” > “adftutorial” 。Select your storage account, and then select Containers > adftutorial.

  2. 在“adftutorial”容器页面的工具栏上，选择“上传” 。On the adftutorial container page's toolbar, select Upload.

  3. 在“上传 Blob”页中，选择“文件”框，然后浏览到 emp.txt 文件并进行选择 。In the Upload blob page, select the Files box, and then browse to and select the emp.txt file.

  4. 展开“高级”标题 。Expand the Advanced heading. 此页现在显示如下内容：The page now displays as shown:

    选择“高级...”链接

  5. 在“上传到文件夹”框中，输入“输入” 。In the Upload to folder box, enter input.

  6. 选择“上传”按钮 。Select the Upload button. 应该会在列表中看到 emp.txt 文件和上传状态。You should see the emp.txt file and the status of the upload in the list.

  7. 选择“关闭”图标 (X) 以关闭“上传 Blob”页面 。Select the Close icon (an X) to close the Upload blob page.

让“adftutorial”容器页面保持打开状态 。Keep the adftutorial container page open. 在本快速入门结束时可以使用它来验证输出。You use it to verify the output at the end of this quickstart.

Visual StudioVisual Studio

本文中的演练使用 Visual Studio 2019。The walkthrough in this article uses Visual Studio 2019. Visual Studio 2013、2015 或 2017 的过程略有不同。The procedures for Visual Studio 2013, 2015, or 2017 differ slightly.

Azure .NET SDKAzure .NET SDK

在计算机上下载并安装 Azure .NET SDK。Download and install Azure .NET SDK on your machine.

在 Azure Active Directory 中创建应用程序Create an application in Azure Active Directory

从“如何： 使用门户创建可访问资源的 Azure AD 应用程序和服务主体”中的各部分开始，按照说明执行以下任务：From the sections in How to: Use the portal to create an Azure AD application and service principal that can access resources, follow the instructions to do these tasks:

  1. 在创建 Azure Active Directory 应用程序中，创建一个应用程序来表示正在本教程中创建的 .NET 应用程序。In Create an Azure Active Directory application, create an application that represents the .NET application you are creating in this tutorial. 对于登录 URL，可以提供虚拟 URL，如本文中所示 (https://contoso.org/exampleapp)。For the sign-on URL, you can provide a dummy URL as shown in the article (https://contoso.org/exampleapp).
  2. 在获取用于登录的值中，获取应用程序 ID 和租户 ID，并记下这些值，稍后要在本教程中使用它们 。In Get values for signing in, get the application ID and tenant ID, and note down these values that you use later in this tutorial.
  3. 在证书与机密中，获取身份验证密钥，并记此值，稍后要在本教程中使用它 。In Certificates and secrets, get the authentication key, and note down this value that you use later in this tutorial.
  4. 在将应用程序分配给角色中，在订阅级别将应用程序分配到“参与者”角色，让该应用程序可以在订阅中创建数据工厂 。In Assign the application to a role, assign the application to the Contributor role at the subscription level so that the application can create data factories in the subscription.

创建 Visual Studio 项目Create a Visual Studio project

接下来，在 Visual Studio 中创建 C# 控制台应用程序：Next, create a C# .NET console application in Visual Studio:

  1. 启动 Visual Studio。Launch Visual Studio.
  2. 在“开始”窗口中，选择“创建新项目” > “控制台应用(.NET Framework)” 。In the Start window, select Create a new project > Console App (.NET Framework). 需要 .NET 4.5.2 或更高版本。.NET version 4.5.2 or above is required.
  3. 在“项目名称”中，输入 ADFv2QuickStart 。In Project name, enter ADFv2QuickStart.
  4. 选择“创建” 来创建项目。Select Create to create the project.

安装 NuGet 包Install NuGet packages

  1. 选择“工具” > “NuGet 包管理器” > “包管理器控制台” 。Select Tools > NuGet Package Manager > Package Manager Console.

  2. 在“包管理器控制台”窗格中，运行以下命令来安装包 。In the Package Manager Console pane, run the following commands to install packages. 有关详细信息，请参阅 Microsoft.Azure.Management.DataFactory NuGet 包。For more information, see the Microsoft.Azure.Management.DataFactory nuget package.

    Install-Package Microsoft.Azure.Management.DataFactory
Install-Package Microsoft.Azure.Management.ResourceManager -IncludePrerelease
Install-Package Microsoft.IdentityModel.Clients.ActiveDirectory

创建数据工厂客户端Create a data factory client

  1. 打开 Program.cs，包括以下语句来添加对命名空间的引用。Open Program.cs, include the following statements to add references to namespaces.

    using System;
using System.Collections.Generic;
using System.Linq;
using Microsoft.Rest;
using Microsoft.Azure.Management.ResourceManager;
using Microsoft.Azure.Management.DataFactory;
using Microsoft.Azure.Management.DataFactory.Models;
using Microsoft.IdentityModel.Clients.ActiveDirectory;

  2. 将以下代码添加到 Main 方法以设置变量。Add the following code to the Main method that sets the variables. 将占位符替换为自己的值。Replace the placeholders with your own values. 若要查看目前提供数据工厂的 Azure 区域的列表，请在以下页面上选择感兴趣的区域，然后展开“分析” 以找到“数据工厂” ：可用产品(按区域)。For a list of Azure regions in which Data Factory is currently available, select the regions that interest you on the following page, and then expand Analytics to locate Data Factory: Products available by region. 数据工厂使用的数据存储（Azure 存储、Azure SQL 数据库等）和计算资源（HDInsight 等）可以位于其他区域中。The data stores (Azure Storage, Azure SQL Database, and more) and computes (HDInsight and others) used by data factory can be in other regions.

    // Set variables
string tenantID = "<your tenant ID>";
string applicationId = "<your application ID>";
string authenticationKey = "<your authentication key for the application>";
string subscriptionId = "<your subscription ID where the data factory resides>";
string resourceGroup = "<your resource group where the data factory resides>";
string region = "<the location of your resource group>";
string dataFactoryName = 
    "<specify the name of data factory to create. It must be globally unique.>";
string storageAccount = "<your storage account name to copy data>";
string storageKey = "<your storage account key>";
// specify the container and input folder from which all files 
// need to be copied to the output folder. 
string inputBlobPath =
    "<path to existing blob(s) to copy data from, e.g. containername/inputdir>";
//specify the contains and output folder where the files are copied
string outputBlobPath =
    "<the blob path to copy data to, e.g. containername/outputdir>";

// name of the Azure Storage linked service, blob dataset, and the pipeline
string storageLinkedServiceName = "AzureStorageLinkedService";
string blobDatasetName = "BlobDataset";
string pipelineName = "Adfv2QuickStartPipeline";

  3. 在 Main 方法中添加用于创建 DataFactoryManagementClient 类的实例的以下代码。Add the following code to the Main method that creates an instance of DataFactoryManagementClient class. 将使用此对象创建数据工厂、链接服务、数据集以及管道。You use this object to create a data factory, a linked service, datasets, and a pipeline. 还将使用此对象来监视管道运行详细信息。You also use this object to monitor the pipeline run details.

    // Authenticate and create a data factory management client
var context = new AuthenticationContext("https://login.chinacloudapi.cn/" + tenantID);
ClientCredential cc = new ClientCredential(applicationId, authenticationKey);
AuthenticationResult result = context.AcquireTokenAsync(
    "https://management.chinacloudapi.cn/", cc).Result;
ServiceClientCredentials cred = new TokenCredentials(result.AccessToken);
var client = new DataFactoryManagementClient(cred) {
    SubscriptionId = subscriptionId , BaseUri = new Uri("https://management.chinacloudapi.cn/")};

创建数据工厂Create a data factory

向 Main 方法中添加用于创建数据工厂的以下代码。Add the following code to the Main method that creates a data factory.

// Create a data factory
Console.WriteLine("Creating data factory " + dataFactoryName + "...");
Factory dataFactory = new Factory
{
    Location = region,
    Identity = new FactoryIdentity()
};
client.Factories.CreateOrUpdate(resourceGroup, dataFactoryName, dataFactory);
Console.WriteLine(
    SafeJsonConvert.SerializeObject(dataFactory, client.SerializationSettings));

while (client.Factories.Get(resourceGroup, dataFactoryName).ProvisioningState ==
       "PendingCreation")
{
    System.Threading.Thread.Sleep(1000);
}

创建链接服务Create a linked service

在 Main 方法中添加用于创建 Azure 存储链接服务的以下代码。Add the following code to the Main method that creates an Azure Storage linked service.

可在数据工厂中创建链接服务，将数据存储和计算服务链接到数据工厂。You create linked services in a data factory to link your data stores and compute services to the data factory. 在此快速入门中，只需创建一个 Azure 存储链接服务，用于复制源和接收器存储。在示例中，此服务名为“AzureStorageLinkedService”。In this Quickstart, you only need to create one Azure Storage linked service for both the copy source and the sink store; it's named "AzureStorageLinkedService" in the sample.

// Create an Azure Storage linked service
Console.WriteLine("Creating linked service " + storageLinkedServiceName + "...");

LinkedServiceResource storageLinkedService = new LinkedServiceResource(
    new AzureStorageLinkedService
    {
        ConnectionString = new SecureString(
            "DefaultEndpointsProtocol=https;AccountName=" + storageAccount +
            ";AccountKey=" + storageKey +
            ";EndpointSuffix=core.chinacloudapi.cn")
    }
);
client.LinkedServices.CreateOrUpdate(
    resourceGroup, dataFactoryName, storageLinkedServiceName, storageLinkedService);
Console.WriteLine(SafeJsonConvert.SerializeObject(
    storageLinkedService, client.SerializationSettings));

创建数据集Create a dataset

向 Main 方法中添加用于创建 Azure blob 数据集的以下代码。Add the following code to the Main method that creates an Azure blob dataset.

定义一个数据集来表示要从源复制到接收器的数据。You define a dataset that represents the data to copy from a source to a sink. 在此示例中，此 Blob 数据集引用在上一步中创建的 Azure 存储链接服务。In this example, this Blob dataset references to the Azure Storage linked service you created in the previous step. 此数据集采用一个参数，其值在使用此数据集的活动中设置。The dataset takes a parameter whose value is set in an activity that consumes the dataset. 该参数用来构造“folderPath”，该项指向数据的驻留/存储位置。The parameter is used to construct the "folderPath" pointing to where the data resides/is stored.

// Create an Azure Blob dataset
Console.WriteLine("Creating dataset " + blobDatasetName + "...");
DatasetResource blobDataset = new DatasetResource(
    new AzureBlobDataset
    {
        LinkedServiceName = new LinkedServiceReference
        {
            ReferenceName = storageLinkedServiceName
        },
        FolderPath = new Expression { Value = "@{dataset().path}" },
        Parameters = new Dictionary<string, ParameterSpecification>
        {
            { "path", new ParameterSpecification { Type = ParameterType.String } }
        }
    }
);
client.Datasets.CreateOrUpdate(
    resourceGroup, dataFactoryName, blobDatasetName, blobDataset);
Console.WriteLine(
    SafeJsonConvert.SerializeObject(blobDataset, client.SerializationSettings));

创建管道Create a pipeline

向 Main 方法中添加用于创建包含复制活动的管道的以下代码。Add the following code to the Main method that creates a pipeline with a copy activity.

在此示例中，此管道包含一个活动并采用两个参数：输入 Blob 路径和输出 Blob 路径。In this example, this pipeline contains one activity and takes two parameters: the input blob path and the output blob path. 这些参数的值是在触发/运行管道时设置的。The values for these parameters are set when the pipeline is triggered/run. 复制活动引用在上一步中创建的同一 blob 数据集作为输入和输出。The copy activity refers to the same blob dataset created in the previous step as input and output. 当该数据集用作输入数据集时，即指定了输入路径。When the dataset is used as an input dataset, input path is specified. 并且，当该数据集用作输出数据集时，即指定了输出路径。And, when the dataset is used as an output dataset, the output path is specified.

// Create a pipeline with a copy activity
Console.WriteLine("Creating pipeline " + pipelineName + "...");
PipelineResource pipeline = new PipelineResource
{
    Parameters = new Dictionary<string, ParameterSpecification>
    {
        { "inputPath", new ParameterSpecification { Type = ParameterType.String } },
        { "outputPath", new ParameterSpecification { Type = ParameterType.String } }
    },
    Activities = new List<Activity>
    {
        new CopyActivity
        {
            Name = "CopyFromBlobToBlob",
            Inputs = new List<DatasetReference>
            {
                new DatasetReference()
                {
                    ReferenceName = blobDatasetName,
                    Parameters = new Dictionary<string, object>
                    {
                        { "path", "@pipeline().parameters.inputPath" }
                    }
                }
            },
            Outputs = new List<DatasetReference>
            {
                new DatasetReference
                {
                    ReferenceName = blobDatasetName,
                    Parameters = new Dictionary<string, object>
                    {
                        { "path", "@pipeline().parameters.outputPath" }
                    }
                }
            },
            Source = new BlobSource { },
            Sink = new BlobSink { }
        }
    }
};
client.Pipelines.CreateOrUpdate(resourceGroup, dataFactoryName, pipelineName, pipeline);
Console.WriteLine(SafeJsonConvert.SerializeObject(pipeline, client.SerializationSettings));

创建管道运行Create a pipeline run

在 Main 方法中添加用于触发管道运行的以下代码。Add the following code to the Main method that triggers a pipeline run.

此代码还设置 inputPath 和 outputPath 参数的值，这些值是使用源和接收器 Blob 路径的实际值在管道中指定的值 。This code also sets values of the inputPath and outputPath parameters specified in the pipeline with the actual values of the source and sink blob paths.

// Create a pipeline run
Console.WriteLine("Creating pipeline run...");
Dictionary<string, object> parameters = new Dictionary<string, object>
{
    { "inputPath", inputBlobPath },
    { "outputPath", outputBlobPath }
};
CreateRunResponse runResponse = client.Pipelines.CreateRunWithHttpMessagesAsync(
    resourceGroup, dataFactoryName, pipelineName, parameters: parameters
).Result.Body;
Console.WriteLine("Pipeline run ID: " + runResponse.RunId);

监视管道运行Monitor a pipeline run

  1. 在 Main 方法中添加以下代码用于持续检查状态，直到它完成数据复制为止。Add the following code to the Main method to continuously check the status until it finishes copying the data.

    // Monitor the pipeline run
Console.WriteLine("Checking pipeline run status...");
PipelineRun pipelineRun;
while (true)
{
    pipelineRun = client.PipelineRuns.Get(
        resourceGroup, dataFactoryName, runResponse.RunId);
    Console.WriteLine("Status: " + pipelineRun.Status);
    if (pipelineRun.Status == "InProgress" || pipelineRun.Status == "Queued")
        System.Threading.Thread.Sleep(15000);
    else
        break;
}

  2. 在 Main 方法中添加以下代码用于检索复制活动运行详细信息，例如，读取/写入的数据大小 。Add the following code to the Main method that retrieves copy activity run details, such as the size of the data that's read or written.

    // Check the copy activity run details
Console.WriteLine("Checking copy activity run details...");

RunFilterParameters filterParams = new RunFilterParameters(
    DateTime.UtcNow.AddMinutes(-10), DateTime.UtcNow.AddMinutes(10));
ActivityRunsQueryResponse queryResponse = client.ActivityRuns.QueryByPipelineRun(
    resourceGroup, dataFactoryName, runResponse.RunId, filterParams);
if (pipelineRun.Status == "Succeeded")
    Console.WriteLine(queryResponse.Value.First().Output);
else
    Console.WriteLine(queryResponse.Value.First().Error);
Console.WriteLine("\nPress any key to exit...");
Console.ReadKey();

运行代码Run the code

生成并启动应用程序，然后验证管道执行。Build and start the application, then verify the pipeline execution.

控制台会输出数据工厂、链接服务、数据集、管道和管道运行的创建进度。The console prints the progress of creating data factory, linked service, datasets, pipeline, and pipeline run. 然后，检查管道运行状态。It then checks the pipeline run status. 请等待，直至看到包含数据读取/写入大小的复制活动运行详细信息。Wait until you see the copy activity run details with the size of the read/write data. 然后，使用 Microsoft Azure 存储资源管理器等工具检查 Blob 是否已根据变量中的指定从“inputBlobPath”复制到“outputBlobPath”。Then use tools such as Azure Storage explorer to check the blob(s) is copied to "outputBlobPath" from "inputBlobPath" as you specified in the variables.

示例输出Sample output

Creating data factory SPv2Factory0907...
{
  "identity": {
    "type": "SystemAssigned"
  },
  "location": "China East 2"
}
Creating linked service AzureStorageLinkedService...
{
  "properties": {
    "type": "AzureStorage",
    "typeProperties": {
      "connectionString": {
        "value": "DefaultEndpointsProtocol=https;AccountName=<storageAccountName>;AccountKey=<storageAccountKey>;EndpointSuffix=core.chinacloudapi.cn",
        "type": "SecureString"
      }
    }
  }
}
Creating dataset BlobDataset...
{
  "properties": {
    "type": "AzureBlob",
    "typeProperties": {
      "folderPath": {
        "value": "@{dataset().path}",
        "type": "Expression"
      }
    },
    "linkedServiceName": {
      "referenceName": "AzureStorageLinkedService",
      "type": "LinkedServiceReference"
    },
    "parameters": {
      "path": {
        "type": "String"
      }
    }
  }
}
Creating pipeline Adfv2QuickStartPipeline...
{
  "properties": {
    "activities": [
      {
        "type": "Copy",
        "typeProperties": {
          "source": {
            "type": "BlobSource"
          },
          "sink": {
            "type": "BlobSink"
          }
        },
        "inputs": [
          {
            "referenceName": "BlobDataset",
            "parameters": {
              "path": "@pipeline().parameters.inputPath"
            },
            "type": "DatasetReference"
          }
        ],
        "outputs": [
          {
            "referenceName": "BlobDataset",
            "parameters": {
              "path": "@pipeline().parameters.outputPath"
            },
            "type": "DatasetReference"
          }
        ],
        "name": "CopyFromBlobToBlob"
      }
    ],
    "parameters": {
      "inputPath": {
        "type": "String"
      },
      "outputPath": {
        "type": "String"
      }
    }
  }
}
Creating pipeline run...
Pipeline run ID: 308d222d-3858-48b1-9e66-acd921feaa09
Checking pipeline run status...
Status: InProgress
Status: InProgress
Checking copy activity run details...
{
    "dataRead": 331452208,
    "dataWritten": 331452208,
    "copyDuration": 23,
    "throughput": 14073.209,
    "errors": [],
    "effectiveIntegrationRuntime": "DefaultIntegrationRuntime (China East 2)",
    "usedDataIntegrationUnits": 2,
    "billedDuration": 23
}

Press any key to exit...

验证输出Verify the output

该管道自动在 adftutorial Blob 容器中创建 output 文件夹 。The pipeline automatically creates the output folder in the adftutorial blob container. 然后，将 emp.txt 文件从 input 文件夹复制到 output 文件夹 。Then, it copies the emp.txt file from the input folder to the output folder.

  1. 在 Azure 门户中，在你在以上为 Blob 容器添加输入文件夹和文件部分中停留的 adftutorial 容器页上，选择“刷新”以查看输出文件夹 。In the Azure portal, on the adftutorial container page that you stopped at in the Add an input folder and file for the blob container section above, select Refresh to see the output folder.
  2. 在文件夹列表中，选择“output” 。In the folder list, select output.
  3. 确认 emp.txt 已复制到 output 文件夹。Confirm that the emp.txt is copied to the output folder.

清理资源Clean up resources

若要以编程方式删除数据工厂，请向程序中添加以下代码行：To programmatically delete the data factory, add the following lines of code to the program:

Console.WriteLine("Deleting the data factory");
client.Factories.Delete(resourceGroup, dataFactoryName);

后续步骤Next steps

此示例中的管道将数据从 Azure Blob 存储中的一个位置复制到另一个位置。The pipeline in this sample copies data from one location to another location in an Azure blob storage. 完成相关教程来了解如何在更多方案中使用数据工厂。Go through the tutorials to learn about using Data Factory in more scenarios.