| title | description | services | documentationcenter | author | manager | ms.reviewer | ms.service | ms.workload | ms.topic | ms.date | ms.author |
|---|---|---|---|---|---|---|---|---|---|---|---|
Copy data by using the Azure Copy Data tool | Microsoft Docs |
Create an Azure data factory and then use the Copy Data tool to copy data from one location in Azure Blob storage to another location. |
data-factory |
linda33wj |
craigg |
douglasl |
data-factory |
data-services |
quickstart |
06/20/2018 |
jingwang |
[!div class="op_single_selector" title1="Select the version of Data Factory service that you are using:"]
In this quickstart, you use the Azure portal to create a data factory. Then, you use the Copy Data tool to create a pipeline that copies data from a folder in Azure Blob storage to another folder.
Note
If you are new to Azure Data Factory, see Introduction to Azure Data Factory before doing this quickstart.
[!INCLUDE data-factory-quickstart-prerequisites]
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Select New on the left menu, select Data + Analytics, and then select Data Factory.
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On the New data factory page, enter ADFTutorialDataFactory for Name.
The name of the Azure data factory must be globally unique. If you see the following error, change the name of the data factory (for example, <yourname>ADFTutorialDataFactory) and try creating again. For naming rules for Data Factory artifacts, see the Data Factory - naming rules article.
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For Subscription, select your Azure subscription in which you want to create the data factory.
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For Resource Group, use one of the following steps:
- Select Use existing, and select an existing resource group from the list.
- Select Create new, and enter the name of a resource group.
To learn about resource groups, see Using resource groups to manage your Azure resources.
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For Version, select V2.
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For Location, select the location for the data factory.
The list shows only locations that Data Factory supports, and where your Azure Data Factory meta data will be stored. Please note that the associated data stores (like Azure Storage and Azure SQL Database) and computes (like Azure HDInsight) that Data Factory uses can run in other regions.
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Select Create.
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After the creation is complete, you see the Data Factory page. Select the Author & Monitor tile to start the Azure Data Factory user interface (UI) application on a separate tab.
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On the Let's get started page, select the Copy Data tile to start the Copy Data tool.
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On the Properties page of the Copy Data tool, you can specify a name for the pipeline and its description, then select Next.
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On the Source data store page, complete the following steps:
a. Click + Create new connection to add a connection.
b. Select Azure Blob Storage from the gallery, and then select Next.
c. On the Specify the Azure Blob storage account page, select your storage account from the Storage account name list, and then select Finish.
d. Select the newly created linked service as source, then click Next.
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On the Choose the input file or folder page, complete the following steps:
a. Click Browse to navigate to the adftutorial/input folder, select the emp.txt file, then click Choose.
d. Check the Binary copy option to copy file as-is, then select Next.
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On the Destination data store page, select the Azure Blob Storage linked service you just created, and then select Next.
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On the Choose the output file or folder page, enter adftutorial/output for the folder path, then select Next.
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On the Settings page, select Next to use the default configurations.
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On the Summary page, review all settings, and select Next.
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On the Deployment complete page, select Monitor to monitor the pipeline that you created.
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The application switches to the Monitor tab. You see the status of the pipeline on this tab. Select Refresh to refresh the list.
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Select the View Activity Runs link in the Actions column. The pipeline has only one activity of type Copy.
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To view details about the copy operation, select the Details (eyeglasses image) link in the Actions column. For details about the properties, see Copy Activity overview.
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Verify that the emp.txt file is created in the output folder of the adftutorial container. If the output folder does not exist, the Data Factory service automatically creates it.
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Switch to the Author tab above the Monitor tab on the left panel so that you can edit linked services, datasets, and pipelines. To learn about editing them in the Data Factory UI, see Create a data factory by using the Azure portal.
The pipeline in this sample copies data from one location to another location in Azure Blob storage. To learn about using Data Factory in more scenarios, go through the tutorials.