title: Copy data in Blob Storage using Azure Data Factory | Microsoft Docs description: Create an Azure data factory to copy data from one location in Azure Blob storage to another location. services: data-factory documentationcenter: '' author: linda33wj manager: craigg ms.reviewer: douglasl

ms.service: data-factory ms.workload: data-services ms.tgt_pltfrm: ms.devlang: powershell ms.topic: quickstart ms.date: 01/22/2018 ms.author: jingwang

Create an Azure data factory using PowerShell

[!div class="op_single_selector" title1="Select the version of Data Factory service you are using:"]

Version 1

Current version

This quickstart describes how to use PowerShell to create an Azure data factory. The pipeline you create in this data factory copies data from one folder to another folder in an Azure blob storage. For a tutorial on how to transform data using Azure Data Factory, see Tutorial: Transform data using Spark.

Note

This article does not provide a detailed introduction of the Data Factory service. For an introduction to the Azure Data Factory service, see Introduction to Azure Data Factory.

[!INCLUDE data-factory-quickstart-prerequisites]

Azure PowerShell

Install the latest Azure PowerShell modules by following instructions in How to install and configure Azure PowerShell.

Log in to PowerShell

Launch PowerShell on your machine. Keep PowerShell open until the end of this quickstart. If you close and reopen, you need to run these commands again.
Run the following command, and enter the same Azure user name and password that you use to sign in to the Azure portal:
```
Connect-AzureRmAccount
```
Run the following command to view all the subscriptions for this account:
```
Get-AzureRmSubscription
```
If you see multiple subscriptions associated with your account, run the following command to select the subscription that you want to work with. Replace SubscriptionId with the ID of your Azure subscription:
```
Select-AzureRmSubscription -SubscriptionId "<SubscriptionId>"   	
```

Create a data factory

Define a variable for the resource group name that you use in PowerShell commands later. Copy the following command text to PowerShell, specify a name for the Azure resource group in double quotes, and then run the command. For example: "ADFQuickStartRG".
```
$resourceGroupName = "ADFQuickStartRG";
```
If the resource group already exists, you may not want to overwrite it. Assign a different value to the $ResourceGroupName variable and run the command again
To create the Azure resource group, run the following command:
```
$ResGrp = New-AzureRmResourceGroup $resourceGroupName -location 'East US'
```
If the resource group already exists, you may not want to overwrite it. Assign a different value to the $ResourceGroupName variable and run the command again.
Define a variable for the data factory name.

[!IMPORTANT] Update the data factory name to be globally unique. For example, ADFTutorialFactorySP1127.
```
$dataFactoryName = "ADFQuickStartFactory";
```
To create the data factory, run the following Set-AzureRmDataFactoryV2 cmdlet, using the Location and ResourceGroupName property from the $ResGrp variable:
```
$DataFactory = Set-AzureRmDataFactoryV2 -ResourceGroupName $ResGrp.ResourceGroupName -Location $ResGrp.Location -Name $dataFactoryName 
```

Note the following points:

The name of the Azure data factory must be globally unique. If you receive the following error, change the name and try again.
```
The specified Data Factory name 'ADFv2QuickStartDataFactory' is already in use. Data Factory names must be globally unique.
```
To create Data Factory instances, the user account you use to log in to Azure must be a member of contributor or owner roles, or an administrator of the Azure subscription.
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. The data stores (Azure Storage, Azure SQL Database, etc.) and computes (HDInsight, etc.) used by data factory can be in other regions.

Create a linked service

Create linked services in a data factory to link your data stores and compute services to the data factory. In this quickstart, you create an Azure Storage linked service that is used as both the source and sink stores. The linked service has the connection information that the Data Factory service uses at runtime to connect to it.

Create a JSON file named AzureStorageLinkedService.json in C:\ADFv2QuickStartPSH folder with the following content: (Create the folder ADFv2QuickStartPSH if it does not already exist.).

[!IMPORTANT] Replace <accountName> and <accountKey> with name and key of your Azure storage account before saving the file.
```
{
    "name": "AzureStorageLinkedService",
    "properties": {
        "type": "AzureStorage",
        "typeProperties": {
            "connectionString": {
                "value": "DefaultEndpointsProtocol=https;AccountName=<accountName>;AccountKey=<accountKey>;EndpointSuffix=core.windows.net",
                "type": "SecureString"
            }
        }
    }
}
```
If you are using Notepad, select All files for the Save as type filed in the Save as dialog box. Otherwise, it may add .txt extension to the file. For example, AzureStorageLinkedService.json.txt. If you create the file in File Explorer before opening it in Notepad, you may not see the .txt extension since the Hide extensions for known files types option is set by default. Remove the .txt extension before proceeding to the next step.
In PowerShell, switch to the ADFv2QuickStartPSH folder.
```
Set-Location 'C:\ADFv2QuickStartPSH'
```

Run the Set-AzureRmDataFactoryV2LinkedService cmdlet to create the linked service: AzureStorageLinkedService.

Set-AzureRmDataFactoryV2LinkedService -DataFactoryName $DataFactory.DataFactoryName -ResourceGroupName $ResGrp.ResourceGroupName -Name "AzureStorageLinkedService" -DefinitionFile ".\AzureStorageLinkedService.json"

Here is the sample output:

LinkedServiceName : AzureStorageLinkedService
ResourceGroupName : <resourceGroupName>
DataFactoryName   : <dataFactoryName>
Properties        : Microsoft.Azure.Management.DataFactory.Models.AzureStorageLinkedService

Create a dataset

In this step, you define a dataset that represents the data to copy from a source to a sink. The dataset is of type AzureBlob. It refers to the Azure Storage linked service you created in the previous step. It takes a parameter to construct the folderPath property. For an input dataset, the copy activity in the pipeline passes the input path as a value for this parameter. Similarly, for an output dataset, the copy activity passes the output path as a value for this parameter.

Create a JSON file named BlobDataset.json in the C:\ADFv2QuickStartPSH folder, with the following content:

{
    "name": "BlobDataset",
    "properties": {
        "type": "AzureBlob",
        "typeProperties": {
            "folderPath": "@{dataset().path}"
        },
        "linkedServiceName": {
            "referenceName": "AzureStorageLinkedService",
            "type": "LinkedServiceReference"
        },
        "parameters": {
            "path": {
                "type": "String"
            }
        }
    }
}

To create the dataset: BlobDataset, run the Set-AzureRmDataFactoryV2Dataset cmdlet.

Set-AzureRmDataFactoryV2Dataset -DataFactoryName $DataFactory.DataFactoryName -ResourceGroupName $ResGrp.ResourceGroupName -Name "BlobDataset" -DefinitionFile ".\BlobDataset.json"

Here is the sample output:

DatasetName       : BlobDataset
ResourceGroupName : <resourceGroupname>
DataFactoryName   : <dataFactoryName>
Structure         :
Properties        : Microsoft.Azure.Management.DataFactory.Models.AzureBlobDataset

Create a pipeline

In this quickstart, you create a pipeline with one activity that takes two parameters - input blob path and output blob path. The values for these parameters are set when the pipeline is triggered/run. The copy activity uses the same blob dataset created in the previous step as input and output. When the dataset is used as an input dataset, input path is specified. And, when the dataset is used as an output dataset, the output path is specified.

Create a JSON file named Adfv2QuickStartPipeline.json in the C:\ADFv2QuickStartPSH folder with the following content:

{
    "name": "Adfv2QuickStartPipeline",
    "properties": {
        "activities": [
            {
                "name": "CopyFromBlobToBlob",
                "type": "Copy",
                "inputs": [
                    {
                        "referenceName": "BlobDataset",
                        "parameters": {
                            "path": "@pipeline().parameters.inputPath"
                        },
                        "type": "DatasetReference"
                    }
                ],
                "outputs": [
                    {
                        "referenceName": "BlobDataset",
                        "parameters": {
                            "path": "@pipeline().parameters.outputPath"
                        },
                        "type": "DatasetReference"
                    }
                ],
                "typeProperties": {
                    "source": {
                        "type": "BlobSource"
                    },
                    "sink": {
                        "type": "BlobSink"
                    }
                }
            }
        ],
        "parameters": {
            "inputPath": {
                "type": "String"
            },
            "outputPath": {
                "type": "String"
            }
        }
    }
}

To create the pipeline: Adfv2QuickStartPipeline, Run the Set-AzureRmDataFactoryV2Pipeline cmdlet.

$DFPipeLine = Set-AzureRmDataFactoryV2Pipeline -DataFactoryName $DataFactory.DataFactoryName -ResourceGroupName $ResGrp.ResourceGroupName -Name "Adfv2QuickStartPipeline" -DefinitionFile ".\Adfv2QuickStartPipeline.json"

Create a pipeline run

In this step, you set values for the pipeline parameters: inputPath and outputPath with actual values of source and sink blob paths. Then, you create a pipeline run by using these arguments.

Create a JSON file named PipelineParameters.json in the C:\ADFv2QuickStartPSH folder with the following content:
```
{
    "inputPath": "adftutorial/input",
    "outputPath": "adftutorial/output"
}
```

Run the Invoke-AzureRmDataFactoryV2Pipeline cmdlet to create a pipeline run and pass in the parameter values. The cmdlet returns the pipeline run ID for future monitoring.

$RunId = Invoke-AzureRmDataFactoryV2Pipeline -DataFactoryName $DataFactory.DataFactoryName -ResourceGroupName $ResGrp.ResourceGroupName -PipelineName $DFPipeLine.Name -ParameterFile .\PipelineParameters.json

Monitor the pipeline run

Run the following PowerShell script to continuously check the pipeline run status until it finishes copying the data. Copy/paste the following script in the PowerShell window, and press ENTER.

while ($True) {
    $Run = Get-AzureRmDataFactoryV2PipelineRun -ResourceGroupName $ResGrp.ResourceGroupName -DataFactoryName $DataFactory.DataFactoryName -PipelineRunId $RunId

    if ($Run) {
        if ($run.Status -ne 'InProgress') {
            Write-Output ("Pipeline run finished. The status is: " +  $Run.Status)
            $Run
            break
        }
        Write-Output  "Pipeline is running...status: InProgress"
    }

    Start-Sleep -Seconds 10
}

Here is the sample output of pipeline run:

Pipeline is running...status: InProgress
Pipeline run finished. The status is:  Succeeded

ResourceGroupName : ADFTutorialResourceGroup
DataFactoryName   : SPTestFactory0928
RunId             : 0000000000-0000-0000-0000-0000000000000
PipelineName      : Adfv2QuickStartPipeline
LastUpdated       : 9/28/2017 8:28:38 PM
Parameters        : {[inputPath, adftutorial/input], [outputPath, adftutorial/output]}
RunStart          : 9/28/2017 8:28:14 PM
RunEnd            : 9/28/2017 8:28:38 PM
DurationInMs      : 24151
Status            : Succeeded
Message           :

If you see the error:

Activity CopyFromBlobToBlob failed: Failed to detect region of linked service 'AzureStorage' : 'AzureStorageLinkedService' with error '[Region Resolver] Azure Storage failed to get address for DNS. Warning: System.Net.Sockets.SocketException (0x80004005): No such host is known

do the following steps:

In the AzureStorageLinkedService.json, confirm that the name and key of your Azure Storage Account are correct.
Verify that the format of the connection string is correct. The properties, for example, AccountName and AccountKey are separated by semi-colon (;) character.
If you have angled brackets surrounding the account name and account key, remove them.

Here is an example connection string:

"connectionString": {
    "value": "DefaultEndpointsProtocol=https;AccountName=mystorageaccountname;AccountKey=mystorageacountkey;EndpointSuffix=core.windows.net",
    "type": "SecureString"
}

Recreate the linked service by following steps in the Create a linked service section.
Rerun the pipeline by following steps in the Create a pipeline run section.
Run the current monitoring command again to monitor the new pipeline run.

Run the following script to retrieve copy activity run details, for example, size of the data read/written.

Write-Output "Activity run details:"
$Result = Get-AzureRmDataFactoryV2ActivityRun -DataFactoryName $DataFactory.DataFactoryName -ResourceGroupName $ResGrp.ResourceGroupName -PipelineRunId $RunId -RunStartedAfter (Get-Date).AddMinutes(-30) -RunStartedBefore (Get-Date).AddMinutes(30)
$Result

Write-Output "Activity 'Output' section:"
$Result.Output -join "`r`n"

Write-Output "Activity 'Error' section:"
$Result.Error -join "`r`n"

Confirm that you see the output similar to the following sample output of activity run result:

ResourceGroupName : ADFTutorialResourceGroup
DataFactoryName   : SPTestFactory0928
ActivityName      : CopyFromBlobToBlob
PipelineRunId     : 00000000000-0000-0000-0000-000000000000
PipelineName      : Adfv2QuickStartPipeline
Input             : {source, sink}
Output            : {dataRead, dataWritten, copyDuration, throughput...}
LinkedServiceName :
ActivityRunStart  : 9/28/2017 8:28:18 PM
ActivityRunEnd    : 9/28/2017 8:28:36 PM
DurationInMs      : 18095
Status            : Succeeded
Error             : {errorCode, message, failureType, target}

Activity 'Output' section:
"dataRead": 38
"dataWritten": 38
"copyDuration": 7
"throughput": 0.01
"errors": []
"effectiveIntegrationRuntime": "DefaultIntegrationRuntime (West US)"
"usedDataIntegrationUnits": 2
"billedDuration": 14

[!INCLUDE data-factory-quickstart-verify-output-cleanup.md]

Next steps

The pipeline in this sample copies data from one location to another location in an Azure blob storage. Go through the tutorials to learn about using Data Factory in more scenarios.

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quickstart-create-data-factory-powershell.md

quickstart-create-data-factory-powershell.md

Create an Azure data factory using PowerShell

Azure PowerShell

Log in to PowerShell

Create a data factory

Create a linked service

Create a dataset

Create a pipeline

Create a pipeline run

Monitor the pipeline run

Next steps

Files

quickstart-create-data-factory-powershell.md

Latest commit

History

quickstart-create-data-factory-powershell.md

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Create an Azure data factory using PowerShell

Azure PowerShell

Log in to PowerShell

Create a data factory

Create a linked service

Create a dataset

Create a pipeline

Create a pipeline run

Monitor the pipeline run

Next steps