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control-flow-if-condition-activity.md

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title description services documentationcenter author manager ms.reviewer ms.service ms.workload ms.tgt_pltfrm ms.devlang ms.topic ms.date ms.author
If Condition activity in Azure Data Factory | Microsoft Docs
The If Condition activity allows you to control the processing flow based on a condition.
data-factory
sharonlo101
craigg
douglasl
data-factory
data-services
na
na
conceptual
01/10/2018
shlo

If Condition activity in Azure Data Factory

The If Condition activity provides the same functionality that an if statement provides in programming languages. It evaluates a set of activities when the condition evaluates to true and another set of activities when the condition evaluates to false.

Syntax

{
    "name": "<Name of the activity>",
    "type": "IfCondition",
    "typeProperties": {
		    "expression": {
            "value": "<expression that evaluates to true or false>",
            "type": "Expression"
		    },

		    "ifTrueActivities": [
            {
                "<Activity 1 definition>"
            },
            {
                "<Activity 2 definition>"
            },
            {
                "<Activity N definition>"
            }
        ],

        "ifFalseActivities": [
            {
                "<Activity 1 definition>"
            },
            {
                "<Activity 2 definition>"
            },
            {
                "<Activity N definition>"
            }
		    ]
    }
}

Type properties

Property Description Allowed values Required
name Name of the if-condition activity. String Yes
type Must be set to IfCondition String Yes
expression Expression that must evaluate to true or false Expression with result type boolean Yes
ifTrueActivities Set of activities that are executed when the expression evaluates to true. Array Yes
ifFalseActivities Set of activities that are executed when the expression evaluates to false. Array Yes

Example

The pipeline in this example copies data from an input folder to an output folder. The output folder is determined by the value of pipeline parameter: routeSelection. If the value of routeSelection is true, the data is copied to outputPath1. And, if the value of routeSelection is false, the data is copied to outputPath2.

Note

This section provides JSON definitions and sample PowerShell commands to run the pipeline. For a walkthrough with step-by-step instructions to create a Data Factory pipeline by using Azure PowerShell and JSON definitions, see tutorial: create a data factory by using Azure PowerShell.

Pipeline with IF-Condition activity (Adfv2QuickStartPipeline.json)

{
    "name": "Adfv2QuickStartPipeline",
    "properties": {
        "activities": [
            {
                "name": "MyIfCondition",
                "type": "IfCondition",
                "typeProperties": {
                    "expression":  {
                        "value":  "@bool(pipeline().parameters.routeSelection)", 
                        "type": "Expression"
                     },
                                           
                    "ifTrueActivities": [
                        {
                            "name": "CopyFromBlobToBlob1",
                            "type": "Copy",
                            "inputs": [
                                {
                                    "referenceName": "BlobDataset",
                                    "parameters": {
                                        "path": "@pipeline().parameters.inputPath"
                                    },
                                    "type": "DatasetReference"
                                }
                            ],
                            "outputs": [
                                {
                                    "referenceName": "BlobDataset",
                                    "parameters": {
                                        "path": "@pipeline().parameters.outputPath1"
                                    },
                                    "type": "DatasetReference"
                                }
                            ],
                            "typeProperties": {
                                "source": {
                                    "type": "BlobSource"
                                },
                                "sink": {
                                    "type": "BlobSink"
                                }
                            }
                        }                                   
                    ],
                    "ifFalseActivities": [
                        {
                            "name": "CopyFromBlobToBlob2",
                            "type": "Copy",
                            "inputs": [
                                {
                                    "referenceName": "BlobDataset",
                                    "parameters": {
                                        "path": "@pipeline().parameters.inputPath"
                                    },
                                    "type": "DatasetReference"
                                }
                            ],
                            "outputs": [
                                {
                                    "referenceName": "BlobDataset",
                                    "parameters": {
                                        "path": "@pipeline().parameters.outputPath2"
                                    },
                                    "type": "DatasetReference"
                                }
                            ],
                            "typeProperties": {
                                "source": {
                                    "type": "BlobSource"
                                },
                                "sink": {
                                    "type": "BlobSink"
                                }
                            }
                        }
                    ]                    
                }
            }
        ],
        "parameters": {
            "inputPath": {
                "type": "String"
            },
            "outputPath1": {
                "type": "String"
            },
            "outputPath2": {
                "type": "String"
            },
            "routeSelection": {
                "type": "String"
            }                        
        }
    }
}

Another example for expression is:

"expression":  {
    "value":  "@pipeline().parameters.routeSelection == 1", 
    "type": "Expression"
}

Azure Storage linked service (AzureStorageLinkedService.json)

{
    "name": "AzureStorageLinkedService",
    "properties": {
        "type": "AzureStorage",
        "typeProperties": {
            "connectionString": {
                "value": "DefaultEndpointsProtocol=https;AccountName=<Azure Storage account name>;AccountKey=<Azure Storage account key>",
                "type": "SecureString"
            }
        }
    }
}

Parameterized Azure Blob dataset (BlobDataset.json)

The pipeline sets the folderPath to the value of either outputPath1 or outputPath2 parameter of the pipeline.

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

Pipeline parameter JSON (PipelineParameters.json)

{
    "inputPath": "adftutorial/input",
    "outputPath1": "adftutorial/outputIf",
    "outputPath2": "adftutorial/outputElse",
    "routeSelection": "false"
}

PowerShell commands

These commands assume that you have saved the JSON files into the folder: C:\ADF.

Connect-AzureRmAccount
Select-AzureRmSubscription "<Your subscription name>"

$resourceGroupName = "<Resource Group Name>"
$dataFactoryName = "<Data Factory Name. Must be globally unique>";
Remove-AzureRmDataFactoryV2 $dataFactoryName -ResourceGroupName $resourceGroupName -force


Set-AzureRmDataFactoryV2 -ResourceGroupName $resourceGroupName -Location "East US" -Name $dataFactoryName
Set-AzureRmDataFactoryV2LinkedService -DataFactoryName $dataFactoryName -ResourceGroupName $resourceGroupName -Name "AzureStorageLinkedService" -DefinitionFile "C:\ADF\AzureStorageLinkedService.json"
Set-AzureRmDataFactoryV2Dataset -DataFactoryName $dataFactoryName -ResourceGroupName $resourceGroupName -Name "BlobDataset" -DefinitionFile "C:\ADF\BlobDataset.json"
Set-AzureRmDataFactoryV2Pipeline -DataFactoryName $dataFactoryName -ResourceGroupName $resourceGroupName -Name "Adfv2QuickStartPipeline" -DefinitionFile "C:\ADF\Adfv2QuickStartPipeline.json"
$runId = Invoke-AzureRmDataFactoryV2Pipeline -DataFactoryName $dataFactoryName -ResourceGroupName $resourceGroupName -PipelineName "Adfv2QuickStartPipeline" -ParameterFile C:\ADF\PipelineParameters.json
while ($True) {
    $run = Get-AzureRmDataFactoryV2PipelineRun -ResourceGroupName $resourceGroupName -DataFactoryName $DataFactoryName -PipelineRunId $runId

    if ($run) {
        if ($run.Status -ne 'InProgress') {
            Write-Host "Pipeline run finished. The status is: " $run.Status -foregroundcolor "Yellow"
            $run
            break
        }
        Write-Host  "Pipeline is running...status: InProgress" -foregroundcolor "Yellow"
    }

    Start-Sleep -Seconds 30
}
Write-Host "Activity run details:" -foregroundcolor "Yellow"
$result = Get-AzureRmDataFactoryV2ActivityRun -DataFactoryName $dataFactoryName -ResourceGroupName $resourceGroupName -PipelineRunId $runId -RunStartedAfter (Get-Date).AddMinutes(-30) -RunStartedBefore (Get-Date).AddMinutes(30)
$result

Write-Host "Activity 'Output' section:" -foregroundcolor "Yellow"
$result.Output -join "`r`n"

Write-Host "\nActivity 'Error' section:" -foregroundcolor "Yellow"
$result.Error -join "`r`n"

Next steps

See other control flow activities supported by Data Factory: