快速入門：使用 REST API 建立 Azure Data Factory 和管線

發行項
05/15/2024

適用於：Azure Data Factory Azure Synapse Analytics

提示

試用 Microsoft Fabric 中的 Data Factory，這是適用於企業的全方位分析解決方案。 Microsoft Fabric 涵蓋從資料移動到資料科學、即時分析、商業智慧和報告的所有項目。了解如何免費開始新的試用！

Azure Data Factory 是雲端式資料整合服務，可讓您在雲端建立資料驅動工作流程，以便協調及自動進行資料移動和資料轉換。使用 Azure Data Factory，您可以建立和排程資料驅動工作流程 (稱為管線)，這類工作流程可以從不同資料存放區內嵌資料，使用計算服務 (例如 Azure HDInsight Hadoop、Spark、Azure Data Lake Analytics 和 Azure Machine Learning) 來處理/轉換資料，以及將輸出資料發佈至資料存放區 (例如 Azure Synapse Analytics)，以供商業智慧 (BI) 應用程式使用。

本快速入門描述如何使用 REST API 來建立 Azure Data Factory。在此資料處理站中的管線會將資料從 Azure Blob 儲存體中的一個位置複製到其他位置。

如果您沒有 Azure 訂用帳戶，請在開始前建立免費帳戶。

必要條件

注意

建議您使用 Azure Az PowerShell 模組來與 Azure 互動。若要開始使用，請參閱安裝 Azure PowerShell (部分機器翻譯)。若要了解如何移轉至 Az PowerShell 模組，請參閱將 Azure PowerShell 從 AzureRM 移轉至 Az。

Azure 訂用帳戶。如果您沒有訂用帳戶，則可以建立免費試用帳戶。
Azure 儲存體帳戶。您需要使用 Blob 儲存體作為來源和接收資料存放區。如果您沒有 Azure 儲存體帳戶，請參閱建立儲存體帳戶一文，按照步驟來建立帳戶。
在 Blob 儲存體中建立一個 Blob 容器，在容器中建立一個輸入資料夾，然後上傳一些檔案到資料夾中。您可以使用 Azure 儲存體總管之類的工具連線到 Azure Blob 儲存體，建立 Blob 容器，上傳輸入檔，以及驗證輸出檔。
安裝 Azure PowerShell。遵循如何安裝並設定 Azure PowerShell 中的指示。本快速入門會使用 PowerShell 來叫用 REST API 呼叫。
遵循此指示，在 Microsoft Entra ID 中建立應用程式。記下這些值，您在稍後的步驟中會用到：應用程式識別碼、clientSecrets 和租用戶識別碼。將應用程式指派給訂用帳戶或資源群組層級的「參與者」角色。

注意

針對主權雲端，您必須針對 ActiveDirectoryAuthority 和 ResourceManagerUrl (BaseUri) 使用適當的雲端專用端點。您可以透過執行「Get-AzEnvironment | Format-List」，使用 PowerShell 輕鬆地取得各種雲端的端點，其會傳回每個雲端環境的端點清單。

設定全域變數

啟動 PowerShell。保持開啟 Azure PowerShell，直到本快速入門結束為止。如果您關閉並重新開啟，則需要再次執行這些命令。

執行下列命令，並輸入您用來登入 Azure 入口網站的使用者名稱和密碼：
```
Connect-AzAccount
```
執行下列命令以檢視此帳戶的所有訂用帳戶：
```
Get-AzSubscription
```
執行下列命令以選取您要使用的訂用帳戶。以您的 Azure 訂用帳戶識別碼取代 SubscriptionId：
```
Select-AzSubscription -SubscriptionId "<SubscriptionId>"
```

以您自己的值使用取代預留位置後，請執行下列命令，以設定在稍後步驟中會用到的全域變數。

$tenantID = "<your tenant ID>"
$appId = "<your application ID>"
$clientSecrets = "<your clientSecrets for the application>"
$subscriptionId = "<your subscription ID to create the factory>"
$resourceGroupName = "<your resource group to create the factory>"
$factoryName = "<specify the name of data factory to create. It must be globally unique.>"
$apiVersion = "2018-06-01"

使用 Microsoft Entra 識別碼驗證

執行下列命令以驗證 Microsoft Entra ID：

$credentials = Get-Credential -UserName $appId
Connect-AzAccount -ServicePrincipal  -Credential $credentials -Tenant $tenantID

系統會提示您輸入密碼，並使用 clientSecrets 變數中的值。

如果您需要取得存取權杖


GetToken

建立資料處理站

執行以下命令以建立資料處理站：

$body = @"
{
    "location": "East US",
    "properties": {},
    "identity": {
        "type": "SystemAssigned"
    }
}
"@

$response =   Invoke-AzRestMethod -SubscriptionId ${subscriptionId}  -ResourceGroupName ${resourceGroupName} -ResourceProviderName  Microsoft.DataFactory -ResourceType "factories" -Name  ${factoryName} -ApiVersion ${apiVersion} -Method PUT -Payload ${body}
$response.Content

請注意下列幾點：

Azure Data Factory 的名稱在全域必須是唯一的。如果發生下列錯誤，請變更名稱，並再試一次。
```
Data factory name "ADFv2QuickStartDataFactory" is not available.
```
如需目前可使用 Data Factory 的 Azure 區域清單，請在下列頁面上選取您感興趣的區域，然後展開 [分析] 以找出 [Data Factory]：依區域提供的產品。資料處理站所使用的資料存放區 (Azure 儲存體、Azure SQL Database 等) 和計算 (HDInsight 等) 可位於其他區域。

以下是範例回應內容：


{  
    "name":"<dataFactoryName>",
    "identity":{  
        "type":"SystemAssigned",
        "principalId":"<service principal ID>",
        "tenantId":"<tenant ID>"
    },
    "id":"/subscriptions/<subscriptionId>/resourceGroups/<resourceGroupName>/providers/Microsoft.DataFactory/factories/<dataFactoryName>",
    "type":"Microsoft.DataFactory/factories",
    "properties":{  
        "provisioningState":"Succeeded",
        "createTime":"2019-09-03T02:10:27.056273Z",
        "version":"2018-06-01"
    },
    "eTag":"\"0200c876-0000-0100-0000-5d6dcb930000\"",
    "location":"East US",
    "tags":{  

    }
}

建立連結服務

您在資料處理站中建立的連結服務會將您的資料存放區和計算服務連結到資料處理站。在此快速入門中，您只需要建立一個 Azure 儲存體連結服務作為複製來源與接收存放區，在此範例中名為 "AzureStorageLinkedService"。

執行下列命令來建立名稱為 AzureStorageLinkedService 的連結服務：

執行命令前，以 Azure 儲存體帳戶的名稱和金鑰取代 <accountName> 和 <accountKey>。

$path = "/subscriptions/${subscriptionId}/resourceGroups/${resourceGroupName}/providers/Microsoft.DataFactory/factories/${factoryName}/linkedservices/AzureStorageLinkedService?api-version=${apiVersion}"

$body = @"
{  
    "name":"AzureStorageLinkedService",
    "properties":{  
        "annotations":[  

        ],
        "type":"AzureBlobStorage",
        "typeProperties":{  
            "connectionString":"DefaultEndpointsProtocol=https;AccountName=<accountName>;AccountKey=<accountKey>"
        }
    }
}
"@
$response =  Invoke-AzRestMethod  -Path ${path}  -Method PUT -Payload $body
$response.content

以下是範例輸出:

{  
    "id":"/subscriptions/<subscriptionId>/resourceGroups/<resourceGroupName>/providers/Microsoft.DataFactory/factories/<dataFactoryName>/linkedservices/AzureStorageLinkedService",
    "name":"AzureStorageLinkedService",
    "type":"Microsoft.DataFactory/factories/linkedservices",
    "properties":{  
        "annotations":[  

        ],
        "type":"AzureBlobStorage",
        "typeProperties":{  
            "connectionString":"DefaultEndpointsProtocol=https;AccountName=<accountName>;"
        }
    },
    "etag":"07011a57-0000-0100-0000-5d6e14a20000"
}

建立資料集

您可以定義資料集來代表要從來源複製到接收的資料。在此範例中，您會建立兩個資料集：InputDataset 和 OutputDataset。其會參考您在前一節中建立的 Azure 儲存體連結服務。輸入資料集代表輸入資料夾中的來源資料。在輸入資料集定義中，您可以指定 Blob 容器 (adftutorial)、資料夾 (input) 以及包含來源資料的檔案 (emp.txt)。輸出資料集代表複製到目的地的資料。在輸出資料集定義中，您可以指定 Blob 容器(adftutorial)、資料夾 (output)，以及資料複製到其中的檔案。

建立 InputDataset


$path = "/subscriptions/${subscriptionId}/resourceGroups/${resourceGroupName}/providers/Microsoft.DataFactory/factories/${factoryName}/datasets/InputDataset?api-version=${apiVersion}"

$body = @"
{  
    "name":"InputDataset",
    "properties":{  
        "linkedServiceName":{  
            "referenceName":"AzureStorageLinkedService",
            "type":"LinkedServiceReference"
        },
        "annotations":[  

        ],
        "type":"Binary",
        "typeProperties":{  
            "location":{  
                "type":"AzureBlobStorageLocation",
                "fileName":"emp.txt",
                "folderPath":"input",
                "container":"adftutorial"
            }
        }
    }
}
"@

$response =  Invoke-AzRestMethod  -Path ${path}  -Method PUT -Payload $body
$response

以下是範例輸出:

{  
    "id":"/subscriptions/<subscriptionId>/resourceGroups/<resourceGroupName>/providers/Microsoft.DataFactory/factories/<dataFactoryName>/datasets/InputDataset",
    "name":"InputDataset",
    "type":"Microsoft.DataFactory/factories/datasets",
    "properties":{  
        "linkedServiceName":{  
            "referenceName":"AzureStorageLinkedService",
            "type":"LinkedServiceReference"
        },
        "annotations":[  

        ],
        "type":"Binary",
        "typeProperties":{  
            "location":"@{type=AzureBlobStorageLocation; fileName=emp.txt; folderPath=input; container=adftutorial}"
        }
    },
    "etag":"07011c57-0000-0100-0000-5d6e14b40000"
}

建立 OutputDataset

$path = "/subscriptions/${subscriptionId}/resourceGroups/${resourceGroupName}/providers/Microsoft.DataFactory/factories/${factoryName}/datasets/OutputDataset?api-version=${apiVersion}"

$body = @"
{  
    "name":"OutputDataset",
    "properties":{  
        "linkedServiceName":{  
            "referenceName":"AzureStorageLinkedService",
            "type":"LinkedServiceReference"
        },
        "annotations":[  

        ],
        "type":"Binary",
        "typeProperties":{  
            "location":{  
                "type":"AzureBlobStorageLocation",
                "folderPath":"output",
                "container":"adftutorial"
            }
        }
    }
}
"@

$response =  Invoke-AzRestMethod  -Path ${path}  -Method PUT -Payload $body
$response.content

以下是範例輸出:

{  
    "id":"/subscriptions/<subscriptionId>/resourceGroups/<resourceGroupName>/providers/Microsoft.DataFactory/factories/<dataFactoryName>/datasets/OutputDataset",
    "name":"OutputDataset",
    "type":"Microsoft.DataFactory/factories/datasets",
    "properties":{  
        "linkedServiceName":{  
            "referenceName":"AzureStorageLinkedService",
            "type":"LinkedServiceReference"
        },
        "annotations":[  

        ],
        "type":"Binary",
        "typeProperties":{  
            "location":"@{type=AzureBlobStorageLocation; folderPath=output; container=adftutorial}"
        }
    },
    "etag":"07013257-0000-0100-0000-5d6e18920000"
}

建立新管線

在此範例中，此管線會包含一個複製活動。複製活動指的是在前一個步驟中建立為輸入和輸出的 "InputDataset" 和 "OutputDataset"。

$path = "/subscriptions/${subscriptionId}/resourceGroups/${resourceGroupName}/providers/Microsoft.DataFactory/factories/${factoryName}/pipelines/Adfv2QuickStartPipeline?api-version=${apiVersion}"

$body = @"
{
    "name": "Adfv2QuickStartPipeline",
    "properties": {
        "activities": [
            {
                "name": "CopyFromBlobToBlob",
                "type": "Copy",
                "dependsOn": [],
                "policy": {
                    "timeout": "7.00:00:00",
                    "retry": 0,
                    "retryIntervalInSeconds": 30,
                    "secureOutput": false,
                    "secureInput": false
                },
                "userProperties": [],
                "typeProperties": {
                    "source": {
                        "type": "BinarySource",
                        "storeSettings": {
                            "type": "AzureBlobStorageReadSettings",
                            "recursive": true
                        }
                    },
                    "sink": {
                        "type": "BinarySink",
                        "storeSettings": {
                            "type": "AzureBlobStorageWriteSettings"
                        }
                    },
                    "enableStaging": false
                },
                "inputs": [
                    {
                        "referenceName": "InputDataset",
                        "type": "DatasetReference"
                    }
                ],
                "outputs": [
                    {
                        "referenceName": "OutputDataset",
                        "type": "DatasetReference"
                    }
                ]
            }
        ],
        "annotations": []
    }
}
"@
$response =  Invoke-AzRestMethod  -Path ${path}  -Method PUT -Payload $body
$response.content

以下是範例輸出:

{  
    "id":"/subscriptions/<subscriptionId>/resourceGroups/<resourceGroupName>/providers/Microsoft.DataFactory/factories/<dataFactoryName>/pipelines/Adfv2QuickStartPipeline",
    "name":"Adfv2QuickStartPipeline",
    "type":"Microsoft.DataFactory/factories/pipelines",
    "properties":{  
        "activities":[  
            "@{name=CopyFromBlobToBlob; type=Copy; dependsOn=System.Object[]; policy=; userProperties=System.Object[]; typeProperties=; inputs=System.Object[]; outputs=System.Object[]}"
        ],
        "annotations":[  

        ]
    },
    "etag":"07012057-0000-0100-0000-5d6e14c00000"
}

建立管線執行

在此步驟中，您會觸發管線執行。回應主體中傳回的管線執行識別碼會在稍後的監視 API 中用到。

$path = "/subscriptions/${subscriptionId}/resourceGroups/${resourceGroupName}/providers/Microsoft.DataFactory/factories/${factoryName}/pipelines/Adfv2QuickStartPipeline/createRun?api-version=${apiVersion}"

$response =  Invoke-AzRestMethod  -Path ${path}  -Method POST 
$response.content

以下是範例輸出:

{  
    "runId":"04a2bb9a-71ea-4c31-b46e-75276b61bafc"
}

您也可以使用下列命令來取得 runId


($response.content | ConvertFrom-Json).runId

將管線參數化

您可以使用參數來建立管線。在下列範例中，我們會建立輸入資料集和輸出資料集，以取得輸入和輸出檔案名稱來作為提供給管線的參數。

建立參數化的輸入資料集

定義名為 strInputFileName 的參數，並以此作為資料集的檔案名稱。


$path = "/subscriptions/${subscriptionId}/resourceGroups/${resourceGroupName}/providers/Microsoft.DataFactory/factories/${factoryName}/datasets/ParamInputDataset?api-version=${apiVersion}"

$body = @"
{
    "name": "ParamInputDataset",
    "properties": {
        "linkedServiceName": {
            "referenceName": "AzureStorageLinkedService",
            "type": "LinkedServiceReference"
        },
        "parameters": {
            "strInputFileName": {
                "type": "string"
            }
        },
        "annotations": [],
        "type": "Binary",
        "typeProperties": {
            "location": {
                "type": "AzureBlobStorageLocation",
                "fileName": {
                    "value": "@dataset().strInputFileName",
                    "type": "Expression"
                },
                "folderPath": "input",
                "container": "adftutorial"
            }
        }
    },
    "type": "Microsoft.DataFactory/factories/datasets"
}
"@

$response =  Invoke-AzRestMethod  -Path ${path}  -Method PUT -Payload $body
$response.content

以下是範例輸出:

{
    "id": "/subscriptions/<subscriptionId>/resourceGroups/<resourceGroupName>/providers/Microsoft.DataFactory/factories/<factoryName>/datasets/ParamInputDataset",
    "name": "ParamInputDataset",
    "type": "Microsoft.DataFactory/factories/datasets",
    "properties": {
        "linkedServiceName": {
            "referenceName": "AzureStorageLinkedService",
            "type": "LinkedServiceReference"
        },
        "parameters": {
            "strInputFileName": {
                "type": "string"
            }
        },
        "annotations": [],
        "type": "Binary",
        "typeProperties": {
            "location": {
                "type": "AzureBlobStorageLocation",
                "fileName": {
                    "value": "@dataset().strInputFileName",
                    "type": "Expression"
                },
                "folderPath": "input",
                "container": "adftutorial"
            }
        }
    },
    "etag": "00000000-0000-0000-0000-000000000000"
}

建立參數化的輸出資料集

定義名為 strOutputFileName 的參數，並以此作為資料集的檔案名稱。



$path = "/subscriptions/${subscriptionId}/resourceGroups/${resourceGroupName}/providers/Microsoft.DataFactory/factories/${factoryName}/datasets/ParamOutputDataset?api-version=${apiVersion}"
$body = @"
{
    "name": "ParamOutputDataset",
    "properties": {
        "linkedServiceName": {
            "referenceName": "AzureStorageLinkedService",
            "type": "LinkedServiceReference"
        },
        "parameters": {
            "strOutPutFileName": {
                "type": "string"
            }
        },
        "annotations": [],
        "type": "Binary",
        "typeProperties": {
            "location": {
                "type": "AzureBlobStorageLocation",
                "fileName": {
                    "value": "@dataset().strOutPutFileName",
                    "type": "Expression"
                },
                "folderPath": "output",
                "container": "adftutorial"
            }
        }
    },
    "type": "Microsoft.DataFactory/factories/datasets"
}

"@

$response =  Invoke-AzRestMethod  -Path ${path}  -Method PUT -Payload $body
$response.content

以下是範例輸出:

{
    "id": "/subscriptions/<subscriptionId>/resourceGroups/<resourceGroupName>/providers/Microsoft.DataFactory/factories/<factoryName>/datasets/ParamOutputDataset",
    "name": "ParamOutputDataset",
    "type": "Microsoft.DataFactory/factories/datasets",
    "properties": {
        "linkedServiceName": {
            "referenceName": "AzureStorageLinkedService",
            "type": "LinkedServiceReference"
        },
        "parameters": {
            "strOutPutFileName": {
                "type": "string"
            }
        },
        "annotations": [],
        "type": "Binary",
        "typeProperties": {
            "location": {
                "type": "AzureBlobStorageLocation",
                "fileName": {
                    "value": "@dataset().strOutPutFileName",
                    "type": "Expression"
                },
                "folderPath": "output",
                "container": "adftutorial"
            }
        }
    },
    "etag": "00000000-0000-0000-0000-000000000000"
}

建立參數化管線

使用兩個管線層級參數來定義管線：strParamInputFileName 和 strParamOutputFileName。然後將這兩個參數連結至資料集的 strInputFileName 和 strOutputFileName 參數。


$path = "/subscriptions/${subscriptionId}/resourceGroups/${resourceGroupName}/providers/Microsoft.DataFactory/factories/${factoryName}/pipelines/Adfv2QuickStartParamPipeline?api-version=${apiVersion}"

$body = @"
{
    "name": "Adfv2QuickStartParamPipeline",
    "properties": {
        "activities": [
            {
                "name": "CopyFromBlobToBlob",
                "type": "Copy",
                "dependsOn": [],
                "policy": {
                    "timeout": "7.00:00:00",
                    "retry": 0,
                    "retryIntervalInSeconds": 30,
                    "secureOutput": false,
                    "secureInput": false
                },
                "userProperties": [],
                "typeProperties": {
                    "source": {
                        "type": "BinarySource",
                        "storeSettings": {
                            "type": "AzureBlobStorageReadSettings",
                            "recursive": true
                        }
                    },
                    "sink": {
                        "type": "BinarySink",
                        "storeSettings": {
                            "type": "AzureBlobStorageWriteSettings"
                        }
                    },
                    "enableStaging": false
                },
                "inputs": [
                    {
                        "referenceName": "ParamInputDataset",
                        "type": "DatasetReference",
                        "parameters": {
                            "strInputFileName": {
                                "value": "@pipeline().parameters.strParamInputFileName",
                                "type": "Expression"
                            }
                        }
                    }
                ],
                "outputs": [
                    {
                        "referenceName": "ParamOutputDataset",
                        "type": "DatasetReference",
                        "parameters": {
                            "strOutPutFileName": {
                                "value": "@pipeline().parameters.strParamOutputFileName",
                                "type": "Expression"
                            }
                        }
                    }
                ]
            }
        ],   

        "parameters": {
            "strParamInputFileName": {
              "type": "String"
            },
            "strParamOutputFileName": {
              "type": "String"
            }
          }
    }
}
"@

$response =  Invoke-AzRestMethod  -Path ${path}  -Method PUT -Payload $body
$response.content

以下是範例輸出:


{
    "id": "/subscriptions/<subscriptionId>/resourceGroups/<resourceGroupName>/providers/Microsoft.DataFactory/factories/<factoryName>/pipelines/Adfv2QuickStartParamPipeline",
    "name": "Adfv2QuickStartParamPipeline",
    "type": "Microsoft.DataFactory/factories/pipelines",
    "properties": {
        "activities": [
            {
                "name": "CopyFromBlobToBlob",
                "type": "Copy",
                "dependsOn": [],
                "policy": {
                    "timeout": "7.00:00:00",
                    "retry": 0,
                    "retryIntervalInSeconds": 30,
                    "secureOutput": false,
                    "secureInput": false
                },
                "userProperties": [],
                "typeProperties": {
                    "source": {
                        "type": "BinarySource",
                        "storeSettings": {
                            "type": "AzureBlobStorageReadSettings",
                            "recursive": true
                        }
                    },
                    "sink": {
                        "type": "BinarySink",
                        "storeSettings": {
                            "type": "AzureBlobStorageWriteSettings"
                        }
                    },
                    "enableStaging": false
                },
                "inputs": [
                    {
                        "referenceName": "ParamInputDataset",
                        "type": "DatasetReference",
                        "parameters": {
                            "strInputFileName": {
                                "value": "@pipeline().parameters.strParamInputFileName",
                                "type": "Expression"
                            }
                        }
                    }
                ],
                "outputs": [
                    {
                        "referenceName": "ParamOutputDataset",
                        "type": "DatasetReference",
                        "parameters": {
                            "strOutPutFileName": {
                                "value": "@pipeline().parameters.strParamOutputFileName",
                                "type": "Expression"
                            }
                        }
                    }
                ]
            }
        ],
        "parameters": {
            "strParamInputFileName": {
                "type": "String"
            },
            "strParamOutputFileName": {
                "type": "String"
            }
        }
    },
    "etag": "5e01918d-0000-0100-0000-60d569a90000"
}

使用參數來建立管線執行

您現在可以在建立管線執行時指定參數的值。


$path = "/subscriptions/${subscriptionId}/resourceGroups/${resourceGroupName}/providers/Microsoft.DataFactory/factories/${factoryName}/pipelines/Adfv2QuickStartParamPipeline/createRun?api-version=${apiVersion}"

$body = @"
{  
        "strParamInputFileName": "emp2.txt",
        "strParamOutputFileName": "aloha.txt"
}
"@

$response =  Invoke-AzRestMethod  -Path ${path}  -Method POST -Payload $body
$response.content
$runId  = ($response.content | ConvertFrom-Json).runId

以下是範例輸出:

{"runId":"aaaa0a0a-bb1b-cc2c-dd3d-eeeeee4e4e4e"}

監視管線

執行下列程式碼以持續檢查管線執行狀態，直到完成複製資料為止。

    $path = "/subscriptions/${subscriptionId}/resourceGroups/${resourceGroupName}/providers/Microsoft.DataFactory/factories/${factoryName}/pipelineruns/${runId}?api-version=${apiVersion}"


    while ($True) {

        $response =  Invoke-AzRestMethod  -Path ${path}  -Method GET 
        $response = $response.content | ConvertFrom-Json

        Write-Host  "Pipeline run status: " $response.Status -foregroundcolor "Yellow"

        if ( ($response.Status -eq "InProgress") -or ($response.Status -eq "Queued") -or ($response.Status -eq "In Progress") ) {
            Start-Sleep -Seconds 10
        }
        else {
            $response | ConvertTo-Json
            break
        }
    }

以下是範例輸出:

    {
      "id": "/subscriptions/<subscriptionId>/resourceGroups/<resourceGroupName>/providers/Microsoft.DataFactory/factories/<factoryName>/pipelineruns/aaaa0a0a-bb1b-cc2c-dd3d-eeeeee4e4e4e",
      "runId": "aaaa0a0a-bb1b-cc2c-dd3d-eeeeee4e4e4e",
      "debugRunId": null,
      "runGroupId": "aaaa0a0a-bb1b-cc2c-dd3d-eeeeee4e4e4e",
      "pipelineName": "Adfv2QuickStartParamPipeline",
      "parameters": {
        "strParamInputFileName": "emp2.txt",
        "strParamOutputFileName": "aloha.txt"
      },
      "invokedBy": {
        "id": "9c0275ed99994c18932317a325276544",
        "name": "Manual",
        "invokedByType": "Manual"
      },
      "runStart": "2021-06-25T05:34:06.8424413Z",
      "runEnd": "2021-06-25T05:34:13.2936585Z",
      "durationInMs": 6451,
      "status": "Succeeded",
      "message": "",
      "lastUpdated": "2021-06-25T05:34:13.2936585Z",
      "annotations": [],
      "runDimension": {},
      "isLatest": true
    }

執行下列指令碼來取出複製活動執行詳細資料，例如，讀取/寫入資料的大小。

     $path = "/subscriptions/${subscriptionId}/resourceGroups/${resourceGroupName}/providers/Microsoft.DataFactory/factories/${factoryName}/pipelineruns/${runId}/queryActivityruns?api-version=${apiVersion}"


    while ($True) {

        $response =  Invoke-AzRestMethod  -Path ${path}  -Method POST 
        $responseContent = $response.content | ConvertFrom-Json
        $responseContentValue = $responseContent.value

        Write-Host  "Activity run status: " $responseContentValue.Status -foregroundcolor "Yellow"

        if ( ($responseContentValue.Status -eq "InProgress") -or ($responseContentValue.Status -eq "Queued") -or ($responseContentValue.Status -eq "In Progress") ) {
            Start-Sleep -Seconds 10
        }
        else {
            $responseContentValue | ConvertTo-Json
            break
        }
    }

以下是範例輸出:

    {
      "activityRunEnd": "2021-06-25T05:34:11.9536764Z",
      "activityName": "CopyFromBlobToBlob",
      "activityRunStart": "2021-06-25T05:34:07.5161151Z",
      "activityType": "Copy",
      "durationInMs": 4437,
      "retryAttempt": null,
      "error": {
        "errorCode": "",
        "message": "",
        "failureType": "",
        "target": "CopyFromBlobToBlob",
        "details": ""
      },
      "activityRunId": "bbbb1b1b-cc2c-dd3d-ee4e-ffffff5f5f5f",
      "iterationHash": "",
      "input": {
        "source": {
          "type": "BinarySource",
          "storeSettings": "@{type=AzureBlobStorageReadSettings; recursive=True}"
        },
        "sink": {
          "type": "BinarySink",
          "storeSettings": "@{type=AzureBlobStorageWriteSettings}"
        },
        "enableStaging": false
      },
      "linkedServiceName": "",
      "output": {
        "dataRead": 134,
        "dataWritten": 134,
        "filesRead": 1,
        "filesWritten": 1,
        "sourcePeakConnections": 1,
        "sinkPeakConnections": 1,
        "copyDuration": 3,
        "throughput": 0.044,
        "errors": [],
        "effectiveIntegrationRuntime": "DefaultIntegrationRuntime (East US)",
        "usedDataIntegrationUnits": 4,
        "billingReference": {
          "activityType": "DataMovement",
          "billableDuration": ""
        },
        "usedParallelCopies": 1,
        "executionDetails": [
          "@{source=; sink=; status=Succeeded; start=06/25/2021 05:34:07; duration=3; usedDataIntegrationUnits=4; usedParallelCopies=1; profile=; detailedDurations=}"
        ],
        "dataConsistencyVerification": {
          "VerificationResult": "NotVerified"
        },
        "durationInQueue": {
          "integrationRuntimeQueue": 0
        }
      },
      "userProperties": {},
      "pipelineName": "Adfv2QuickStartParamPipeline",
      "pipelineRunId": "aaaa0a0a-bb1b-cc2c-dd3d-eeeeee4e4e4e",
      "status": "Succeeded",
      "recoveryStatus": "None",
      "integrationRuntimeNames": [
        "defaultintegrationruntime"
      ],
      "executionDetails": {
        "integrationRuntime": [
          "@{name=DefaultIntegrationRuntime; type=Managed; location=East US; nodes=}"
        ]
      },
      "id": "/subscriptions/<subscriptionId>/resourceGroups/<resourceGroupName>/providers/Microsoft.DataFactory/factories/<factoryName>/pipelineruns/aaaa0a0a-bb1b-cc2c-dd3d-eeeeee4e4e4e/activityruns/bbbb1b1b-cc2c-dd3d-ee4e-ffffff5f5f5f"
    }

驗證輸出

使用 Azure 儲存體總管來檢查檔案是否已從 "inputPath" 複製到 "outputPath" (如您在建立管線執行時所指定)。

清除資源

您有兩種方式可以清除您在本快速入門中建立的資源。您可以刪除 Azure 資源群組，其中包括資源群組中的所有資源。如果您想要讓其他資源保持不變，請僅刪除您在本教學課程中建立的資料處理站。

執行下列命令來刪除整個資源群組：

Remove-AzResourceGroup -ResourceGroupName $resourcegroupname

執行下列命令來僅刪除資料處理站：

Remove-AzDataFactoryV2 -Name "<NameOfYourDataFactory>" -ResourceGroupName "<NameOfResourceGroup>"

在此範例中的管線會將資料從 Azure Blob 儲存體中的一個位置複製到其他位置。瀏覽教學課程以了解使用 Data Factory 的更多案例。

共用方式為

快速入門：使用 REST API 建立 Azure Data Factory 和管線

必要條件

設定全域變數

使用 Microsoft Entra 識別碼驗證

建立資料處理站

建立連結服務

建立資料集

建立新管線

建立管線執行

將管線參數化

建立參數化的輸入資料集

建立參數化的輸出資料集

建立參數化管線

使用參數來建立管線執行

監視管線

驗證輸出

清除資源

意見反應

其他資源

共用方式為

快速入門：使用 REST API 建立 Azure Data Factory 和管線

必要條件

設定全域變數

使用 Microsoft Entra 識別碼驗證

建立資料處理站

建立連結服務

建立資料集

建立新管線

建立管線執行

將管線參數化

建立參數化的輸入資料集

建立參數化的輸出資料集

建立參數化管線

使用參數來建立管線執行

監視管線

驗證輸出

清除資源

相關內容

意見反應

其他資源