【问题标题】:Importing ARM template for creating ADF resources not creating any导入用于创建 ADF 资源的 ARM 模板不创建任何
【发布时间】:2020-03-19 14:12:20
【问题描述】:

我是 ADF 和 ARM 的新手。我有一个空白的 Data Factory-v2(TestDataFactory-123Test),我想使用现有的 ADF(TestDataFactory-123) 填充它。我一步一步地按照官方文档Create a Resource Manager template for each environment 中提到的内容进行操作。部署显示成功,但我看不到任何内容。我使用门户中的“在编辑器中构建您自己的模板”选项来导入现有的 ARM 模板。我错过了什么吗?

下面是我通过“导出”TestDataFactory-123 的 ARM 得到的 ARM:

{
  "$schema": "http://schema.management.azure.com/schemas/2015-01-01/deploymentTemplate.json#",
  "contentVersion": "1.0.0.0",
  "parameters": {
    "factoryName": {
      "type": "string",
      "metadata": "Data Factory name",
      "defaultValue": "TestDataFactory-123"
    },
    "AzureBlobStorageLinkedService_connectionString": {
      "type": "secureString",
      "metadata": "Secure string for 'connectionString' of 'AzureBlobStorageLinkedService'",
      "defaultValue": "TestDataFactory-123"
    }
  },
  "variables": {
    "factoryId": "[concat('Microsoft.DataFactory/factories/', parameters('factoryName'))]"
  },
  "resources": [
    {
      "name": "[concat(parameters('factoryName'), '/AzureBlobStorageLinkedService')]",
      "type": "Microsoft.DataFactory/factories/linkedServices",
      "apiVersion": "2018-06-01",
      "properties": {
        "annotations": [],
        "type": "AzureBlobStorage",
        "typeProperties": {
          "connectionString": "[parameters('AzureBlobStorageLinkedService_connectionString')]"
        }
      },
      "dependsOn": []
    },
    {
      "name": "[concat(parameters('factoryName'), '/InputDataset')]",
      "type": "Microsoft.DataFactory/factories/datasets",
      "apiVersion": "2018-06-01",
      "properties": {
        "linkedServiceName": {
          "referenceName": "AzureBlobStorageLinkedService",
          "type": "LinkedServiceReference"
        },
        "annotations": [],
        "type": "Binary",
        "typeProperties": {
          "location": {
            "type": "AzureBlobStorageLocation",
            "fileName": "emp.txt",
            "folderPath": "input",
            "container": "adftutorial"
          }
        }
      },
      "dependsOn": [
        "[concat(variables('factoryId'), '/linkedServices/AzureBlobStorageLinkedService')]"
      ]
    },
    {
      "name": "[concat(parameters('factoryName'), '/OutputDataset')]",
      "type": "Microsoft.DataFactory/factories/datasets",
      "apiVersion": "2018-06-01",
      "properties": {
        "linkedServiceName": {
          "referenceName": "AzureBlobStorageLinkedService",
          "type": "LinkedServiceReference"
        },
        "annotations": [],
        "type": "Binary",
        "typeProperties": {
          "location": {
            "type": "AzureBlobStorageLocation",
            "folderPath": "output",
            "container": "adftutorial"
          }
        }
      },
      "dependsOn": [
        "[concat(variables('factoryId'), '/linkedServices/AzureBlobStorageLinkedService')]"
      ]
    },
    {
      "name": "[concat(parameters('factoryName'), '/CopyPipeline')]",
      "type": "Microsoft.DataFactory/factories/pipelines",
      "apiVersion": "2018-06-01",
      "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",
                "parameters": {}
              }
            ],
            "outputs": [
              {
                "referenceName": "OutputDataset",
                "type": "DatasetReference",
                "parameters": {}
              }
            ]
          }
        ],
        "annotations": []
      },
      "dependsOn": [
        "[concat(variables('factoryId'), '/datasets/InputDataset')]",
        "[concat(variables('factoryId'), '/datasets/OutputDataset')]"
      ]
    }
  ]
}

【问题讨论】:

  • 是否有任何部署错误?如果没有,它应该出现。通常需要一小段时间(可能需要 1 或 2 分钟)才能作为“数据工厂”的一部分出现。一段时间后点击“刷新”,它应该会出现。
  • 不,没有部署错误..是的,我等了几分钟然后刷新..但没有运气..这让我想,这可能是因为 arm_template 的任何问题。我正在上传的 json 文件?
  • 但是如果有问题通常会出现错误。还要确认一下,如果通过 UI 创建新的数据工厂没有问题吗?如果不是太长,您可以尝试在此处粘贴您的 sn-p,看看我们是否可以提供帮助?
  • @thebernardlim 我现在粘贴了整个 ARM..实际上它很小..我也做了一些小调整,资源现在按预期部署!我将在答案部分提供解决方法。无论如何,非常感谢!

标签: azure-data-factory azure-data-factory-2


【解决方案1】:

修复很简单,只需将“factoryName”参数的“defaultValue”替换为空数据工厂的名称即可。 'TestDataFactory-123Test' 而不是现有的'TestDataFactory-123'!此外,我将“AzureBlobStorageLinkedService_connectionString”参数的“defaultValue”替换为实际的连接字符串。

【讨论】:

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