【发布时间】:2019-02-02 14:20:45
【问题描述】:
在 Azure DataFactory 管道中,我尝试让两个 CopyActivities 按顺序运行,即第一个将数据从 blob 复制到 SQL 表,然后第二个将 SQL 表复制到另一个数据库。
我尝试了下面的代码,但结果管道不依赖于活动(从工作流程图和 JSON 在 Azure UI 中检查)。当我运行管道时,我收到如下错误消息: “ErrorResponseException:模板验证失败:'模板操作'我的第二个活动 nameScope' 在第 '1' 行和列 '22521' 的 'runAfter' 属性包含不存在的操作。balababla ....” em>
在 Azure UI 中手动添加依赖项后,我可以成功运行管道。
如果有人能指出示例代码 (Python/C#/Powershell) 或文档,我将不胜感激。 我的 Python 代码:
def createDataFactoryRectStage(self,
aPipelineName, aActivityStageName, aActivityAcquireName,
aRectFileName, aRectDSName,
aStageTableName, aStageDSName,
aAcquireTableName, aAcquireDSName):
adf_client = self.__getAdfClient()
ds_blob = AzureBlobDataset(linked_service_name = LinkedServiceReference(AZURE_DATAFACTORY_LS_BLOB_RECT),
folder_path=PRJ_AZURE_BLOB_PATH_RECT,
file_name = aRectFileName,
format = {"type": "TextFormat",
"columnDelimiter": ",",
"rowDelimiter": "",
"nullValue": "\\N",
"treatEmptyAsNull": "true",
"firstRowAsHeader": "true",
"quoteChar": "\"",})
adf_client.datasets.create_or_update(AZURE_RESOURCE_GROUP, AZURE_DATAFACTORY, aRectDSName, ds_blob)
ds_stage= AzureSqlTableDataset(linked_service_name = LinkedServiceReference(AZURE_DATAFACTORY_LS_SQLDB_STAGE),
table_name='[dbo].[' + aStageTableName + ']')
adf_client.datasets.create_or_update(AZURE_RESOURCE_GROUP, AZURE_DATAFACTORY, aStageDSName, ds_stage)
ca_blob_to_stage = CopyActivity(aActivityStageName,
inputs=[DatasetReference(aRectDSName)],
outputs=[DatasetReference(aStageDSName)],
source= BlobSource(),
sink= SqlSink(write_batch_size = AZURE_SQL_WRITE_BATCH_SIZE))
ds_acquire= AzureSqlTableDataset(linked_service_name = LinkedServiceReference(AZURE_DATAFACTORY_LS_SQLDB_ACQUIRE),
table_name='[dbo].[' + aAcquireTableName + ']')
adf_client.datasets.create_or_update(AZURE_RESOURCE_GROUP, AZURE_DATAFACTORY, aAcquireDSName, ds_acquire)
dep = ActivityDependency(ca_blob_to_stage, dependency_conditions =[DependencyCondition('Succeeded')])
ca_stage_to_acquire = CopyActivity(aActivityAcquireName,
inputs=[DatasetReference(aStageDSName)],
outputs=[DatasetReference(aAcquireDSName)],
source= SqlSource(),
sink= SqlSink(write_batch_size = AZURE_SQL_WRITE_BATCH_SIZE),
depends_on=[dep])
p_obj = PipelineResource(activities=[ca_blob_to_stage, ca_stage_to_acquire], parameters={})
return adf_client.pipelines.create_or_update(AZURE_RESOURCE_GROUP, AZURE_DATAFACTORY, aPipelineName, p_obj)
【问题讨论】:
标签: python dependencies azure-data-factory