在ADFv2中,如果遇到列映射问题,可以通过使用数据流活动和映射数据流来解决。下面是一个包含代码示例的解决方法:
{
"name": "DataFlowActivity",
"type": "Microsoft.DataFactory/factories/pipelines/activities",
"dependsOn": [
{
"activity": "[concat('CopyActivity_', pipeline().parameters.inputDataset)]",
"dependencyConditions": [
"Succeeded"
]
}
],
"policy": {
"timeout": "7.00:00:00",
"retry": 0,
"retryIntervalInSeconds": 30,
"secureOutput": false
},
"userProperties": [],
"typeProperties": {
"streamingUnits": 1,
"dataflow": {
"referenceName": "MyDataFlow",
"type": "MappingDataFlow"
},
"source": {
"type": "DatasetReference",
"referenceName": "InputDataset"
},
"sink": {
"type": "DatasetReference",
"referenceName": "OutputDataset"
}
}
}
{
"name": "MyDataFlow",
"properties": {
"type": "MappingDataFlow",
"typeProperties": {
"sources": [
{
"dataset": {
"referenceName": "InputDataset",
"type": "DatasetReference"
},
"name": "Source"
}
],
"sinks": [
{
"dataset": {
"referenceName": "OutputDataset",
"type": "DatasetReference"
},
"name": "Sink"
}
],
"transformations": [
{
"name": "ColumnMapping",
"properties": {
"type": "Mapping",
"typeProperties": {
"source": {
"type": "TabularTranslator",
"mappings": [
{
"sourceColumnName": "SourceColumn1",
"sinkColumnName": "SinkColumn1"
},
{
"sourceColumnName": "SourceColumn2",
"sinkColumnName": "SinkColumn2"
},
...
]
},
"sink": {
"type": "TabularTranslator"
}
}
}
}
]
}
}
}
以上示例中,我们假设有两个输入列(SourceColumn1和SourceColumn2)和两个输出列(SinkColumn1和SinkColumn2)。你可以根据你的实际需求,添加或修改列映射规则。
请注意,示例代码中的数据集(InputDataset和OutputDataset)需要根据你的实际情况进行替换。
这是ADFv2中解决列映射问题的一个基本方法,你可以根据实际需求进行修改和扩展。