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Azure Data Factory loading data into Data Lake Store but Column names is not reflecting in file RRS feed

  • Question

  • Hi All

    we have created ADF pipeline to load data from on premises Oracle to Data Lake store , when we are loading file in Data lake the column names are coming as 1,2,3 ....  instead name of the column .

    we have defined  Oracle Source Dataset 

        "name": "OracleTableDatasetSource",

        "properties": {
            "structure": [
                {
                    "name": "DSTRCT_CODE",
                    "type": "String"
                },
                {
                    "name": "STD_JOB_NO",
                    "type": "String"
                },

    we defined Data Lake Store Destination 

    {
        "name": "AzureDataLakeStoreOutput",
        "properties": {
            "structure": [
                {
                    "name": "DSTRCT_CODE",
                    "type": "String"
                },
                {
                    "name": "STD_JOB_NO",
                    "type": "String"
                }

    and Pipeline defined as 

    "translator": {
                            "type": "TabularTranslator",
                            "columnMappings": "DSTRCT_CODE: DSTRCT_CODE, STD_JOB_NO: STD_JOB_NO"

    Please let me know why we are not able to get column and is there any thing we need specify to get the column name in the output .


    Surendra Thota

    Wednesday, August 30, 2017 1:02 PM

Answers

  • You need to define the format properties to let him know what type of file you want and if you want to include headers.

    For example:

     "format": {
            "type": "TextFormat",
            "columnDelimiter": ",",
            "quoteChar": "\"",
            "firstRowAsHeader": true
          }

    Reference: https://docs.microsoft.com/en-us/azure/data-factory/data-factory-supported-file-and-compression-formats#text-format

    • Marked as answer by Surendra_Thota Friday, September 1, 2017 2:51 PM
    Friday, September 1, 2017 2:20 PM