uploading csv file from local computer via Azure Data Studio

Question

Hello, I am facing issues with uploading csv files from my local computer via Azure Data Studio . I have many columns in the table and Azure Data Studio maps them incorectly that the file is in the end not imported. I cannot check all the types of columns one by one and change them manually because the tables have too many. How can i properly set up the types of the columns?

Regards

Petra

Answer 1

@Petra Carrion
Uploading and importing CSV files in Azure Data Studio can sometimes be challenging, especially when dealing with tables that have numerous columns. The issue you're facing, where columns are being mapped incorrectly and causing the import to fail, could be due to inconsistent data types in your CSV file or differences between the data types in your CSV file and the target table.

To properly set up the types of columns during CSV import in Azure Data Studio, you can follow these steps:

Preview Data and Define Schema: When you're importing a CSV file, Azure Data Studio provides a preview of the data before the actual import process. In this preview step, you have the option to manually map the columns from the CSV to the columns in the target table. This is where you can specify the appropriate data types for each column.

Import Wizard: In the Import Wizard of Azure Data Studio, after you've selected the CSV file to import, you'll see a step that shows a preview of the data. This step allows you to adjust the data type mapping for each column. To set up the column types correctly without manually going through each column, you can utilize the "Advanced Editor" option.

1. Using Advanced Editor for Column Mapping: In the "Advanced Editor" option, you can define the data types for columns in bulk using a JSON-style mapping. This can be especially helpful when dealing with many columns. Here's an example of how the JSON-style mapping might look:

{
    "columnMappings": [
        { "source": "ColumnName1", "destination": "ColumnName1", "type": "nvarchar" },
        { "source": "ColumnName2", "destination": "ColumnName2", "type": "int" },
        // Repeat for other columns...
    ]
}

Verify and Execute: After setting up the column types through the Advanced Editor, review the settings to ensure everything is correct. Once you're satisfied, proceed with the import process.

Remember to make sure that the column names in your JSON-style mapping match the column names in both the CSV file and the target table. Additionally, ensure that the data types you're specifying are compatible with the actual data in your CSV file.

If your issue persists even after following these steps, you might want to consider cleaning and pre-processing your CSV data to ensure consistent data types before importing it into Azure Data Studio. This can help prevent mapping issues during the import process.