how to i able to read column mapping metadata for delta tables

[sher]

i want to read column mapping metadata

https://github.com/delta-io/delta/blob/master/PROTOCOL.md#column-mapping

in above link we can able to find the code block with json data. the same data i want to read in pyspark.. is there any option to read that metadata from databricks please let me know

below code block i want to read for my delta tables

{
    "name" : "e",
    "type" : {
      "type" : "array",
      "elementType" : {
        "type" : "struct",
        "fields" : [ {
          "name" : "d",
          "type" : "integer",
          "nullable" : false,
          "metadata" : { 
            "delta.columnMapping.id": 5,
            "delta.columnMapping.physicalName": "col-a7f4159c-53be-4cb0-b81a-f7e5240cfc49"
          }
        } ]
      },
      "containsNull" : true
    },
    "nullable" : true,
    "metadata" : { 
      "delta.columnMapping.id": 4,
      "delta.columnMapping.physicalName": "col-5f422f40-de70-45b2-88ab-1d5c90e94db1"
    }
  }

[brockb]

Hi,

Information about the delta table such as history information could be found by running a `describe history table_name`. A `rename column` operation could be found in the `operation` column with a value of `RENAME COLUMN`. 

If you then look at the corresponding delta transaction json file in the table's `_delta_log` directory, you will find the details. For example, if the column rename occurred in Delta version 1, you could go to the `<tableLocation>/_delta_log/00000000000000000001.json` file for the details.

You could read this json file with `spark.read.json(path)`. Much of the data of interest to you would be in the  `metaData.schemaString` column.

I hope this helps.

[sher]

thanks