I am trying to parse, flatten the nested data using pyspark. any suggestion on how to parse such json file

Here is sample code tried so far, but was not successful.

jsonData ="""{
    "data": {
        "unique_id1": {
            "random_code1": {
                "name": "some_name",
                "status": "value1"
            },
            "random_code2": {
                "name": "some_name",
                "status": "value2"
            }
        },
        "unique_id2": {
            "random_code3": {
                "name": "some_name",
                "status": "value2"
            },
            "random_code4": {
                "name": "some_name",
                "status": "value2"
            }
        }
    }

}"""
df = spark.read.option("multiLine", "true").json(spark.sparkContext.parallelize([jsonData]))

data_schema = df.schema["data"].dataType.simpleString()
data_schema  = re.sub(r"([w-]+)(?=:struct<name)", "_RandomCode", data_schema)
data_schema  = re.sub(r"([w-]+)(?=:struct<_RandomCode)", "_Ids", data_schema)
data_schema = re.sub(r"(?<=,|<)([^,<]+)(?=:)", r"`1`", data_schema)

Expected output

_Ids              _RandomCode              name
unique_id1         random_code1            some_name
unique_id1         random_code2            some_name

unique_id2         random_code3            some_name
unique_id2         random_code4            some_name