How to rename a column when creating an external table in Athena based on Parquet files in S3? - hive

Question

Does anybody know how to rename a column when creating an external table in Athena based on Parquet files in S3?
The Parquet files I'm trying to load have both a column named export_date as well as an export_date partition in the s3 structure.
An example file path is: 's3://bucket_x/path/to/data/export_date=2020-08-01/platform=platform_a'
CREATE EXTERNAL TABLE `user_john_doe.new_table`(
`column_1` string,
`export_date` DATE,
`column_3` DATE,
`column_4` bigint,
`column_5` string)
PARTITIONED BY (
`export_date` string,
`platform` string)
ROW FORMAT SERDE
'org.apache.hadoop.hive.ql.io.parquet.serde.ParquetHiveSerDe'
LOCATION
's3://bucket_x/path/to/data'
TBLPROPERTIES (
'parquet.compression'='GZIP')
;
So what I would like to do, is to rename the export_date column to export_date_exp. The AWS documentation indicates that:
To make Parquet read by index, which will allow you to rename
columns, you must create a table with parquet.column.index.access
SerDe property set to true.
https://docs.amazonaws.cn/en_us/athena/latest/ug/handling-schema-updates-chapter.html#parquet-read-by-name
But the following code does not load any data in the export_date_exp column:
CREATE EXTERNAL TABLE `user_john_doe.new_table`(
`column_1` string,
`export_date_exp` DATE,
`column_3` DATE,
`column_4` bigint,
`column_5` string)
PARTITIONED BY (
`export_date` string,
`platform` string)
ROW FORMAT SERDE
'org.apache.hadoop.hive.ql.io.parquet.serde.ParquetHiveSerDe'
WITH SERDEPROPERTIES ( 'parquet.column.index.access'='true')
LOCATION
's3://bucket_x/path/to/data'
TBLPROPERTIES (
'parquet.compression'='GZIP')
;
This question has been asked already, but did not receive an answer:
How to rename AWS Athena columns with parquet file source?
I am asking again because the documentation explicitly says it is possible.
As a side note: in my particular use case I can just not load the export_date column, as I've learned that reading Parquet by name does not require you to load every column. In my case I don't need the export_date column, so this avoids the conflict with the partition name.