how to update nested column value with spark

[panda403]

Query engine

use spark with iceberg

Question

here is my iceberg table root |-- partition_time: long (nullable = true) |-- base: struct (nullable = true) | |-- report_time_ms: long (nullable = true) | |-- dev_info: struct (nullable = true) | | |-- env: string (nullable = true) | | |-- user: string (nullable = true) | | |-- pwd: string (nullable = true) | |-- com_info: struct (nullable = true) ........... i want to update colum base.dev_info.env's value to 'prod'，when i use df.withColumn("new_env", F.when(F.col("type") === 1, "").otherwise(F.col("base.dev_info.env"))) the new_env's value is correct but when i use df.withColumn("base.dev_info.env", F.when(F.col("type") === 1, "").otherwise(F.col("base.dev_info.env"))) , the base.dev_info.env has no change it seems spark cant identify the nested column, how to update nested column value with spark?