append to parquet file with column type changed corrupts fie

from pyspark.sql.functions import *
from pyspark.sql.types import *

fnBad = "dbfs:/tmp/richard.gooding@os.uk/test_bad_parquet/f1"
df = spark.createDataFrame( [ ["aaaa" ] ] ).select( col("_1").alias("aa") )
df.printSchema()

fmt = "parquet"

1. fmt = "delta"
   df.write.mode("overwrite").format( fmt ) .save( fnBad )
   df.show()

df = df.withColumn( "aa", struct( col("aa")) ) # change type of column - error on load
df.printSchema()
df.show()
df.write.mode("append").format( fmt).save( fnBad ) # format = delta :   "AnalysisException: Failed to merge fields 'aa' and 'aa'. Failed to merge incompatible data types StringType and StructType(StructField(aa,StringType,true))"

1. df.write.mode("append").option("mergeSchema", "true").format(fmt).save( fnBad ) # gives a different error, but only when dataframe read

print(" — at df 2 — ")
df2 = spark.read.format(fmt).load( fnBad )

1. df2 = spark.read.option("mergeSchema", "true").format(fmt).load( fnBad )
   df2.show()  # this will error -