Dropna doesn't work for struct columns

import pyspark.sql.functions as F

df = spark.createDataFrame([(5, 80, 'Alice'), (10, None, 'Bob'), (15, 80, None)], schema=['age', 'height', 'name'])
df.show()
+---+------+-----+
|age|height| name|
+---+------+-----+
|  5|    80|Alice|
| 10|  null|  Bob|
| 15|    80| null|
+---+------+-----+

# this works just fine
df.dropna(subset=['name']).show()
+---+------+-----+
|age|height| name|
+---+------+-----+
|  5|    80|Alice|
| 10|  null|  Bob|
+---+------+-----+

# now add a struct column
df_with_struct = df.withColumn('struct_col', F.struct('age', 'height', 'name'))
df_with_struct.show(truncate=False)
+---+------+-----+--------------+
|age|height|name |struct_col    |
+---+------+-----+--------------+
|5  |80    |Alice|[5, 80, Alice]|
|10 |null  |Bob  |[10,, Bob]    |
|15 |80    |null |[15, 80,]     |
+---+------+-----+--------------+

# now dropna drops the whole dataframe when you use struct_col
df_with_struct.dropna(subset=['struct_col.name']).show(truncate=False)
+---+------+----+----------+
|age|height|name|struct_col|
+---+------+----+----------+
+---+------+----+----------+

df_with_struct.dropna(subset=['struct_col.name']).show(truncate=False)
+---+------+-----+--------------+
|age|height|name |struct_col    |
+---+------+-----+--------------+
|5  |80    |Alice|[5, 80, Alice]|
|10 |null  |Bob  |[10,, Bob]    |
+---+------+-----+--------------+