ueshin opened a new pull request, #40627:
URL: https://github.com/apache/spark/pull/40627
### What changes were proposed in this pull request?
Fix `DataFrame.collect` with null struct.
### Why are the changes needed?
There is a behavior difference when collecting `null` struct:
In Spark Connect:
```py
>>> df = spark.sql("values (1, struct('a' as x)), (2, struct(null as x)),
(null, null) as t(a, b)")
>>> df.printSchema()
root
|-- a: integer (nullable = true)
|-- b: struct (nullable = true)
| |-- x: string (nullable = true)
>>> df.show()
+----+------+
| a| b|
+----+------+
| 1| {a}|
| 2|{null}|
|null| null|
+----+------+
>>> df.collect()
[Row(a=1, b=Row(x='a')), Row(a=2, b=Row(x=None)), Row(a=None, b=<Row()>)]
```
whereas PySpark:
```py
>>> df.collect()
[Row(a=1, b=Row(x='a')), Row(a=2, b=Row(x=None)), Row(a=None, b=None)]
```
### Does this PR introduce _any_ user-facing change?
The behavior fix.
### How was this patch tested?
Added/modified the related tests.
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