[SPARK-50489][SQL][PYTHON] Fix self-join after applyInArrow

### What changes were proposed in this pull request?
Fix self-join after `applyInArrow`, the same issue of `applyInPandas` was fixed in #31429

### Why are the changes needed?
bug fix

before:
```
In [1]: import pyarrow as pa

In [2]: df = spark.createDataFrame([(1, 1)], ("k", "v"))

In [3]: def arrow_func(key, table):
   ...:     return pa.Table.from_pydict({"x": [2], "y": [2]})
   ...:

In [4]: df2 = df.groupby("k").applyInArrow(arrow_func, schema="x long, y long")

In [5]: df2.show()
24/12/04 17:47:43 WARN CheckAllocator: More than one DefaultAllocationManager on classpath. Choosing first found
+---+---+
|  x|  y|
+---+---+
|  2|  2|
+---+---+

In [6]: df2.join(df2)
...
Failure when resolving conflicting references in Join:
'Join Inner
:- FlatMapGroupsInArrow [k#0L], arrow_func(k#0L, v#1L)#2, [x#3L, y#4L]
:  +- Project [k#0L, k#0L, v#1L]
:     +- LogicalRDD [k#0L, v#1L], false
+- FlatMapGroupsInArrow [k#12L], arrow_func(k#12L, v#13L)#2, [x#3L, y#4L]
   +- Project [k#12L, k#12L, v#13L]
      +- LogicalRDD [k#12L, v#13L], false

Conflicting attributes: "x", "y". SQLSTATE: XX000
	at org.apache.spark.SparkException$.internalError(SparkException.scala:92)
	at org.apache.spark.SparkException$.internalError(SparkException.scala:79)
	at org.apache.spark.sql.catalyst.analysis.CheckAnalysis.$anonfun$checkAnalysis0$2(CheckAnalysis.scala:798)
```

after:
```
In [6]: df2.join(df2)
Out[6]: DataFrame[x: bigint, y: bigint, x: bigint, y: bigint]

In [7]: df2.join(df2).show()
+---+---+---+---+
|  x|  y|  x|  y|
+---+---+---+---+
|  2|  2|  2|  2|
+---+---+---+---+
```

### Does this PR introduce _any_ user-facing change?
bug fix

### How was this patch tested?
added tests

### Was this patch authored or co-authored using generative AI tooling?
no

Closes #49056 from zhengruifeng/fix_arrow_join.

Authored-by: Ruifeng Zheng <ruifengz@apache.org>
Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>

Author: zhengruifeng

python/pyspark/sql/tests/test_arrow_cogrouped_map.py

@@ -299,6 +299,16 @@ def summarize(left, right):
             "+---------+------------+----------+-------------+\n",
         )
 
+    def test_self_join(self):
+        df = self.spark.createDataFrame([(1, 1)], ("k", "v"))
+
+        def arrow_func(key, left, right):
+            return pa.Table.from_pydict({"x": [2], "y": [2]})
+
+        df2 = df.groupby("k").cogroup(df.groupby("k")).applyInArrow(arrow_func, "x long, y long")
+
+        self.assertEqual(df2.join(df2).count(), 1)
+
 
 class CogroupedMapInArrowTests(CogroupedMapInArrowTestsMixin, ReusedSQLTestCase):
     @classmethod

python/pyspark/sql/tests/test_arrow_grouped_map.py

@@ -255,6 +255,16 @@ def foo(_):
                 self.assertEqual(r.a, "hi")
                 self.assertEqual(r.b, 1)
 
+    def test_self_join(self):
+        df = self.spark.createDataFrame([(1, 1)], ("k", "v"))
+
+        def arrow_func(key, table):
+            return pa.Table.from_pydict({"x": [2], "y": [2]})
+
+        df2 = df.groupby("k").applyInArrow(arrow_func, schema="x long, y long")
+
+        self.assertEqual(df2.join(df2).count(), 1)
+
 
 class GroupedMapInArrowTests(GroupedMapInArrowTestsMixin, ReusedSQLTestCase):
     @classmethod

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/DeduplicateRelations.scala

@@ -132,13 +132,27 @@ object DeduplicateRelations extends Rule[LogicalPlan] {
         _.output.map(_.exprId.id),
         newFlatMap => newFlatMap.copy(output = newFlatMap.output.map(_.newInstance())))
 
+    case f: FlatMapGroupsInArrow =>
+      deduplicateAndRenew[FlatMapGroupsInArrow](
+        existingRelations,
+        f,
+        _.output.map(_.exprId.id),
+        newFlatMap => newFlatMap.copy(output = newFlatMap.output.map(_.newInstance())))
+
     case f: FlatMapCoGroupsInPandas =>
       deduplicateAndRenew[FlatMapCoGroupsInPandas](
         existingRelations,
         f,
         _.output.map(_.exprId.id),
         newFlatMap => newFlatMap.copy(output = newFlatMap.output.map(_.newInstance())))
 
+    case f: FlatMapCoGroupsInArrow =>
+      deduplicateAndRenew[FlatMapCoGroupsInArrow](
+        existingRelations,
+        f,
+        _.output.map(_.exprId.id),
+        newFlatMap => newFlatMap.copy(output = newFlatMap.output.map(_.newInstance())))
+
     case m: MapInPandas =>
       deduplicateAndRenew[MapInPandas](
         existingRelations,