[SPARK-38185][SQL] Fix data incorrect if aggregate function is empty

### What changes were proposed in this pull request?

Add `aggregateExpressions.nonEmpty` check in `groupOnly` function.

### Why are the changes needed?

The group only condition should check if the aggregate expression is empty.

In DataFrame api, it is allowed to make a empty aggregations.

So the following query should return 1 rather than 0 because it's a global aggregate.
```scala
val emptyAgg = Map.empty[String, String]
spark.range(2).where("id > 2").agg(emptyAgg).limit(1).count
```

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

yes, bug fix

### How was this patch tested?

Add test

Closes #35490 from ulysses-you/SPARK-38185.

Authored-by: ulysses-you <[email protected]>
Signed-off-by: Wenchen Fan <[email protected]>

Author: ulysses-you

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicLogicalOperators.scala

@@ -984,7 +984,9 @@ case class Aggregate(
 
   // Whether this Aggregate operator is group only. For example: SELECT a, a FROM t GROUP BY a
   private[sql] def groupOnly: Boolean = {
-    aggregateExpressions.map {
+    // aggregateExpressions can be empty through Dateset.agg,
+    // so we should also check groupingExpressions is non empty
+    groupingExpressions.nonEmpty && aggregateExpressions.map {
       case Alias(child, _) => child
       case e => e
     }.forall(a => groupingExpressions.exists(g => a.semanticEquals(g)))

sql/core/src/test/scala/org/apache/spark/sql/DataFrameAggregateSuite.scala

@@ -1443,6 +1443,11 @@ class DataFrameAggregateSuite extends QueryTest
     val res = df.select($"d".cast("decimal(12, 2)").as("d")).agg(avg($"d").cast("string"))
     checkAnswer(res, Row("9999999999.990000"))
   }
+
+  test("SPARK-38185: Fix data incorrect if aggregate function is empty") {
+    val emptyAgg = Map.empty[String, String]
+    assert(spark.range(2).where("id > 2").agg(emptyAgg).limit(1).count == 1)
+  }
 }
 
 case class B(c: Option[Double])