[SPARK-34876][SQL] Fill defaultResult of non-nullable aggregates

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

Filled the `defaultResult` field on non-nullable aggregates

### Why are the changes needed?

The `defaultResult` defaults to `None` and in some situations (like correlated scalar subqueries) it is used for the value of the aggregation.

The UT result before the fix:
```
-- !query
SELECT t1a,
   (SELECT count(t2d) FROM t2 WHERE t2a = t1a) count_t2,
   (SELECT count_if(t2d > 0) FROM t2 WHERE t2a = t1a) count_if_t2,
   (SELECT approx_count_distinct(t2d) FROM t2 WHERE t2a = t1a) approx_count_distinct_t2,
   (SELECT collect_list(t2d) FROM t2 WHERE t2a = t1a) collect_list_t2,
   (SELECT collect_set(t2d) FROM t2 WHERE t2a = t1a) collect_set_t2,
    (SELECT hex(count_min_sketch(t2d, 0.5d, 0.5d, 1)) FROM t2 WHERE t2a = t1a) collect_set_t2
FROM t1
-- !query schema
struct<t1a:string,count_t2:bigint,count_if_t2:bigint,approx_count_distinct_t2:bigint,collect_list_t2:array<bigint>,collect_set_t2:array<bigint>,collect_set_t2:string>
-- !query output
val1a	0	0	NULL	NULL	NULL	NULL
val1a	0	0	NULL	NULL	NULL	NULL
val1a	0	0	NULL	NULL	NULL	NULL
val1a	0	0	NULL	NULL	NULL	NULL
val1b	6	6	3	[19,119,319,19,19,19]	[19,119,319]	0000000100000000000000060000000100000004000000005D8D6AB90000000000000000000000000000000400000000000000010000000000000001
val1c	2	2	2	[219,19]	[219,19]	0000000100000000000000020000000100000004000000005D8D6AB90000000000000000000000000000000100000000000000000000000000000001
val1d	0	0	NULL	NULL	NULL	NULL
val1d	0	0	NULL	NULL	NULL	NULL
val1d	0	0	NULL	NULL	NULL	NULL
val1e	1	1	1	[19]	[19]	0000000100000000000000010000000100000004000000005D8D6AB90000000000000000000000000000000100000000000000000000000000000000
val1e	1	1	1	[19]	[19]	0000000100000000000000010000000100000004000000005D8D6AB90000000000000000000000000000000100000000000000000000000000000000
val1e	1	1	1	[19]	[19]	0000000100000000000000010000000100000004000000005D8D6AB90000000000000000000000000000000100000000000000000000000000000000
```

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

Bugfix

### How was this patch tested?

UT

Closes #31973 from tanelk/SPARK-34876_non_nullable_agg_subquery.

Authored-by: Tanel Kiis <tanel.kiis@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/CountMinSketchAgg.scala

@@ -20,7 +20,7 @@ package org.apache.spark.sql.catalyst.expressions.aggregate
 import org.apache.spark.sql.catalyst.InternalRow
 import org.apache.spark.sql.catalyst.analysis.TypeCheckResult
 import org.apache.spark.sql.catalyst.analysis.TypeCheckResult.{TypeCheckFailure, TypeCheckSuccess}
-import org.apache.spark.sql.catalyst.expressions.{ExpectsInputTypes, Expression, ExpressionDescription}
+import org.apache.spark.sql.catalyst.expressions.{ExpectsInputTypes, Expression, ExpressionDescription, Literal}
 import org.apache.spark.sql.types._
 import org.apache.spark.unsafe.types.UTF8String
 import org.apache.spark.util.sketch.CountMinSketch
@@ -142,6 +142,9 @@ case class CountMinSketchAgg(
 
   override def dataType: DataType = BinaryType
 
+  override def defaultResult: Option[Literal] =
+    Option(Literal.create(eval(createAggregationBuffer()), dataType))
+
   override def children: Seq[Expression] =
     Seq(child, epsExpression, confidenceExpression, seedExpression)
 

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/HyperLogLogPlusPlus.scala

@@ -90,6 +90,8 @@ case class HyperLogLogPlusPlus(
 
   override def aggBufferSchema: StructType = StructType.fromAttributes(aggBufferAttributes)
 
+  override def defaultResult: Option[Literal] = Option(Literal.create(0L, dataType))
+
   val hllppHelper = new HyperLogLogPlusPlusHelper(relativeSD)
 
   /** Allocate enough words to store all registers. */

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/collect.scala

@@ -47,6 +47,8 @@ abstract class Collect[T <: Growable[Any] with Iterable[Any]] extends TypedImper
   // actual order of input rows.
   override lazy val deterministic: Boolean = false
 
+  override def defaultResult: Option[Literal] = Option(Literal.create(Array(), dataType))
+
   protected def convertToBufferElement(value: Any): Any
 
   override def update(buffer: T, input: InternalRow): T = {

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/interfaces.scala

@@ -203,8 +203,7 @@ abstract class AggregateFunction extends Expression {
   def inputAggBufferAttributes: Seq[AttributeReference]
 
   /**
-   * Result of the aggregate function when the input is empty. This is currently only used for the
-   * proper rewriting of distinct aggregate functions.
+   * Result of the aggregate function when the input is empty.
    */
   def defaultResult: Option[Literal] = None
 

sql/core/src/test/resources/sql-tests/inputs/subquery/scalar-subquery/scalar-subquery-select.sql

@@ -128,3 +128,13 @@ WHERE  NOT EXISTS (SELECT (SELECT max(t2b)
                                  ON     t2a = t1a
                                  WHERE  t2c = t3c)
                    AND    t3a = t1a);
+
+-- SPARK-34876: Non-nullable aggregates should not return NULL in a correlated subquery
+SELECT t1a,
+    (SELECT count(t2d) FROM t2 WHERE t2a = t1a) count_t2,
+    (SELECT count_if(t2d > 0) FROM t2 WHERE t2a = t1a) count_if_t2,
+    (SELECT approx_count_distinct(t2d) FROM t2 WHERE t2a = t1a) approx_count_distinct_t2,
+    (SELECT collect_list(t2d) FROM t2 WHERE t2a = t1a) collect_list_t2,
+    (SELECT collect_set(t2d) FROM t2 WHERE t2a = t1a) collect_set_t2,
+    (SELECT hex(count_min_sketch(t2d, 0.5d, 0.5d, 1)) FROM t2 WHERE t2a = t1a) collect_set_t2
+FROM t1;

sql/core/src/test/resources/sql-tests/results/subquery/scalar-subquery/scalar-subquery-select.sql.out

@@ -1,5 +1,5 @@
 -- Automatically generated by SQLQueryTestSuite
--- Number of queries: 11
+-- Number of queries: 12
 
 
 -- !query
@@ -196,3 +196,29 @@ val1d	NULL
 val1e	10
 val1e	10
 val1e	10
+
+
+-- !query
+SELECT t1a,
+    (SELECT count(t2d) FROM t2 WHERE t2a = t1a) count_t2,
+    (SELECT count_if(t2d > 0) FROM t2 WHERE t2a = t1a) count_if_t2,
+    (SELECT approx_count_distinct(t2d) FROM t2 WHERE t2a = t1a) approx_count_distinct_t2,
+    (SELECT collect_list(t2d) FROM t2 WHERE t2a = t1a) collect_list_t2,
+    (SELECT collect_set(t2d) FROM t2 WHERE t2a = t1a) collect_set_t2,
+    (SELECT hex(count_min_sketch(t2d, 0.5d, 0.5d, 1)) FROM t2 WHERE t2a = t1a) collect_set_t2
+FROM t1
+-- !query schema
+struct<t1a:string,count_t2:bigint,count_if_t2:bigint,approx_count_distinct_t2:bigint,collect_list_t2:array<bigint>,collect_set_t2:array<bigint>,collect_set_t2:string>
+-- !query output
+val1a	0	0	0	[]	[]	0000000100000000000000000000000100000004000000005D8D6AB90000000000000000000000000000000000000000000000000000000000000000
+val1a	0	0	0	[]	[]	0000000100000000000000000000000100000004000000005D8D6AB90000000000000000000000000000000000000000000000000000000000000000
+val1a	0	0	0	[]	[]	0000000100000000000000000000000100000004000000005D8D6AB90000000000000000000000000000000000000000000000000000000000000000
+val1a	0	0	0	[]	[]	0000000100000000000000000000000100000004000000005D8D6AB90000000000000000000000000000000000000000000000000000000000000000
+val1b	6	6	3	[19,119,319,19,19,19]	[19,119,319]	0000000100000000000000060000000100000004000000005D8D6AB90000000000000000000000000000000400000000000000010000000000000001
+val1c	2	2	2	[219,19]	[219,19]	0000000100000000000000020000000100000004000000005D8D6AB90000000000000000000000000000000100000000000000000000000000000001
+val1d	0	0	0	[]	[]	0000000100000000000000000000000100000004000000005D8D6AB90000000000000000000000000000000000000000000000000000000000000000
+val1d	0	0	0	[]	[]	0000000100000000000000000000000100000004000000005D8D6AB90000000000000000000000000000000000000000000000000000000000000000
+val1d	0	0	0	[]	[]	0000000100000000000000000000000100000004000000005D8D6AB90000000000000000000000000000000000000000000000000000000000000000
+val1e	1	1	1	[19]	[19]	0000000100000000000000010000000100000004000000005D8D6AB90000000000000000000000000000000100000000000000000000000000000000
+val1e	1	1	1	[19]	[19]	0000000100000000000000010000000100000004000000005D8D6AB90000000000000000000000000000000100000000000000000000000000000000
+val1e	1	1	1	[19]	[19]	0000000100000000000000010000000100000004000000005D8D6AB90000000000000000000000000000000100000000000000000000000000000000