diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JDBCRDD.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JDBCRDD.scala
index 1b8d33b94fbd2..394ba3f8bb8c2 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JDBCRDD.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JDBCRDD.scala
@@ -25,7 +25,6 @@ import org.apache.spark.{InterruptibleIterator, Partition, SparkContext, TaskCon
 import org.apache.spark.internal.Logging
 import org.apache.spark.rdd.RDD
 import org.apache.spark.sql.catalyst.InternalRow
-import org.apache.spark.sql.connector.expressions.aggregate.{AggregateFunc, Count, CountStar, Max, Min, Sum}
 import org.apache.spark.sql.execution.datasources.v2.TableSampleInfo
 import org.apache.spark.sql.jdbc.{JdbcDialect, JdbcDialects}
 import org.apache.spark.sql.sources._
@@ -140,34 +139,6 @@ object JDBCRDD extends Logging {
     })
   }
 
-  def compileAggregates(
-      aggregates: Seq[AggregateFunc],
-      dialect: JdbcDialect): Option[Seq[String]] = {
-    def quote(colName: String): String = dialect.quoteIdentifier(colName)
-
-    Some(aggregates.map {
-      case min: Min =>
-        if (min.column.fieldNames.length != 1) return None
-        s"MIN(${quote(min.column.fieldNames.head)})"
-      case max: Max =>
-        if (max.column.fieldNames.length != 1) return None
-        s"MAX(${quote(max.column.fieldNames.head)})"
-      case count: Count =>
-        if (count.column.fieldNames.length != 1) return None
-        val distinct = if (count.isDistinct) "DISTINCT " else ""
-        val column = quote(count.column.fieldNames.head)
-        s"COUNT($distinct$column)"
-      case sum: Sum =>
-        if (sum.column.fieldNames.length != 1) return None
-        val distinct = if (sum.isDistinct) "DISTINCT " else ""
-        val column = quote(sum.column.fieldNames.head)
-        s"SUM($distinct$column)"
-      case _: CountStar =>
-        s"COUNT(*)"
-      case _ => return None
-    })
-  }
-
   /**
    * Build and return JDBCRDD from the given information.
    *
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/jdbc/JDBCScanBuilder.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/jdbc/JDBCScanBuilder.scala
index 7605b03f49ea5..d3c141ed53c5c 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/jdbc/JDBCScanBuilder.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/jdbc/JDBCScanBuilder.scala
@@ -72,8 +72,8 @@ case class JDBCScanBuilder(
     if (!jdbcOptions.pushDownAggregate) return false
 
     val dialect = JdbcDialects.get(jdbcOptions.url)
-    val compiledAgg = JDBCRDD.compileAggregates(aggregation.aggregateExpressions, dialect)
-    if (compiledAgg.isEmpty) return false
+    val compiledAggs = aggregation.aggregateExpressions.flatMap(dialect.compileAggregate(_))
+    if (compiledAggs.length != aggregation.aggregateExpressions.length) return false
 
     val groupByCols = aggregation.groupByColumns.map { col =>
       if (col.fieldNames.length != 1) return false
@@ -84,7 +84,7 @@ case class JDBCScanBuilder(
     // e.g. "DEPT","NAME",MAX("SALARY"),MIN("BONUS") =>
     // SELECT "DEPT","NAME",MAX("SALARY"),MIN("BONUS") FROM "test"."employee"
     //   GROUP BY "DEPT", "NAME"
-    val selectList = groupByCols ++ compiledAgg.get
+    val selectList = groupByCols ++ compiledAggs
     val groupByClause = if (groupByCols.isEmpty) {
       ""
     } else {
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/jdbc/JdbcDialects.scala b/sql/core/src/main/scala/org/apache/spark/sql/jdbc/JdbcDialects.scala
index c7db771c73a68..fcc2be2d16d88 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/jdbc/JdbcDialects.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/jdbc/JdbcDialects.scala
@@ -33,6 +33,7 @@ import org.apache.spark.sql.connector.catalog.TableChange
 import org.apache.spark.sql.connector.catalog.TableChange._
 import org.apache.spark.sql.connector.catalog.index.TableIndex
 import org.apache.spark.sql.connector.expressions.NamedReference
+import org.apache.spark.sql.connector.expressions.aggregate.{AggregateFunc, Count, CountStar, Max, Min, Sum}
 import org.apache.spark.sql.errors.QueryCompilationErrors
 import org.apache.spark.sql.execution.datasources.jdbc.{JDBCOptions, JdbcUtils}
 import org.apache.spark.sql.execution.datasources.v2.TableSampleInfo
@@ -193,6 +194,36 @@ abstract class JdbcDialect extends Serializable with Logging{
     case _ => value
   }
 
+  /**
+   * Converts aggregate function to String representing a SQL expression.
+   * @param aggregate The aggregate function to be converted.
+   * @return Converted value.
+   */
+  @Since("3.3.0")
+  def compileAggregate(aggFunction: AggregateFunc): Option[String] = {
+    aggFunction match {
+      case min: Min =>
+        if (min.column.fieldNames.length != 1) return None
+        Some(s"MIN(${quoteIdentifier(min.column.fieldNames.head)})")
+      case max: Max =>
+        if (max.column.fieldNames.length != 1) return None
+        Some(s"MAX(${quoteIdentifier(max.column.fieldNames.head)})")
+      case count: Count =>
+        if (count.column.fieldNames.length != 1) return None
+        val distinct = if (count.isDistinct) "DISTINCT " else ""
+        val column = quoteIdentifier(count.column.fieldNames.head)
+        Some(s"COUNT($distinct$column)")
+      case sum: Sum =>
+        if (sum.column.fieldNames.length != 1) return None
+        val distinct = if (sum.isDistinct) "DISTINCT " else ""
+        val column = quoteIdentifier(sum.column.fieldNames.head)
+        Some(s"SUM($distinct$column)")
+      case _: CountStar =>
+        Some(s"COUNT(*)")
+      case _ => None
+    }
+  }
+
   /**
    * Return Some[true] iff `TRUNCATE TABLE` causes cascading default.
    * Some[true] : TRUNCATE TABLE causes cascading.