[SPARK-54720][SQL] Add SparkSession.emptyDataFrame with a schema

### What changes were proposed in this pull request?
This PR adds a version of `SparkSession.emptyDataFrame` that takes a schema.

### Why are the changes needed?
It makes it easier to create an empty DataFrame in Scala.

### Does this PR introduce _any_ user-facing change?
Yes, it adds a new API.

### How was this patch tested?
I have added a test case.

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

Closes #53489 from hvanhovell/SPARK-54720.

Authored-by: Herman van Hövell <[email protected]>
Signed-off-by: Herman van Hövell <[email protected]>

Author: hvanhovell

sql/api/src/main/scala/org/apache/spark/sql/SparkSession.scala

@@ -210,9 +210,15 @@ abstract class SparkSession extends Serializable with Closeable {
    *
    * @since 2.0.0
    */
-  @transient
   def emptyDataFrame: DataFrame
 
+  /**
+   * Returns a `DataFrame` with schema `schema` and no rows.
+   *
+   * @since 4.2.0
+   */
+  def emptyDataFrame(schema: StructType): DataFrame = emptyDataset(Encoders.row(schema))
+
   /**
    * Creates a `DataFrame` from a local Seq of Product.
    *

sql/api/src/test/scala/org/apache/spark/sql/SparkSessionBuilderImplementationBindingSuite.scala

@@ -22,6 +22,7 @@ import org.scalatest.funsuite.AnyFunSuite
 
 import org.apache.spark.SparkContext
 import org.apache.spark.sql.functions.{max, sum}
+import org.apache.spark.sql.types.{IntegerType, StringType, StructField, StructType}
 
 /**
  * Test suite for SparkSession implementation binding.
@@ -70,4 +71,17 @@ trait SparkSessionBuilderImplementationBindingSuite
     val df = ctx.createDataset(1 to 11).select(max("value").as[Long])
     assert(df.head() == 11)
   }
+
+  test("emptyDataFrame with Schema") {
+    val session = SparkSession.builder().getOrCreate()
+    val schema =
+      new StructType(Array(StructField("a", IntegerType), StructField("b", StringType)))
+    val df = session.emptyDataFrame(schema)
+    assert(df.schema == schema)
+    assert(df.isEmpty)
+    val derivedSchema = new StructType(Array(StructField("a", IntegerType)))
+    val derivedDf = df.select("a")
+    assert(derivedDf.schema == derivedSchema)
+    assert(derivedDf.isEmpty)
+  }
 }