[SPARK-52881][SQL] Implement the make_time function in Scala

### What changes were proposed in this pull request?
Implement the `make_time` function in Scala API.

### Why are the changes needed?
Expand API support for the `MakeTime` expression.

### Does this PR introduce _any_ user-facing change?
Yes, the new function is now available in Scala API.

### How was this patch tested?
Added appropriate Scala function tests.

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

Closes apache#51573 from uros-db/scala-make_time.

Lead-authored-by: Uros Bojanic <uros.bojanic@databricks.com>
Co-authored-by: Maxim Gekk <max.gekk@gmail.com>
Signed-off-by: Max Gekk <max.gekk@gmail.com>

Author: uros-db

python/pyspark/sql/tests/test_functions.py

@@ -81,7 +81,10 @@ def test_function_parity(self):
         missing_in_py = jvm_fn_set.difference(py_fn_set)
 
         # Functions that we expect to be missing in python until they are added to pyspark
-        expected_missing_in_py = set()
+        expected_missing_in_py = set(
+            # TODO(SPARK-52888): Implement the make_time function in Python
+            ["make_time"]
+        )
 
         self.assertEqual(
             expected_missing_in_py, missing_in_py, "Missing functions in pyspark not as expected"

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

@@ -871,6 +871,22 @@ object functions {
   def last_value(e: Column, ignoreNulls: Column): Column =
     Column.fn("last_value", e, ignoreNulls)
 
+  /**
+   * Create time from hour, minute and second fields. For invalid inputs it will throw an error.
+   *
+   * @param hour
+   *   the hour to represent, from 0 to 23
+   * @param minute
+   *   the minute to represent, from 0 to 59
+   * @param second
+   *   the second to represent, from 0 to 59.999999
+   * @group datetime_funcs
+   * @since 4.1.0
+   */
+  def make_time(hour: Column, minute: Column, second: Column): Column = {
+    Column.fn("make_time", hour, minute, second)
+  }
+
   /**
    * Aggregate function: returns the most frequent value in a group.
    *

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

@@ -28,6 +28,41 @@ import org.apache.spark.sql.types._
 abstract class TimeFunctionsSuiteBase extends QueryTest with SharedSparkSession {
   import testImplicits._
 
+  test("SPARK-52881: make_time function") {
+    // Input data for the function.
+    val schema = StructType(Seq(
+      StructField("hour", IntegerType, nullable = false),
+      StructField("minute", IntegerType, nullable = false),
+      StructField("second", DecimalType(16, 6), nullable = false)
+    ))
+    val data = Seq(
+      Row(0, 0, BigDecimal(0.0)),
+      Row(1, 2, BigDecimal(3.4)),
+      Row(23, 59, BigDecimal(59.999999))
+    )
+    val df = spark.createDataFrame(spark.sparkContext.parallelize(data), schema)
+
+    // Test the function using both `selectExpr` and `select`.
+    val result1 = df.selectExpr(
+      "make_time(hour, minute, second)"
+    )
+    val result2 = df.select(
+      make_time(col("hour"), col("minute"), col("second"))
+    )
+    // Check that both methods produce the same result.
+    checkAnswer(result1, result2)
+
+    // Expected output of the function.
+    val expected = Seq(
+      "00:00:00",
+      "01:02:03.4",
+      "23:59:59.999999"
+    ).toDF("timeString").select(col("timeString").cast("time"))
+    // Check that the results match the expected output.
+    checkAnswer(result1, expected)
+    checkAnswer(result2, expected)
+  }
+
   test("SPARK-52885: hour function") {
     // Input data for the function.
     val schema = StructType(Seq(