[SPARK-51488][SQL] Support the TIME keyword as a data type

### What changes were proposed in this pull request?
In the PR, I propose to support `TIME(n)` as a data type in Spark SQL syntax, and convert it to `TimeType(precision)` during parse.

### Why are the changes needed?
To achieve feature parity between Spark SQL and Scala/Java APIs. SQL users can use `TIME` as a data type.

### Does this PR introduce _any_ user-facing change?
Yes, users can refer to `TIME` as a data type, but before they got an error.

### How was this patch tested?
By running new tests:
```
$ build/sbt "test:testOnly *DataTypeParserSuite"
```

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

Closes #50250 from MaxGekk/time-type.

Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>

Author: MaxGekk

sql/api/src/main/antlr4/org/apache/spark/sql/catalyst/parser/SqlBaseParser.g4

@@ -1280,6 +1280,7 @@ type
     | FLOAT | REAL
     | DOUBLE
     | DATE
+    | TIME
     | TIMESTAMP | TIMESTAMP_NTZ | TIMESTAMP_LTZ
     | STRING collateClause?
     | CHARACTER | CHAR

sql/api/src/main/scala/org/apache/spark/sql/catalyst/parser/DataTypeAstBuilder.scala

@@ -30,7 +30,7 @@ import org.apache.spark.sql.catalyst.util.SparkParserUtils.{string, withOrigin}
 import org.apache.spark.sql.connector.catalog.IdentityColumnSpec
 import org.apache.spark.sql.errors.QueryParsingErrors
 import org.apache.spark.sql.internal.SqlApiConf
-import org.apache.spark.sql.types.{ArrayType, BinaryType, BooleanType, ByteType, CalendarIntervalType, CharType, DataType, DateType, DayTimeIntervalType, DecimalType, DoubleType, FloatType, IntegerType, LongType, MapType, MetadataBuilder, NullType, ShortType, StringType, StructField, StructType, TimestampNTZType, TimestampType, VarcharType, VariantType, YearMonthIntervalType}
+import org.apache.spark.sql.types.{ArrayType, BinaryType, BooleanType, ByteType, CalendarIntervalType, CharType, DataType, DateType, DayTimeIntervalType, DecimalType, DoubleType, FloatType, IntegerType, LongType, MapType, MetadataBuilder, NullType, ShortType, StringType, StructField, StructType, TimestampNTZType, TimestampType, TimeType, VarcharType, VariantType, YearMonthIntervalType}
 
 class DataTypeAstBuilder extends SqlBaseParserBaseVisitor[AnyRef] {
   protected def typedVisit[T](ctx: ParseTree): T = {
@@ -79,6 +79,8 @@ class DataTypeAstBuilder extends SqlBaseParserBaseVisitor[AnyRef] {
       case (FLOAT | REAL, Nil) => FloatType
       case (DOUBLE, Nil) => DoubleType
       case (DATE, Nil) => DateType
+      case (TIME, Nil) => TimeType(TimeType.MICROS_PRECISION)
+      case (TIME, precision :: Nil) => TimeType(precision.getText.toInt)
       case (TIMESTAMP, Nil) => SqlApiConf.get.timestampType
       case (TIMESTAMP_NTZ, Nil) => TimestampNTZType
       case (TIMESTAMP_LTZ, Nil) => TimestampType

sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/parser/DataTypeParserSuite.scala

@@ -17,7 +17,7 @@
 
 package org.apache.spark.sql.catalyst.parser
 
-import org.apache.spark.SparkFunSuite
+import org.apache.spark.{SparkException, SparkFunSuite}
 import org.apache.spark.sql.catalyst.plans.SQLHelper
 import org.apache.spark.sql.internal.SQLConf
 import org.apache.spark.sql.internal.SQLConf.TimestampTypes
@@ -57,6 +57,9 @@ class DataTypeParserSuite extends SparkFunSuite with SQLHelper {
   checkDataType("Dec(10, 5)", DecimalType(10, 5))
   checkDataType("deC", DecimalType.USER_DEFAULT)
   checkDataType("DATE", DateType)
+  checkDataType("TimE", TimeType())
+  checkDataType("time(0)", TimeType(0))
+  checkDataType("TIME(6)", TimeType(6))
   checkDataType("timestamp", TimestampType)
   checkDataType("timestamp_ntz", TimestampNTZType)
   checkDataType("timestamp_ltz", TimestampType)
@@ -172,4 +175,19 @@ class DataTypeParserSuite extends SparkFunSuite with SQLHelper {
   // DataType parser accepts comments.
   checkDataType("Struct<x: INT, y: STRING COMMENT 'test'>",
     (new StructType).add("x", IntegerType).add("y", StringType, true, "test"))
+
+  test("unsupported precision of the time data type") {
+    checkError(
+      exception = intercept[SparkException] {
+        CatalystSqlParser.parseDataType("time(9)")
+      },
+      condition = "UNSUPPORTED_TIME_PRECISION",
+      parameters = Map("precision" -> "9"))
+    checkError(
+      exception = intercept[ParseException] {
+        CatalystSqlParser.parseDataType("time(-1)")
+      },
+      condition = "PARSE_SYNTAX_ERROR",
+      parameters = Map("error" -> "'('", "hint" -> ""))
+  }
 }