[SPARK-52692][SQL] Support caching the TIME type

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

The proposed changes are largely based on commit 0674327, which added caching support for TIMESTAMP_NTZ. This PR makes the same changes, except for the TIME type.

### Why are the changes needed?

To support caching the TIME type, e.g.:
```
CACHE TABLE v1 AS SELECT TIME'22:00:00';
```
### Does this PR introduce _any_ user-facing change?

No. The TIME type is not released yet.

### How was this patch tested?

New unit test.

### Was this patch authored or co-authored using generative AI tooling?

No.

Closes #51385 from bersprockets/time_cache.

Authored-by: Bruce Robbins <[email protected]>
Signed-off-by: Max Gekk <[email protected]>

Author: bersprockets

sql/core/src/main/scala/org/apache/spark/sql/execution/columnar/ColumnBuilder.scala

@@ -185,7 +185,7 @@ private[columnar] object ColumnBuilder {
       case ByteType => new ByteColumnBuilder
       case ShortType => new ShortColumnBuilder
       case IntegerType | DateType | _: YearMonthIntervalType => new IntColumnBuilder
-      case LongType | TimestampType | TimestampNTZType | _: DayTimeIntervalType =>
+      case LongType | TimestampType | TimestampNTZType | _: DayTimeIntervalType | _: TimeType =>
         new LongColumnBuilder
       case FloatType => new FloatColumnBuilder
       case DoubleType => new DoubleColumnBuilder

sql/core/src/main/scala/org/apache/spark/sql/execution/columnar/ColumnType.scala

@@ -869,7 +869,8 @@ private[columnar] object ColumnType {
       case ByteType => BYTE
       case ShortType => SHORT
       case IntegerType | DateType | _: YearMonthIntervalType => INT
-      case LongType | TimestampType | TimestampNTZType | _: DayTimeIntervalType => LONG
+      case LongType | TimestampType | TimestampNTZType | _: DayTimeIntervalType | _: TimeType =>
+        LONG
       case FloatType => FLOAT
       case DoubleType => DOUBLE
       case s: StringType => STRING(s)

sql/core/src/main/scala/org/apache/spark/sql/execution/columnar/GenerateColumnAccessor.scala

@@ -82,7 +82,7 @@ object GenerateColumnAccessor extends CodeGenerator[Seq[DataType], ColumnarItera
         case ByteType => classOf[ByteColumnAccessor].getName
         case ShortType => classOf[ShortColumnAccessor].getName
         case IntegerType | DateType | _: YearMonthIntervalType => classOf[IntColumnAccessor].getName
-        case LongType | TimestampType | TimestampNTZType | _: DayTimeIntervalType =>
+        case LongType | TimestampType | TimestampNTZType | _: DayTimeIntervalType | _: TimeType =>
           classOf[LongColumnAccessor].getName
         case FloatType => classOf[FloatColumnAccessor].getName
         case DoubleType => classOf[DoubleColumnAccessor].getName

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

@@ -19,7 +19,7 @@ package org.apache.spark.sql
 
 import java.io.{File, FilenameFilter}
 import java.nio.file.{Files, Paths}
-import java.time.{Duration, LocalDateTime, Period}
+import java.time.{Duration, LocalDateTime, LocalTime, Period}
 import java.util.concurrent.atomic.AtomicBoolean
 
 import scala.collection.mutable.HashSet
@@ -1792,6 +1792,19 @@ class CachedTableSuite extends QueryTest with SQLTestUtils
     }
   }
 
+  test("SPARK-52692: Support cache/uncache table with Time type") {
+    val tableName = "timeCache"
+    withTable(tableName) {
+      sql(s"CACHE TABLE $tableName AS SELECT TIME'22:00:00'")
+      checkAnswer(spark.table(tableName), Row(LocalTime.parse("22:00:00")))
+      spark.table(tableName).queryExecution.withCachedData.collect {
+        case cached: InMemoryRelation =>
+          assert(cached.stats.sizeInBytes === 8)
+      }
+      sql(s"UNCACHE TABLE $tableName")
+    }
+  }
+
   Seq(true, false).foreach { callerEnableAQE =>
     test(s"SPARK-49982: AQE negative caching with in memory table cache - callerEnableAQE=" +
       callerEnableAQE) {