build: reduce combinatorial explosion in temporal fuzz tests

spark/src/test/scala/org/apache/comet/CometFuzzTestSuite.scala

@@ -271,19 +271,25 @@ class CometFuzzTestSuite extends CometFuzzTestBase {
   }
 
   test("Parquet temporal types written as INT96") {
-    testParquetTemporalTypes(ParquetOutputTimestampType.INT96)
+    // INT96 is the only format where int96AsTimestamp and int96TimestampConversion matter
+    testParquetTemporalTypes(ParquetOutputTimestampType.INT96, testInt96Settings = true)
   }
 
   test("Parquet temporal types written as TIMESTAMP_MICROS") {
-    testParquetTemporalTypes(ParquetOutputTimestampType.TIMESTAMP_MICROS)
+    testParquetTemporalTypes(
+      ParquetOutputTimestampType.TIMESTAMP_MICROS,
+      testInt96Settings = false)
   }
 
   test("Parquet temporal types written as TIMESTAMP_MILLIS") {
-    testParquetTemporalTypes(ParquetOutputTimestampType.TIMESTAMP_MILLIS)
+    testParquetTemporalTypes(
+      ParquetOutputTimestampType.TIMESTAMP_MILLIS,
+      testInt96Settings = false)
   }
 
   private def testParquetTemporalTypes(
-      outputTimestampType: ParquetOutputTimestampType.Value): Unit = {
+      outputTimestampType: ParquetOutputTimestampType.Value,
+      testInt96Settings: Boolean): Unit = {
 
     val dataGenOptions = DataGenOptions(generateNegativeZero = false)
 
@@ -294,15 +300,17 @@ class CometFuzzTestSuite extends CometFuzzTestBase {
         SQLConf.PARQUET_OUTPUT_TIMESTAMP_TYPE.key -> outputTimestampType.toString,
         SQLConf.SESSION_LOCAL_TIMEZONE.key -> defaultTimezone) {
 
+        // Include both DateType and TimestampType to properly test timestamp configurations
         // TODO test with MapType
         // https://github.com/apache/datafusion-comet/issues/2945
         val schema = StructType(
           Seq(
             StructField("c0", DataTypes.DateType),
-            StructField("c1", DataTypes.createArrayType(DataTypes.DateType)),
+            StructField("c1", DataTypes.TimestampType),
+            StructField("c2", DataTypes.createArrayType(DataTypes.DateType)),
             StructField(
-              "c2",
-              DataTypes.createStructType(Array(StructField("c3", DataTypes.DateType))))))
+              "c3",
+              DataTypes.createStructType(Array(StructField("c4", DataTypes.DateType))))))
 
         ParquetGenerator.makeParquetFile(
           random,
@@ -313,28 +321,33 @@ class CometFuzzTestSuite extends CometFuzzTestBase {
           dataGenOptions)
       }
 
-      Seq(defaultTimezone, "UTC", "America/Denver").foreach { tz =>
-        Seq(true, false).foreach { inferTimestampNtzEnabled =>
-          Seq(true, false).foreach { int96TimestampConversion =>
-            Seq(true, false).foreach { int96AsTimestamp =>
-              withSQLConf(
-                CometConf.COMET_ENABLED.key -> "true",
-                SQLConf.SESSION_LOCAL_TIMEZONE.key -> tz,
-                SQLConf.PARQUET_INT96_AS_TIMESTAMP.key -> int96AsTimestamp.toString,
-                SQLConf.PARQUET_INT96_TIMESTAMP_CONVERSION.key -> int96TimestampConversion.toString,
-                SQLConf.PARQUET_INFER_TIMESTAMP_NTZ_ENABLED.key -> inferTimestampNtzEnabled.toString) {
+      // Test with local timezone and UTC (2 timezones instead of 3)
+      Seq(defaultTimezone, "UTC").foreach { tz =>
+        // INT96-specific settings only matter for INT96 format
+        val int96Combinations = if (testInt96Settings) {
+          // Test key combinations for INT96: both settings true, both false, and mixed
+          Seq((true, true), (false, false), (true, false))
+        } else {
+          // For non-INT96 formats, these settings don't matter, so just use defaults
+          Seq((true, false))
+        }
+
+        int96Combinations.foreach { case (int96AsTimestamp, int96TimestampConversion) =>
+          withSQLConf(
+            CometConf.COMET_ENABLED.key -> "true",
+            SQLConf.SESSION_LOCAL_TIMEZONE.key -> tz,
+            SQLConf.PARQUET_INT96_AS_TIMESTAMP.key -> int96AsTimestamp.toString,
+            SQLConf.PARQUET_INT96_TIMESTAMP_CONVERSION.key -> int96TimestampConversion.toString) {
 
-                val df = spark.read.parquet(filename.toString)
-                df.createOrReplaceTempView("t1")
-                val columns =
-                  df.schema.fields
-                    .filter(f => DataTypeSupport.hasTemporalType(f.dataType))
-                    .map(_.name)
+            val df = spark.read.parquet(filename.toString)
+            df.createOrReplaceTempView("t1")
+            val columns =
+              df.schema.fields
+                .filter(f => DataTypeSupport.hasTemporalType(f.dataType))
+                .map(_.name)
 
-                for (col <- columns) {
-                  checkSparkAnswer(s"SELECT $col FROM t1 ORDER BY $col")
-                }
-              }
+            for (col <- columns) {
+              checkSparkAnswer(s"SELECT $col FROM t1 ORDER BY $col")
             }
           }
         }