diff --git a/hudi-spark-datasource/hudi-spark/src/test/scala/org/apache/spark/sql/hudi/command/index/TestExpressionIndex.scala b/hudi-spark-datasource/hudi-spark/src/test/scala/org/apache/spark/sql/hudi/command/index/TestExpressionIndex.scala
index e632980962829..c3dbc771be68d 100644
--- a/hudi-spark-datasource/hudi-spark/src/test/scala/org/apache/spark/sql/hudi/command/index/TestExpressionIndex.scala
+++ b/hudi-spark-datasource/hudi-spark/src/test/scala/org/apache/spark/sql/hudi/command/index/TestExpressionIndex.scala
@@ -35,7 +35,7 @@ import org.apache.hudi.config.{HoodieCleanConfig, HoodieCompactionConfig, Hoodie
 import org.apache.hudi.hive.testutils.HiveTestUtil
 import org.apache.hudi.hive.{HiveSyncTool, HoodieHiveSyncClient}
 import org.apache.hudi.index.HoodieIndex
-import org.apache.hudi.index.expression.{HoodieExpressionIndex, HoodieSparkExpressionIndex}
+import org.apache.hudi.index.expression.HoodieExpressionIndex
 import org.apache.hudi.metadata.{HoodieMetadataFileSystemView, MetadataPartitionType}
 import org.apache.hudi.storage.StoragePath
 import org.apache.hudi.sync.common.HoodieSyncConfig.{META_SYNC_BASE_PATH, META_SYNC_DATABASE_NAME, META_SYNC_NO_PARTITION_METADATA, META_SYNC_TABLE_NAME}
@@ -743,11 +743,87 @@ class TestExpressionIndex extends HoodieSparkSqlTestBase {
     }
   }
 
+  /**
+   * Test expression index with auto generation of record keys
+   */
+  test("Test Expression Index With AutoGen") {
+    withTempDir { tmp =>
+      Seq("cow", "mor").foreach { tableType =>
+        val tableName = generateTableName + s"_stats_pruning_binary_$tableType"
+        val basePath = s"${tmp.getCanonicalPath}/$tableName"
+
+        spark.sql("set hoodie.fileIndex.dataSkippingFailureMode=strict")
+
+        spark.sql(
+          s"""
+           CREATE TABLE $tableName (
+             |    ts LONG,
+             |    id STRING,
+             |    rider STRING,
+             |    driver STRING,
+             |    fare DOUBLE,
+             |    dateDefault STRING,
+             |    date STRING,
+             |    city STRING,
+             |    state STRING
+             |) USING HUDI
+             |options(
+             |    type = '$tableType',
+             |    hoodie.metadata.enable = 'true',
+             |    hoodie.enable.data.skipping = 'true'
+             |)
+             |PARTITIONED BY (state)
+             |location '$basePath'
+             |""".stripMargin)
+
+        spark.sql("set hoodie.parquet.small.file.limit=0")
+        if (HoodieSparkUtils.gteqSpark3_4) {
+          spark.sql("set spark.sql.defaultColumn.enabled=false")
+        }
+
+        spark.sql(
+          s"""
+             |insert into $tableName(ts, id, rider, driver, fare, dateDefault, date, city, state) VALUES
+             |  (1695414520,'trip2','rider-C','driver-M',27.70,'2024-11-30 01:30:40', '2024-11-30', 'sunnyvale','california'),
+             |  (1699349649,'trip5','rider-A','driver-Q',3.32, '2019-11-30 01:30:40', '2019-11-30', 'san_diego','texas')
+             |""".stripMargin)
+        val tableSchema: StructType =
+          StructType(
+            Seq(
+              StructField("ts", LongType),
+              StructField("id", StringType),
+              StructField("rider", StringType),
+              StructField("driver", StringType),
+              StructField("fare", DoubleType),
+              StructField("dateDefault", StringType),
+              StructField("date", StringType),
+              StructField("city", StringType),
+              StructField("state", StringType)
+            )
+          )
+
+        spark.sql(s"create index idx_datestr on $tableName using column_stats(ts) options(expr='from_unixtime')")
+        checkAnswer(s"select id, rider, from_unixtime(ts) from $tableName where from_unixtime(ts) > '1970-01-03'")(
+          Seq("trip2", "rider-C", "2023-09-22 20:28:40"),
+          Seq("trip5", "rider-A", "2023-11-07 09:34:09")
+        )
+
+        // validate pruning
+        val opts = Map.apply(DataSourceReadOptions.ENABLE_DATA_SKIPPING.key -> "true", HoodieMetadataConfig.ENABLE.key -> "true")
+        val metaClient = createMetaClient(spark, basePath)
+        val fromUnixTime = resolveExpr(spark, unapply(functions.from_unixtime(functions.col("ts"))).get, tableSchema)
+        val literal = Literal.create("2023-09-22 20:28:40")
+        val dataFilter = EqualTo(fromUnixTime, literal)
+        verifyFilePruning(opts, dataFilter, metaClient, isDataSkippingExpected = true)
+        spark.sql(s"drop index idx_datestr on $tableName")
+      }
+    }
+  }
+
   /**
    * Test expression index with invalid options
    */
-  @Test
-  def testInvalidOptions(): Unit = {
+  test("Test Expression Index Creation With Invalid Options") {
     withTempDir { tmp =>
       Seq("cow", "mor").foreach { tableType =>
         val tableName = generateTableName + s"_stats_pruning_binary_$tableType"
@@ -802,8 +878,7 @@ class TestExpressionIndex extends HoodieSparkSqlTestBase {
   /**
    * Test expression index with data skipping for date and timestamp based expressions.
    */
-  @Test
-  def testColumnStatsPruningWithDateTimestampExpressions(): Unit = {
+  test("Test Expression Index Column Stat Pruning With Timestamp Expressions") {
     withTempDir { tmp =>
       Seq("cow", "mor").foreach { tableType =>
         val tableName = generateTableName + s"_stats_pruning_date_expr_$tableType"
@@ -952,8 +1027,7 @@ class TestExpressionIndex extends HoodieSparkSqlTestBase {
   /**
    * Test expression index with data skipping for string expressions.
    */
-  @Test
-  def testColumnStatsPruningWithStringExpressions(): Unit = {
+  test("Test Expression Index Column Stat Pruning With String Expression") {
     withTempDir { tmp =>
       Seq("cow", "mor").foreach { tableType =>
         val tableName = generateTableName + s"_stats_pruning_string_expr_$tableType"