soumilshah1995 commented on issue #10110:
URL: https://github.com/apache/hudi/issues/10110#issuecomment-1815424659

   # Code
   
   ```
   
   from pyspark.sql import SparkSession
   from pyspark.sql.types import StructType, StructField, StringType, 
TimestampType, FloatType
   from datetime import datetime
   import os
   import sys
   
   from pyspark.sql import SparkSession
   from pyspark.sql.types import StructType, StructField, StringType, 
TimestampType, FloatType
   from datetime import datetime
   import os
   import sys
   
   
   HUDI_VERSION = '1.0.0-beta1'
   SPARK_VERSION = '3.4'
   
   SUBMIT_ARGS = f"--packages 
org.apache.hudi:hudi-spark{SPARK_VERSION}-bundle_2.12:{HUDI_VERSION} 
pyspark-shell"
   os.environ["PYSPARK_SUBMIT_ARGS"] = SUBMIT_ARGS
   os.environ['PYSPARK_PYTHON'] = sys.executable
   
   # Spark session
   spark = SparkSession.builder \
       .config('spark.serializer', 
'org.apache.spark.serializer.KryoSerializer') \
       .config('spark.sql.extensions', 
'org.apache.spark.sql.hudi.HoodieSparkSessionExtension') \
       .config('className', 'org.apache.hudi') \
       .config('spark.sql.hive.convertMetastoreParquet', 'false') \
       .getOrCreate()
   
   
   data = [
       [1695159649, '334e26e9-8355-45cc-97c6-c31daf0df330', 'rider-A', 
'driver-K', 19.10, 'san_francisco'],
       [1695159649, 'e96c4396-3fad-413a-a942-4cb36106d721', 'rider-C', 
'driver-M', 27.70, 'san_francisco'],
   ]
   
   # Define schema for the DataFrame
   schema = StructType([
       StructField("ts", StringType(), True),
       StructField("transaction_id", StringType(), True),
       StructField("rider", StringType(), True),
       StructField("driver", StringType(), True),
       StructField("price", FloatType(), True),
       StructField("location", StringType(), True),
   ])
   
   # Create Spark DataFrame
   df = spark.createDataFrame(data, schema=schema)
   
   df.show()
   
   
   path = 'file:///Users/soumilnitinshah/Downloads/hudidb/hudi_table_func_index'
   
   
   hudi_options = {
       'hoodie.table.name': 'hudi_table_func_index',
       'hoodie.datasource.write.table.type': 'COPY_ON_WRITE',
       'hoodie.datasource.write.operation': 'upsert',
       'hoodie.datasource.write.recordkey.field': 'transaction_id',
       'hoodie.datasource.write.precombine.field': 'ts',
       'hoodie.table.metadata.enable': 'true',
       'hoodie.datasource.write.partitionpath.field': 'location',
       'hoodie.parquet.small.file.limit':'0'
   }
   
   
   df.write.format("hudi").options(**hudi_options).mode("append").save(path)
   
   
   
   
   PATH = 'file:///Users/soumilnitinshah/Downloads/hudidb/hudi_table_func_index'
   TABLE_NAME = "hudi_table_func_index"
   
   spark.read.format("hudi").load(PATH).createOrReplaceTempView(TABLE_NAME)
   
   spark.sql(f"""SELECT from_unixtime(ts, 'yyyy-MM-dd') as datestr FROM 
{TABLE_NAME}""").show()
   spark.sql(f"""CREATE INDEX {TABLE_NAME}_datestr ON {TABLE_NAME} USING 
column_stats(ts) options(func='from_unixtime', format='yyyy-MM-dd')""")
   
   
   ```
   
   # Error 
   ```
   
   +----------+
   |   datestr|
   +----------+
   |2023-09-19|
   |2023-09-19|
   +----------+
   
   ---------------------------------------------------------------------------
   Py4JJavaError                             Traceback (most recent call last)
   Cell In[7], line 7
         4 
spark.read.format("hudi").load(PATH).createOrReplaceTempView(TABLE_NAME)
         6 spark.sql(f"""SELECT from_unixtime(ts, 'yyyy-MM-dd') as datestr FROM 
{TABLE_NAME}""").show()
   ----> 7 spark.sql(f"""CREATE INDEX {TABLE_NAME}_datestr ON {TABLE_NAME} 
USING column_stats(ts) options(func='from_unixtime', format='yyyy-MM-dd')""")
   
   File ~/anaconda3/lib/python3.11/site-packages/pyspark/sql/session.py:1440, 
in SparkSession.sql(self, sqlQuery, args, **kwargs)
      1438 try:
      1439     litArgs = {k: _to_java_column(lit(v)) for k, v in (args or 
{}).items()}
   -> 1440     return DataFrame(self._jsparkSession.sql(sqlQuery, litArgs), 
self)
      1441 finally:
      1442     if len(kwargs) > 0:
   
   File ~/anaconda3/lib/python3.11/site-packages/py4j/java_gateway.py:1322, in 
JavaMember.__call__(self, *args)
      1316 command = proto.CALL_COMMAND_NAME +\
      1317     self.command_header +\
      1318     args_command +\
      1319     proto.END_COMMAND_PART
      1321 answer = self.gateway_client.send_command(command)
   -> 1322 return_value = get_return_value(
      1323     answer, self.gateway_client, self.target_id, self.name)
      1325 for temp_arg in temp_args:
      1326     if hasattr(temp_arg, "_detach"):
   
   File 
~/anaconda3/lib/python3.11/site-packages/pyspark/errors/exceptions/captured.py:169,
 in capture_sql_exception.<locals>.deco(*a, **kw)
       167 def deco(*a: Any, **kw: Any) -> Any:
       168     try:
   --> 169         return f(*a, **kw)
       170     except Py4JJavaError as e:
       171         converted = convert_exception(e.java_exception)
   
   File ~/anaconda3/lib/python3.11/site-packages/py4j/protocol.py:326, in 
get_return_value(answer, gateway_client, target_id, name)
       324 value = OUTPUT_CONVERTER[type](answer[2:], gateway_client)
       325 if answer[1] == REFERENCE_TYPE:
   --> 326     raise Py4JJavaError(
       327         "An error occurred while calling {0}{1}{2}.\n".
       328         format(target_id, ".", name), value)
       329 else:
       330     raise Py4JError(
       331         "An error occurred while calling {0}{1}{2}. Trace:\n{3}\n".
       332         format(target_id, ".", name, value))
   
   Py4JJavaError: An error occurred while calling o34.sql.
   : java.lang.ClassCastException: class 
org.apache.spark.sql.catalyst.plans.logical.SubqueryAlias cannot be cast to 
class org.apache.spark.sql.catalyst.analysis.ResolvedTable 
(org.apache.spark.sql.catalyst.plans.logical.SubqueryAlias and 
org.apache.spark.sql.catalyst.analysis.ResolvedTable are in unnamed module of 
loader 'app')
        at 
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveFieldNameAndPosition$$anonfun$apply$58.applyOrElse(Analyzer.scala:3671)
        at 
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveFieldNameAndPosition$$anonfun$apply$58.applyOrElse(Analyzer.scala:3668)
        at 
org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.$anonfun$resolveOperatorsUpWithPruning$3(AnalysisHelper.scala:138)
        at 
org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:104)
        at 
org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.$anonfun$resolveOperatorsUpWithPruning$1(AnalysisHelper.scala:138)
        at 
org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$.allowInvokingTransformsInAnalyzer(AnalysisHelper.scala:323)
        at 
org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.resolveOperatorsUpWithPruning(AnalysisHelper.scala:134)
        at 
org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.resolveOperatorsUpWithPruning$(AnalysisHelper.scala:130)
        at 
org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperatorsUpWithPruning(LogicalPlan.scala:31)
        at 
org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.resolveOperatorsUp(AnalysisHelper.scala:111)
        at 
org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.resolveOperatorsUp$(AnalysisHelper.scala:110)
        at 
org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperatorsUp(LogicalPlan.scala:31)
        at 
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveFieldNameAndPosition$.apply(Analyzer.scala:3668)
        at 
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveFieldNameAndPosition$.apply(Analyzer.scala:3667)
        at 
org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$execute$2(RuleExecutor.scala:222)
        at 
scala.collection.LinearSeqOptimized.foldLeft(LinearSeqOptimized.scala:126)
        at 
scala.collection.LinearSeqOptimized.foldLeft$(LinearSeqOptimized.scala:122)
        at scala.collection.immutable.List.foldLeft(List.scala:91)
        at 
org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$execute$1(RuleExecutor.scala:219)
        at 
org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$execute$1$adapted(RuleExecutor.scala:211)
        at scala.collection.immutable.List.foreach(List.scala:431)
        at 
org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:211)
        at 
org.apache.spark.sql.catalyst.analysis.Analyzer.org$apache$spark$sql$catalyst$analysis$Analyzer$$executeSameContext(Analyzer.scala:228)
        at 
org.apache.spark.sql.catalyst.analysis.Analyzer.$anonfun$execute$1(Analyzer.scala:224)
        at 
org.apache.spark.sql.catalyst.analysis.AnalysisContext$.withNewAnalysisContext(Analyzer.scala:173)
        at 
org.apache.spark.sql.catalyst.analysis.Analyzer.execute(Analyzer.scala:224)
        at 
org.apache.spark.sql.catalyst.analysis.Analyzer.execute(Analyzer.scala:188)
        at 
org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$executeAndTrack$1(RuleExecutor.scala:182)
        at 
org.apache.spark.sql.catalyst.QueryPlanningTracker$.withTracker(QueryPlanningTracker.scala:88)
        at 
org.apache.spark.sql.catalyst.rules.RuleExecutor.executeAndTrack(RuleExecutor.scala:182)
        at 
org.apache.spark.sql.catalyst.analysis.Analyzer.$anonfun$executeAndCheck$1(Analyzer.scala:209)
        at 
org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$.markInAnalyzer(AnalysisHelper.scala:330)
        at 
org.apache.spark.sql.catalyst.analysis.Analyzer.executeAndCheck(Analyzer.scala:208)
        at 
org.apache.spark.sql.execution.QueryExecution.$anonfun$analyzed$1(QueryExecution.scala:76)
        at 
org.apache.spark.sql.catalyst.QueryPlanningTracker.measurePhase(QueryPlanningTracker.scala:111)
        at 
org.apache.spark.sql.execution.QueryExecution.$anonfun$executePhase$2(QueryExecution.scala:202)
        at 
org.apache.spark.sql.execution.QueryExecution$.withInternalError(QueryExecution.scala:526)
        at 
org.apache.spark.sql.execution.QueryExecution.$anonfun$executePhase$1(QueryExecution.scala:202)
        at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:827)
        at 
org.apache.spark.sql.execution.QueryExecution.executePhase(QueryExecution.scala:201)
        at 
org.apache.spark.sql.execution.QueryExecution.analyzed$lzycompute(QueryExecution.scala:76)
        at 
org.apache.spark.sql.execution.QueryExecution.analyzed(QueryExecution.scala:74)
        at 
org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:66)
        at org.apache.spark.sql.Dataset$.$anonfun$ofRows$2(Dataset.scala:98)
        at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:827)
        at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:96)
        at 
org.apache.spark.sql.SparkSession.$anonfun$sql$1(SparkSession.scala:640)
        at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:827)
        at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:630)
        at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:662)
        at 
java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
        at 
java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
        at 
java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
        at java.base/java.lang.reflect.Method.invoke(Method.java:566)
        at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
        at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:374)
        at py4j.Gateway.invoke(Gateway.java:282)
        at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
        at py4j.commands.CallCommand.execute(CallCommand.java:79)
        at 
py4j.ClientServerConnection.waitForCommands(ClientServerConnection.java:182)
        at py4j.ClientServerConnection.run(ClientServerConnection.java:106)
        at java.base/java.lang.Thread.run(Thread.java:829)
   
   
   ​
   
   ```


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