Unable to alter column name for a Hudi table in AWS

I am getting an error while I was trying to rename the column in the hudi table

`
%etl
%session_id_prefix native-hudi-dataframe-
%glue_version 3.0
%idle_timeout 2880
%worker_type G.2X
%number_of_workers 20
%%configure
{
"--conf": "spark.serializer=org.apache.spark.serializer.KryoSerializer --conf spark.sql.hive.convertMetastoreParquet=false --conf spark.sql.catalog.spark_catalog=org.apache.spark.sql.hudi.catalog.HoodieCatalog --conf spark.sql.legacy.pathOptionBehavior.enabled= true --conf spark.sql.extensions= org.apache.spark.sql.hudi.HoodieSparkSessionExtension",
"--datalake-formats": "hudi",
"--enable-metrics": "true",
"--enable-spark-ui": "true",
"--spark-event-logs-path": "s3://aws-glue-assets-441369475256-us-west-1/sparkHistoryLogs/",
"--enable-job-insights": "true",
"--enable-glue-datacatalog": "true",
"--enable-continuous-cloudwatch-log": "true",
"--job-bookmark-option": "job-bookmark-disable"
}

import logging
import sys
from awsglue.transforms import *
from awsglue.utils import getResolvedOptions
from pyspark.context import SparkContext
from awsglue.context import GlueContext
from awsglue.job import Job
from awsglue.dynamicframe import DynamicFrame

sc = SparkContext.getOrCreate()
glueContext = GlueContext(sc)
spark = glueContext.spark_session
job = Job(glueContext)
logger = glueContext.get_logger()

db_name = "dev_mesh"
table_name_test = "data_quality_pass_results"
query = f"ALTER TABLE {db_name}.{table_name_test} RENAME COLUMN PartialPaymentLetterOfExpalnDate TO PartialPaymentLetterOfExplanDate"
spark.sql(query)
print(f"Query Executed: {query}")

print_hudi_table(BUCKET=BUCKET)`

`Py4JJavaError: An error occurred while calling o97.sql. : org.apache.spark.SparkException: Cannot find catalog plugin class for catalog 'spark_catalog': org.apache.spark.sql.hudi.catalog.HoodieCatalog at org.apache.spark.sql.connector.catalog.Catalogs$.load(Catalogs.scala:66) at org.apache.spark.sql.connector.catalog.CatalogManager.loadV2SessionCatalog(CatalogManager.scala:66) at org.apache.spark.sql.connector.catalog.CatalogManager.$anonfun$v2SessionCatalog$2(CatalogManager.scala:85) at scala.collection.mutable.HashMap.getOrElseUpdate(HashMap.scala:82) at org.apache.spark.sql.connector.catalog.CatalogManager.$anonfun$v2SessionCatalog$1(CatalogManager.scala:85) at scala.Option.map(Option.scala:146) at org.apache.spark.sql.connector.catalog.CatalogManager.v2SessionCatalog(CatalogManager.scala:84) at org.apache.spark.sql.connector.catalog.CatalogManager.catalog(CatalogManager.scala:50) at org.apache.spark.sql.connector.catalog.CatalogManager.currentCatalog(CatalogManager.scala:117) at org.apache.spark.sql.connector.catalog.LookupCatalog.currentCatalog(LookupCatalog.scala:35) at org.apache.spark.sql.connector.catalog.LookupCatalog.currentCatalog$(LookupCatalog.scala:35) at org.apache.spark.sql.catalyst.analysis.ResolveCatalogs.currentCatalog(ResolveCatalogs.scala:29) at org.apache.spark.sql.connector.catalog.LookupCatalog$CatalogAndIdentifier$.unapply(LookupCatalog.scala:131) at org.apache.spark.sql.connector.catalog.LookupCatalog$NonSessionCatalogAndIdentifier$.unapply(LookupCatalog.scala:78) at org.apache.spark.sql.catalyst.analysis.ResolveCatalogs$NonSessionCatalogAndTable$.unapply(ResolveCatalogs.scala:220) at org.apache.spark.sql.catalyst.analysis.ResolveCatalogs$$anonfun$apply$1.applyOrElse(ResolveCatalogs.scala:93) at org.apache.spark.sql.catalyst.analysis.ResolveCatalogs$$anonfun$apply$1.applyOrElse(ResolveCatalogs.scala:34) at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.$anonfun$resolveOperatorsDown$2(AnalysisHelper.scala:108) at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:74) at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.$anonfun$resolveOperatorsDown$1(AnalysisHelper.scala:108) at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$.allowInvokingTransformsInAnalyzer(AnalysisHelper.scala:221) at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.resolveOperatorsDown(AnalysisHelper.scala:106) at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.resolveOperatorsDown$(AnalysisHelper.scala:104) at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperatorsDown(LogicalPlan.scala:29) at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.resolveOperators(AnalysisHelper.scala:73) at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.resolveOperators$(AnalysisHelper.scala:72) at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperators(LogicalPlan.scala:29) at org.apache.spark.sql.catalyst.analysis.ResolveCatalogs.apply(ResolveCatalogs.scala:34) at org.apache.spark.sql.catalyst.analysis.ResolveCatalogs.apply(ResolveCatalogs.scala:29) at org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$execute$2(RuleExecutor.scala:216) at scala.collection.LinearSeqOptimized.foldLeft(LinearSeqOptimized.scala:122) at scala.collection.LinearSeqOptimized.foldLeft$(LinearSeqOptimized.scala:118) at scala.collection.immutable.List.foldLeft(List.scala:85) at org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$execute$1(RuleExecutor.scala:213) at org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$execute$1$adapted(RuleExecutor.scala:205) at scala.collection.immutable.List.foreach(List.scala:388) at org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:205) at org.apache.spark.sql.catalyst.analysis.Analyzer.org$apache$spark$sql$catalyst$analysis$Analyzer$$executeSameContext(Analyzer.scala:196) at org.apache.spark.sql.catalyst.analysis.Analyzer.execute(Analyzer.scala:190) at org.apache.spark.sql.catalyst.analysis.Analyzer.execute(Analyzer.scala:155) at org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$executeAndTrack$1(RuleExecutor.scala:183) at org.apache.spark.sql.catalyst.QueryPlanningTracker$.withTracker(QueryPlanningTracker.scala:107) at org.apache.spark.sql.catalyst.rules.RuleExecutor.executeAndTrack(RuleExecutor.scala:183) at org.apache.spark.sql.catalyst.analysis.Analyzer.$anonfun$executeAndCheck$1(Analyzer.scala:174) at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$.markInAnalyzer(AnalysisHelper.scala:228) at org.apache.spark.sql.catalyst.analysis.Analyzer.executeAndCheck(Analyzer.scala:173) at org.apache.spark.sql.execution.QueryExecution.$anonfun$analyzed$1(QueryExecution.scala:73) at org.apache.spark.sql.catalyst.QueryPlanningTracker.measurePhase(QueryPlanningTracker.scala:192) at org.apache.spark.sql.execution.QueryExecution.$anonfun$executePhase$1(QueryExecution.scala:163) at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:772) at org.apache.spark.sql.execution.QueryExecution.executePhase(QueryExecution.scala:163) at org.apache.spark.sql.execution.QueryExecution.analyzed$lzycompute(QueryExecution.scala:73) at org.apache.spark.sql.execution.QueryExecution.analyzed(QueryExecution.scala:71) at org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:63) at org.apache.spark.sql.Dataset$.$anonfun$ofRows$2(Dataset.scala:99) at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:772) at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:97) at org.apache.spark.sql.SparkSession.$anonfun$sql$1(SparkSession.scala:615) at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:772) at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:610) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:498) at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244) at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357) 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.GatewayConnection.run(GatewayConnection.java:238) at java.lang.Thread.run(Thread.java:750)`

Start with the AWS Glue 3.0 configuration, the Spark session settings, and the ALTER TABLE statement shown in the report. Reproduce the catalog plugin error and determine whether the Hudi catalog can support this column rename in that environment; the issue is done when the supported behavior or required configuration is established.

Written by the indexing model from the issue text.