[
https://issues.apache.org/jira/browse/SPARK-40602?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17612166#comment-17612166
]
zzzzming95 commented on SPARK-40602:
------------------------------------
It seems to be a problem with the hive metastore and S3. You can use the hive
client to execute SQL to further debug。
> RunTimeException for ETL job
> ----------------------------
>
> Key: SPARK-40602
> URL: https://issues.apache.org/jira/browse/SPARK-40602
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 2.4.5
> Reporter: Zhixian Hu
> Priority: Blocker
>
> pulling data from datalake on S3 and shows error below:
> Py4JJavaError: An error occurred while calling o666.save. :
> java.lang.RuntimeException: Caught Hive MetaException attempting to get
> partition metadata by filter from Hive. You can set the Spark configuration
> setting spark.sql.hive.manageFilesourcePartitions to false to work around
> this problem, however this will result in degraded performance. Please report
> a bug: https://issues.apache.org/jira/browse/SPARK at
> org.apache.spark.sql.hive.client.Shim_v0_13.getPartitionsByFilter(HiveShim.scala:785)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$getPartitionsByFilter$1.apply(HiveClientImpl.scala:791)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$getPartitionsByFilter$1.apply(HiveClientImpl.scala:789)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$withHiveState$1.apply(HiveClientImpl.scala:331)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$retryLocked$1.apply(HiveClientImpl.scala:239)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$retryLocked$1.apply(HiveClientImpl.scala:231)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl.synchronizeOnObject(HiveClientImpl.scala:275)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl.retryLocked(HiveClientImpl.scala:231)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl.withHiveState(HiveClientImpl.scala:314)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl.getPartitionsByFilter(HiveClientImpl.scala:789)
> at
> org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$listPartitionsByFilter$1.apply(HiveExternalCatalog.scala:1299)
> at
> org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$listPartitionsByFilter$1.apply(HiveExternalCatalog.scala:1292)
> at
> org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$withClient$1$$anonfun$apply$1.apply(HiveExternalCatalog.scala:144)
> at
> org.apache.spark.sql.hive.HiveExternalCatalog.org$apache$spark$sql$hive$HiveExternalCatalog$$maybeSynchronized(HiveExternalCatalog.scala:105)
> at
> org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$withClient$1.apply(HiveExternalCatalog.scala:142)
> at
> com.databricks.backend.daemon.driver.ProgressReporter$.withStatusCode(ProgressReporter.scala:372)
> at
> com.databricks.backend.daemon.driver.ProgressReporter$.withStatusCode(ProgressReporter.scala:358)
> at
> com.databricks.spark.util.SparkDatabricksProgressReporter$.withStatusCode(ProgressReporter.scala:34)
> at
> org.apache.spark.sql.hive.HiveExternalCatalog.withClient(HiveExternalCatalog.scala:140)
> at
> org.apache.spark.sql.hive.HiveExternalCatalog.listPartitionsByFilter(HiveExternalCatalog.scala:1292)
> at
> org.apache.spark.sql.catalyst.catalog.ExternalCatalogWithListener.listPartitionsByFilter(ExternalCatalogWithListener.scala:265)
> at
> org.apache.spark.sql.catalyst.catalog.SessionCatalog.listPartitionsByFilter(SessionCatalog.scala:1045)
> at
> org.apache.spark.sql.execution.datasources.CatalogFileIndex.filterPartitions(CatalogFileIndex.scala:73)
> at
> org.apache.spark.sql.execution.datasources.PruneFileSourcePartitions$$anonfun$apply$1.applyOrElse(PruneFileSourcePartitions.scala:62)
> at
> org.apache.spark.sql.execution.datasources.PruneFileSourcePartitions$$anonfun$apply$1.applyOrElse(PruneFileSourcePartitions.scala:27)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$2.apply(TreeNode.scala:279)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$2.apply(TreeNode.scala:279)
> at
> org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:76)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:278)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.org$apache$spark$sql$catalyst$plans$logical$AnalysisHelper$$super$transformDown(LogicalPlan.scala:29)
> at
> org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$class.transformDown(AnalysisHelper.scala:153)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDown(LogicalPlan.scala:29)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDown(LogicalPlan.scala:29)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:284)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:284)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$8.apply(TreeNode.scala:353)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:207)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:351)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:284)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.org$apache$spark$sql$catalyst$plans$logical$AnalysisHelper$$super$transformDown(LogicalPlan.scala:29)
> at
> org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$class.transformDown(AnalysisHelper.scala:153)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDown(LogicalPlan.scala:29)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDown(LogicalPlan.scala:29)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:284)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:284)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$8.apply(TreeNode.scala:353)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:207)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:351)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:284)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.org$apache$spark$sql$catalyst$plans$logical$AnalysisHelper$$super$transformDown(LogicalPlan.scala:29)
> at
> org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$class.transformDown(AnalysisHelper.scala:153)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDown(LogicalPlan.scala:29)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDown(LogicalPlan.scala:29)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:284)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:284)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$8.apply(TreeNode.scala:353)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:207)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:351)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:284)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.org$apache$spark$sql$catalyst$plans$logical$AnalysisHelper$$super$transformDown(LogicalPlan.scala:29)
> at
> org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$class.transformDown(AnalysisHelper.scala:153)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDown(LogicalPlan.scala:29)
> at
> org.apache.spark.sql.execution.datasources.PruneFileSourcePartitions$.apply(PruneFileSourcePartitions.scala:27)
> at
> org.apache.spark.sql.execution.datasources.PruneFileSourcePartitions$.apply(PruneFileSourcePartitions.scala:26)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:112)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:109)
> at
> scala.collection.IndexedSeqOptimized$class.foldl(IndexedSeqOptimized.scala:57)
> at
> scala.collection.IndexedSeqOptimized$class.foldLeft(IndexedSeqOptimized.scala:66)
> at scala.collection.mutable.WrappedArray.foldLeft(WrappedArray.scala:35) at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:109)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:101)
> at scala.collection.immutable.List.foreach(List.scala:392) at
> org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:101)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$executeAndTrack$1.apply(RuleExecutor.scala:80)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$executeAndTrack$1.apply(RuleExecutor.scala:80)
> at
> org.apache.spark.sql.catalyst.QueryPlanningTracker$.withTracker(QueryPlanningTracker.scala:88)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor.executeAndTrack(RuleExecutor.scala:79)
> at
> org.apache.spark.sql.execution.QueryExecution$$anonfun$optimizedPlan$1.apply(QueryExecution.scala:96)
> at
> org.apache.spark.sql.execution.QueryExecution$$anonfun$optimizedPlan$1.apply(QueryExecution.scala:96)
> at
> org.apache.spark.sql.catalyst.QueryPlanningTracker.measurePhase(QueryPlanningTracker.scala:111)
> at
> org.apache.spark.sql.execution.QueryExecution.optimizedPlan$lzycompute(QueryExecution.scala:95)
> at
> org.apache.spark.sql.execution.QueryExecution.optimizedPlan(QueryExecution.scala:95)
> at
> org.apache.spark.sql.execution.QueryExecution$$anonfun$sparkPlan$1.apply(QueryExecution.scala:100)
> at
> org.apache.spark.sql.execution.QueryExecution$$anonfun$sparkPlan$1.apply(QueryExecution.scala:100)
> at
> org.apache.spark.sql.catalyst.QueryPlanningTracker.measurePhase(QueryPlanningTracker.scala:111)
> at
> org.apache.spark.sql.execution.QueryExecution.sparkPlan$lzycompute(QueryExecution.scala:99)
> at
> org.apache.spark.sql.execution.QueryExecution.sparkPlan(QueryExecution.scala:99)
> at
> org.apache.spark.sql.execution.QueryExecution$$anonfun$executedPlan$1.apply(QueryExecution.scala:107)
> at
> org.apache.spark.sql.execution.QueryExecution$$anonfun$executedPlan$1.apply(QueryExecution.scala:106)
> at
> org.apache.spark.sql.catalyst.QueryPlanningTracker.measurePhase(QueryPlanningTracker.scala:111)
> at
> org.apache.spark.sql.execution.QueryExecution.executedPlan$lzycompute(QueryExecution.scala:106)
> at
> org.apache.spark.sql.execution.QueryExecution.executedPlan(QueryExecution.scala:106)
> at
> org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:117)
> at
> org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:115)
> at org.apache.spark.sql.Dataset.rdd$lzycompute(Dataset.scala:3138) at
> org.apache.spark.sql.Dataset.rdd(Dataset.scala:3136) at
> net.snowflake.spark.snowflake.SnowflakeWriter.dataFrameToRDD(SnowflakeWriter.scala:100)
> at
> net.snowflake.spark.snowflake.SnowflakeWriter.save(SnowflakeWriter.scala:77)
> at
> net.snowflake.spark.snowflake.DefaultSource.createRelation(DefaultSource.scala:144)
> at
> org.apache.spark.sql.execution.datasources.SaveIntoDataSourceCommand.run(SaveIntoDataSourceCommand.scala:45)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:70)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:68)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:86)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:152)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:140)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$5.apply(SparkPlan.scala:193)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
> at
> org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:189) at
> org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:140) at
> org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:117)
> at
> org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:115)
> at
> org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:711)
> at
> org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:711)
> at
> org.apache.spark.sql.execution.SQLExecution$$anonfun$withCustomExecutionEnv$1.apply(SQLExecution.scala:113)
> at
> org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:243)
> at
> org.apache.spark.sql.execution.SQLExecution$.withCustomExecutionEnv(SQLExecution.scala:99)
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:173)
> at
> org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:711) at
> org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:307)
> at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:293) 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:380) at
> py4j.Gateway.invoke(Gateway.java:295) at
> py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132) at
> py4j.commands.CallCommand.execute(CallCommand.java:79) at
> py4j.GatewayConnection.run(GatewayConnection.java:251) at
> java.lang.Thread.run(Thread.java:748) Caused by:
> java.lang.reflect.InvocationTargetException 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
> org.apache.spark.sql.hive.client.Shim_v0_13.getPartitionsByFilter(HiveShim.scala:772)
> ... 130 more Caused by: MetaException(message:Rate exceeded (Service:
> AWSGlue; Status Code: 400; Error Code: ThrottlingException; Request ID:
> 1f2337a6-71ab-44e2-a26d-3b87d2f3c3f7)) at
> com.amazonaws.glue.catalog.converters.CatalogToHiveConverter.getHiveException(CatalogToHiveConverter.java:100)
> at
> com.amazonaws.glue.catalog.converters.CatalogToHiveConverter.wrapInHiveException(CatalogToHiveConverter.java:88)
> at
> com.amazonaws.glue.catalog.metastore.GlueMetastoreClientDelegate.getCatalogPartitions(GlueMetastoreClientDelegate.java:1042)
> at
> com.amazonaws.glue.catalog.metastore.GlueMetastoreClientDelegate.access$200(GlueMetastoreClientDelegate.java:141)
> at
> com.amazonaws.glue.catalog.metastore.GlueMetastoreClientDelegate$3.call(GlueMetastoreClientDelegate.java:987)
> at
> com.amazonaws.glue.catalog.metastore.GlueMetastoreClientDelegate$3.call(GlueMetastoreClientDelegate.java:984)
> at java.util.concurrent.FutureTask.run(FutureTask.java:266) at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
> ... 1 more
--
This message was sent by Atlassian Jira
(v8.20.10#820010)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
