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https://issues.apache.org/jira/browse/SPARK-27421?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Shivu Sondur updated SPARK-27421:
---------------------------------
Comment: was deleted
(was: i am checking this issue)
> RuntimeException when querying a view on a partitioned parquet table
> --------------------------------------------------------------------
>
> Key: SPARK-27421
> URL: https://issues.apache.org/jira/browse/SPARK-27421
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 2.4.0, 2.4.1
> Environment: Using Scala version 2.11.12 (Java HotSpot(TM) 64-Bit
> Server VM, Java 1.8.0_141)
> Reporter: Eric Maynard
> Priority: Minor
>
> When running a simple query, I get the following stacktrace:
> {code}
> 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:772)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$getPartitionsByFilter$1.apply(HiveClientImpl.scala:686)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$getPartitionsByFilter$1.apply(HiveClientImpl.scala:684)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$withHiveState$1.apply(HiveClientImpl.scala:283)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl.liftedTree1$1(HiveClientImpl.scala:221)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl.retryLocked(HiveClientImpl.scala:220)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl.withHiveState(HiveClientImpl.scala:266)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl.getPartitionsByFilter(HiveClientImpl.scala:684)
> at
> org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$listPartitionsByFilter$1.apply(HiveExternalCatalog.scala:1268)
> at
> org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$listPartitionsByFilter$1.apply(HiveExternalCatalog.scala:1261)
> at
> org.apache.spark.sql.hive.HiveExternalCatalog.withClient(HiveExternalCatalog.scala:99)
> at
> org.apache.spark.sql.hive.HiveExternalCatalog.listPartitionsByFilter(HiveExternalCatalog.scala:1261)
> at
> org.apache.spark.sql.catalyst.catalog.ExternalCatalogWithListener.listPartitionsByFilter(ExternalCatalogWithListener.scala:262)
> at
> org.apache.spark.sql.catalyst.catalog.SessionCatalog.listPartitionsByFilter(SessionCatalog.scala:957)
> at
> org.apache.spark.sql.execution.datasources.CatalogFileIndex.filterPartitions(CatalogFileIndex.scala:73)
> at
> org.apache.spark.sql.execution.datasources.PruneFileSourcePartitions$$anonfun$apply$1.applyOrElse(PruneFileSourcePartitions.scala:63)
> 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:256)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$2.apply(TreeNode.scala:256)
> at
> org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:70)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:255)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.org$apache$spark$sql$catalyst$plans$logical$AnalysisHelper$$super$transformDown(LogicalPlan.scala:29)
> at
> org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$class.transformDown(AnalysisHelper.scala:149)
> 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:87)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:84)
> at
> scala.collection.IndexedSeqOptimized$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$$anonfun$execute$1.apply(RuleExecutor.scala:84)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:76)
> at scala.collection.immutable.List.foreach(List.scala:392)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:76)
> at
> org.apache.spark.sql.execution.QueryExecution.optimizedPlan$lzycompute(QueryExecution.scala:66)
> at
> org.apache.spark.sql.execution.QueryExecution.optimizedPlan(QueryExecution.scala:66)
> at
> org.apache.spark.sql.execution.QueryExecution.sparkPlan$lzycompute(QueryExecution.scala:72)
> at
> org.apache.spark.sql.execution.QueryExecution.sparkPlan(QueryExecution.scala:68)
> at
> org.apache.spark.sql.execution.QueryExecution.executedPlan$lzycompute(QueryExecution.scala:77)
> at
> org.apache.spark.sql.execution.QueryExecution.executedPlan(QueryExecution.scala:77)
> at
> org.apache.spark.sql.execution.QueryExecution$$anonfun$simpleString$1.apply(QueryExecution.scala:188)
> at
> org.apache.spark.sql.execution.QueryExecution$$anonfun$simpleString$1.apply(QueryExecution.scala:188)
> at
> org.apache.spark.sql.execution.QueryExecution.stringOrError(QueryExecution.scala:99)
> at
> org.apache.spark.sql.execution.QueryExecution.simpleString(QueryExecution.scala:188)
> at
> org.apache.spark.sql.execution.command.ExplainCommand.run(commands.scala:171)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:70)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:68)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.executeCollect(commands.scala:79)
> at org.apache.spark.sql.Dataset.explain(Dataset.scala:484)
> at org.apache.spark.sql.Dataset.explain(Dataset.scala:497)
> ... 49 elided
> Caused by: java.lang.reflect.InvocationTargetException:
> org.apache.hadoop.hive.metastore.api.MetaException: Filtering is supported
> only on partition keys of type string
> 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:759)
> ... 99 more
> Caused by: org.apache.hadoop.hive.metastore.api.MetaException: Filtering is
> supported only on partition keys of type string
> at
> org.apache.hadoop.hive.metastore.api.ThriftHiveMetastore$get_partitions_by_filter_result$get_partitions_by_filter_resultStandardScheme.read(ThriftHiveMetastore.java)
> at
> org.apache.hadoop.hive.metastore.api.ThriftHiveMetastore$get_partitions_by_filter_result$get_partitions_by_filter_resultStandardScheme.read(ThriftHiveMetastore.java)
> at
> org.apache.hadoop.hive.metastore.api.ThriftHiveMetastore$get_partitions_by_filter_result.read(ThriftHiveMetastore.java)
> at org.apache.thrift.TServiceClient.receiveBase(TServiceClient.java:86)
> at
> org.apache.hadoop.hive.metastore.api.ThriftHiveMetastore$Client.recv_get_partitions_by_filter(ThriftHiveMetastore.java:2514)
> at
> org.apache.hadoop.hive.metastore.api.ThriftHiveMetastore$Client.get_partitions_by_filter(ThriftHiveMetastore.java:2498)
> at
> org.apache.hadoop.hive.metastore.HiveMetaStoreClient.listPartitionsByFilter(HiveMetaStoreClient.java:1453)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at
> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
> at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:498)
> at
> org.apache.hadoop.hive.metastore.RetryingMetaStoreClient.invoke(RetryingMetaStoreClient.java:154)
> at com.sun.proxy.$Proxy33.listPartitionsByFilter(Unknown Source)
> 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.hadoop.hive.metastore.HiveMetaStoreClient$SynchronizedHandler.invoke(HiveMetaStoreClient.java:2562)
> at com.sun.proxy.$Proxy33.listPartitionsByFilter(Unknown Source)
> at
> org.apache.hadoop.hive.ql.metadata.Hive.getPartitionsByFilter(Hive.java:2820)
> ... 104 more
> {code}
> I can replicate the issue with the following:
> {code:java}
> spark.sql("CREATE table test (name STRING) partitioned by (id int) STORED AS
> PARQUET")
> spark.sql("CREATE VIEW test_view as select cast(id as string) as id, name
> from test")
> spark.sql("SELECT * FROM test_view WHERE id = '0'").explain
> {code}
> If we use a table which isn't stored as parquet, there appears to be no issue:
> {code:java}
> spark.sql("CREATE table test (name STRING) partitioned by (id int)")
> spark.sql("CREATE VIEW test_view as select cast(id as string) as id, name
> from test")
> spark.sql("SELECT * FROM test_view WHERE id = '0'").explain
> {code}
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