[jira] [Updated] (SPARK-34631) Caught Hive MetaException when query by partition (partition col start with ‘$’)
[
https://issues.apache.org/jira/browse/SPARK-34631?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Kent Yao updated SPARK-34631:
-
Description:
emphasized textcreate a table, set location as parquet, do msck repair table to
get the data.
But when query with partition column, got some errors (adding backtick would
not help)
{code:java}
// code placeholder
{code}
select count from some_table where `$partition_date` = '2015-01-01'
{panel:title=error:}
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$$anonfun$getPartitionsByFilter$1.apply(HiveClientImpl.scala:679)
at
org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$getPartitionsByFilter$1.apply(HiveClientImpl.scala:677)
at
org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$withHiveState$1.apply(HiveClientImpl.scala:275)
at
org.apache.spark.sql.hive.client.HiveClientImpl.liftedTree1$1(HiveClientImpl.scala:213)
at
org.apache.spark.sql.hive.client.HiveClientImpl.retryLocked(HiveClientImpl.scala:212)
at
org.apache.spark.sql.hive.client.HiveClientImpl.withHiveState(HiveClientImpl.scala:258)
at
org.apache.spark.sql.hive.client.HiveClientImpl.getPartitionsByFilter(HiveClientImpl.scala:677)
at
org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$listPartitionsByFilter$1.apply(HiveExternalCatalog.scala:1221)
at
org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$listPartitionsByFilter$1.apply(HiveExternalCatalog.scala:1214)
at
org.apache.spark.sql.hive.HiveExternalCatalog.withClient(HiveExternalCatalog.scala:97)
at
org.apache.spark.sql.hive.HiveExternalCatalog.listPartitionsByFilter(HiveExternalCatalog.scala:1214)
at
org.apache.spark.sql.catalyst.catalog.ExternalCatalogWithListener.listPartitionsByFilter(ExternalCatalogWithListener.scala:254)
at
org.apache.spark.sql.catalyst.catalog.SessionCatalog.listPartitionsByFilter(SessionCatalog.scala:962)
at
org.apache.spark.sql.hive.execution.HiveTableScanExec.rawPartitions$lzycompute(HiveTableScanExec.scala:174)
at
org.apache.spark.sql.hive.execution.HiveTableScanExec.rawPartitions(HiveTableScanExec.scala:166)
at
org.apache.spark.sql.hive.execution.HiveTableScanExec$$anonfun$11.apply(HiveTableScanExec.scala:192)
at
org.apache.spark.sql.hive.execution.HiveTableScanExec$$anonfun$11.apply(HiveTableScanExec.scala:192)
at org.apache.spark.util.Utils$.withDummyCallSite(Utils.scala:2470)
at
org.apache.spark.sql.hive.execution.HiveTableScanExec.doExecute(HiveTableScanExec.scala:191)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
at
org.apache.spark.sql.execution.SparkPlan.getByteArrayRdd(SparkPlan.scala:247)
at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:339)
at
org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:38)
at
org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collectFromPlan(Dataset.scala:3389)
at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2550)
at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2550)
at org.apache.spark.sql.Dataset$$anonfun$52.apply(Dataset.scala:3370)
at
org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:78)
at
org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:125)
at
org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:73)
at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3369)
at org.apache.spark.sql.Dataset.head(Dataset.scala:2550)
at org.apache.spark.sql.Dataset.take(Dataset.scala:2764)
at org.apache.spark.sql.Dataset.getRows(Dataset.scala:254)
at org.apache.spark.sql.Dataset.showString(Dataset.scala:291)
at org.apache.spark.sql.Dataset.show(Dataset.scala:751)
at org.apache.spark.sql.Dataset.show(Dataset.scala:710)
at org.apache.spark.sql.Dataset.show(Dataset.scala:719)
... 49 elided
Caused by: java.lang.reflect.InvocationTargetException:
org.apache.hadoop.hive.metastore.api.MetaException: Error parsing partition
filter : line 1:0 no
[jira] [Updated] (SPARK-34631) Caught Hive MetaException when query by partition (partition col start with ‘$’)
[
https://issues.apache.org/jira/browse/SPARK-34631?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
zhouyuan updated SPARK-34631:
-
Component/s: DStreams
> Caught Hive MetaException when query by partition (partition col start with
> ‘$’)
>
>
> Key: SPARK-34631
> URL: https://issues.apache.org/jira/browse/SPARK-34631
> Project: Spark
> Issue Type: Bug
> Components: DStreams, Java API
>Affects Versions: 2.4.4
>Reporter: zhouyuan
>Priority: Major
>
> create a table, set location as parquet, do msck repair table to get the data.
> But when query with partition column, got some errors (adding backtick would
> not help)
> {code:java}
> // code placeholder
> {code}
> select count from some_table where `$partition_date` = '2015-01-01'
>
> {panel:title=error:}
> 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:679)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$getPartitionsByFilter$1.apply(HiveClientImpl.scala:677)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$withHiveState$1.apply(HiveClientImpl.scala:275)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl.liftedTree1$1(HiveClientImpl.scala:213)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl.retryLocked(HiveClientImpl.scala:212)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl.withHiveState(HiveClientImpl.scala:258)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl.getPartitionsByFilter(HiveClientImpl.scala:677)
> at
> org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$listPartitionsByFilter$1.apply(HiveExternalCatalog.scala:1221)
> at
> org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$listPartitionsByFilter$1.apply(HiveExternalCatalog.scala:1214)
> at
> org.apache.spark.sql.hive.HiveExternalCatalog.withClient(HiveExternalCatalog.scala:97)
> at
> org.apache.spark.sql.hive.HiveExternalCatalog.listPartitionsByFilter(HiveExternalCatalog.scala:1214)
> at
> org.apache.spark.sql.catalyst.catalog.ExternalCatalogWithListener.listPartitionsByFilter(ExternalCatalogWithListener.scala:254)
> at
> org.apache.spark.sql.catalyst.catalog.SessionCatalog.listPartitionsByFilter(SessionCatalog.scala:962)
> at
> org.apache.spark.sql.hive.execution.HiveTableScanExec.rawPartitions$lzycompute(HiveTableScanExec.scala:174)
> at
> org.apache.spark.sql.hive.execution.HiveTableScanExec.rawPartitions(HiveTableScanExec.scala:166)
> at
> org.apache.spark.sql.hive.execution.HiveTableScanExec$$anonfun$11.apply(HiveTableScanExec.scala:192)
> at
> org.apache.spark.sql.hive.execution.HiveTableScanExec$$anonfun$11.apply(HiveTableScanExec.scala:192)
> at org.apache.spark.util.Utils$.withDummyCallSite(Utils.scala:2470)
> at
> org.apache.spark.sql.hive.execution.HiveTableScanExec.doExecute(HiveTableScanExec.scala:191)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
> at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
> at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
> at
> org.apache.spark.sql.execution.SparkPlan.getByteArrayRdd(SparkPlan.scala:247)
> at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:339)
> at
> org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:38)
> at
> org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collectFromPlan(Dataset.scala:3389)
> at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2550)
> at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2550)
> at org.apache.spark.sql.Dataset$$anonfun$52.apply(Dataset.scala:3370)
> at
> org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:78)
> at
> org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:125)
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:73)
> at
[jira] [Updated] (SPARK-34631) Caught Hive MetaException when query by partition (partition col start with ‘$’)
[
https://issues.apache.org/jira/browse/SPARK-34631?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
zhouyuan updated SPARK-34631:
-
Priority: Critical (was: Major)
> Caught Hive MetaException when query by partition (partition col start with
> ‘$’)
>
>
> Key: SPARK-34631
> URL: https://issues.apache.org/jira/browse/SPARK-34631
> Project: Spark
> Issue Type: Bug
> Components: DStreams, Java API
>Affects Versions: 2.4.4
>Reporter: zhouyuan
>Priority: Critical
>
> create a table, set location as parquet, do msck repair table to get the data.
> But when query with partition column, got some errors (adding backtick would
> not help)
> {code:java}
> // code placeholder
> {code}
> select count from some_table where `$partition_date` = '2015-01-01'
>
> {panel:title=error:}
> 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$$anonfun$getPartitionsByFilter$1.apply(HiveClientImpl.scala:679)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$getPartitionsByFilter$1.apply(HiveClientImpl.scala:677)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$withHiveState$1.apply(HiveClientImpl.scala:275)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl.liftedTree1$1(HiveClientImpl.scala:213)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl.retryLocked(HiveClientImpl.scala:212)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl.withHiveState(HiveClientImpl.scala:258)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl.getPartitionsByFilter(HiveClientImpl.scala:677)
> at
> org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$listPartitionsByFilter$1.apply(HiveExternalCatalog.scala:1221)
> at
> org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$listPartitionsByFilter$1.apply(HiveExternalCatalog.scala:1214)
> at
> org.apache.spark.sql.hive.HiveExternalCatalog.withClient(HiveExternalCatalog.scala:97)
> at
> org.apache.spark.sql.hive.HiveExternalCatalog.listPartitionsByFilter(HiveExternalCatalog.scala:1214)
> at
> org.apache.spark.sql.catalyst.catalog.ExternalCatalogWithListener.listPartitionsByFilter(ExternalCatalogWithListener.scala:254)
> at
> org.apache.spark.sql.catalyst.catalog.SessionCatalog.listPartitionsByFilter(SessionCatalog.scala:962)
> at
> org.apache.spark.sql.hive.execution.HiveTableScanExec.rawPartitions$lzycompute(HiveTableScanExec.scala:174)
> at
> org.apache.spark.sql.hive.execution.HiveTableScanExec.rawPartitions(HiveTableScanExec.scala:166)
> at
> org.apache.spark.sql.hive.execution.HiveTableScanExec$$anonfun$11.apply(HiveTableScanExec.scala:192)
> at
> org.apache.spark.sql.hive.execution.HiveTableScanExec$$anonfun$11.apply(HiveTableScanExec.scala:192)
> at org.apache.spark.util.Utils$.withDummyCallSite(Utils.scala:2470)
> at
> org.apache.spark.sql.hive.execution.HiveTableScanExec.doExecute(HiveTableScanExec.scala:191)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
> at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
> at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
> at
> org.apache.spark.sql.execution.SparkPlan.getByteArrayRdd(SparkPlan.scala:247)
> at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:339)
> at
> org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:38)
> at
> org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collectFromPlan(Dataset.scala:3389)
> at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2550)
> at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2550)
> at org.apache.spark.sql.Dataset$$anonfun$52.apply(Dataset.scala:3370)
> at
> org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:78)
> at
> org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:125)
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:73)
> at
[jira] [Updated] (SPARK-34631) Caught Hive MetaException when query by partition (partition col start with ‘$’)
[
https://issues.apache.org/jira/browse/SPARK-34631?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Hyukjin Kwon updated SPARK-34631:
-
Priority: Major (was: Blocker)
> Caught Hive MetaException when query by partition (partition col start with
> ‘$’)
>
>
> Key: SPARK-34631
> URL: https://issues.apache.org/jira/browse/SPARK-34631
> Project: Spark
> Issue Type: Bug
> Components: Java API
>Affects Versions: 2.4.4
>Reporter: zhouyuan
>Priority: Major
>
> create a table, set location as parquet, do msck repair table to get the data.
> But when query with partition column, got some errors (adding backtick would
> not help)
> {code:java}
> // code placeholder
> {code}
> select count from some_table where `$partition_date` = '2015-01-01'
>
> {panel:title=error:}
> java.lang.RuntimeException: Caught Hive MetaException attempting to get
> partition metadata by filter from Hive. You can set the Spark configuration
> setting spark.sql.hive.manageFilesourcePartitions to false to work around
> this problem, however this will result in degraded performance. Please report
> a bug: https://issues.apache.org/jira/browse/SPARK
> at
> org.apache.spark.sql.hive.client.Shim_v0_13.getPartitionsByFilter(HiveShim.scala:772)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$getPartitionsByFilter$1.apply(HiveClientImpl.scala:679)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$getPartitionsByFilter$1.apply(HiveClientImpl.scala:677)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$withHiveState$1.apply(HiveClientImpl.scala:275)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl.liftedTree1$1(HiveClientImpl.scala:213)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl.retryLocked(HiveClientImpl.scala:212)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl.withHiveState(HiveClientImpl.scala:258)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl.getPartitionsByFilter(HiveClientImpl.scala:677)
> at
> org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$listPartitionsByFilter$1.apply(HiveExternalCatalog.scala:1221)
> at
> org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$listPartitionsByFilter$1.apply(HiveExternalCatalog.scala:1214)
> at
> org.apache.spark.sql.hive.HiveExternalCatalog.withClient(HiveExternalCatalog.scala:97)
> at
> org.apache.spark.sql.hive.HiveExternalCatalog.listPartitionsByFilter(HiveExternalCatalog.scala:1214)
> at
> org.apache.spark.sql.catalyst.catalog.ExternalCatalogWithListener.listPartitionsByFilter(ExternalCatalogWithListener.scala:254)
> at
> org.apache.spark.sql.catalyst.catalog.SessionCatalog.listPartitionsByFilter(SessionCatalog.scala:962)
> at
> org.apache.spark.sql.hive.execution.HiveTableScanExec.rawPartitions$lzycompute(HiveTableScanExec.scala:174)
> at
> org.apache.spark.sql.hive.execution.HiveTableScanExec.rawPartitions(HiveTableScanExec.scala:166)
> at
> org.apache.spark.sql.hive.execution.HiveTableScanExec$$anonfun$11.apply(HiveTableScanExec.scala:192)
> at
> org.apache.spark.sql.hive.execution.HiveTableScanExec$$anonfun$11.apply(HiveTableScanExec.scala:192)
> at org.apache.spark.util.Utils$.withDummyCallSite(Utils.scala:2470)
> at
> org.apache.spark.sql.hive.execution.HiveTableScanExec.doExecute(HiveTableScanExec.scala:191)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
> at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
> at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
> at
> org.apache.spark.sql.execution.SparkPlan.getByteArrayRdd(SparkPlan.scala:247)
> at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:339)
> at
> org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:38)
> at
> org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collectFromPlan(Dataset.scala:3389)
> at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2550)
> at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2550)
> at org.apache.spark.sql.Dataset$$anonfun$52.apply(Dataset.scala:3370)
> at
> org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:78)
> at
> org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:125)
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:73)
> at
[jira] [Updated] (SPARK-34631) Caught Hive MetaException when query by partition (partition col start with ‘$’)
[
https://issues.apache.org/jira/browse/SPARK-34631?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Yuming Wang updated SPARK-34631:
Fix Version/s: (was: 2.4.4)
> Caught Hive MetaException when query by partition (partition col start with
> ‘$’)
>
>
> Key: SPARK-34631
> URL: https://issues.apache.org/jira/browse/SPARK-34631
> Project: Spark
> Issue Type: Bug
> Components: Java API
>Affects Versions: 2.4.4
>Reporter: zhouyuan
>Priority: Blocker
>
> create a table, set location as parquet, do msck repair table to get the data.
> But when query with partition column, got some errors (adding backtick would
> not help)
> {code:java}
> // code placeholder
> {code}
> select count from some_table where `$partition_date` = '2015-01-01'
>
> {panel:title=error:}
> 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$$anonfun$getPartitionsByFilter$1.apply(HiveClientImpl.scala:679)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$getPartitionsByFilter$1.apply(HiveClientImpl.scala:677)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$withHiveState$1.apply(HiveClientImpl.scala:275)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl.liftedTree1$1(HiveClientImpl.scala:213)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl.retryLocked(HiveClientImpl.scala:212)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl.withHiveState(HiveClientImpl.scala:258)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl.getPartitionsByFilter(HiveClientImpl.scala:677)
> at
> org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$listPartitionsByFilter$1.apply(HiveExternalCatalog.scala:1221)
> at
> org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$listPartitionsByFilter$1.apply(HiveExternalCatalog.scala:1214)
> at
> org.apache.spark.sql.hive.HiveExternalCatalog.withClient(HiveExternalCatalog.scala:97)
> at
> org.apache.spark.sql.hive.HiveExternalCatalog.listPartitionsByFilter(HiveExternalCatalog.scala:1214)
> at
> org.apache.spark.sql.catalyst.catalog.ExternalCatalogWithListener.listPartitionsByFilter(ExternalCatalogWithListener.scala:254)
> at
> org.apache.spark.sql.catalyst.catalog.SessionCatalog.listPartitionsByFilter(SessionCatalog.scala:962)
> at
> org.apache.spark.sql.hive.execution.HiveTableScanExec.rawPartitions$lzycompute(HiveTableScanExec.scala:174)
> at
> org.apache.spark.sql.hive.execution.HiveTableScanExec.rawPartitions(HiveTableScanExec.scala:166)
> at
> org.apache.spark.sql.hive.execution.HiveTableScanExec$$anonfun$11.apply(HiveTableScanExec.scala:192)
> at
> org.apache.spark.sql.hive.execution.HiveTableScanExec$$anonfun$11.apply(HiveTableScanExec.scala:192)
> at org.apache.spark.util.Utils$.withDummyCallSite(Utils.scala:2470)
> at
> org.apache.spark.sql.hive.execution.HiveTableScanExec.doExecute(HiveTableScanExec.scala:191)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
> at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
> at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
> at
> org.apache.spark.sql.execution.SparkPlan.getByteArrayRdd(SparkPlan.scala:247)
> at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:339)
> at
> org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:38)
> at
> org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collectFromPlan(Dataset.scala:3389)
> at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2550)
> at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2550)
> at org.apache.spark.sql.Dataset$$anonfun$52.apply(Dataset.scala:3370)
> at
> org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:78)
> at
> org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:125)
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:73)
> at
[jira] [Updated] (SPARK-34631) Caught Hive MetaException when query by partition (partition col start with ‘$’)
[
https://issues.apache.org/jira/browse/SPARK-34631?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Yuming Wang updated SPARK-34631:
Target Version/s: (was: 2.4.4)
> Caught Hive MetaException when query by partition (partition col start with
> ‘$’)
>
>
> Key: SPARK-34631
> URL: https://issues.apache.org/jira/browse/SPARK-34631
> Project: Spark
> Issue Type: Bug
> Components: Java API
>Affects Versions: 2.4.4
>Reporter: zhouyuan
>Priority: Blocker
> Fix For: 2.4.4
>
>
> create a table, set location as parquet, do msck repair table to get the data.
> But when query with partition column, got some errors (adding backtick would
> not help)
> {code:java}
> // code placeholder
> {code}
> select count from some_table where `$partition_date` = '2015-01-01'
>
> {panel:title=error:}
> java.lang.RuntimeException: Caught Hive MetaException attempting to get
> partition metadata by filter from Hive. You can set the Spark configuration
> setting spark.sql.hive.manageFilesourcePartitions to false to work around
> this problem, however this will result in degraded performance. Please report
> a bug: https://issues.apache.org/jira/browse/SPARK
> at
> org.apache.spark.sql.hive.client.Shim_v0_13.getPartitionsByFilter(HiveShim.scala:772)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$getPartitionsByFilter$1.apply(HiveClientImpl.scala:679)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$getPartitionsByFilter$1.apply(HiveClientImpl.scala:677)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$withHiveState$1.apply(HiveClientImpl.scala:275)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl.liftedTree1$1(HiveClientImpl.scala:213)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl.retryLocked(HiveClientImpl.scala:212)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl.withHiveState(HiveClientImpl.scala:258)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl.getPartitionsByFilter(HiveClientImpl.scala:677)
> at
> org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$listPartitionsByFilter$1.apply(HiveExternalCatalog.scala:1221)
> at
> org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$listPartitionsByFilter$1.apply(HiveExternalCatalog.scala:1214)
> at
> org.apache.spark.sql.hive.HiveExternalCatalog.withClient(HiveExternalCatalog.scala:97)
> at
> org.apache.spark.sql.hive.HiveExternalCatalog.listPartitionsByFilter(HiveExternalCatalog.scala:1214)
> at
> org.apache.spark.sql.catalyst.catalog.ExternalCatalogWithListener.listPartitionsByFilter(ExternalCatalogWithListener.scala:254)
> at
> org.apache.spark.sql.catalyst.catalog.SessionCatalog.listPartitionsByFilter(SessionCatalog.scala:962)
> at
> org.apache.spark.sql.hive.execution.HiveTableScanExec.rawPartitions$lzycompute(HiveTableScanExec.scala:174)
> at
> org.apache.spark.sql.hive.execution.HiveTableScanExec.rawPartitions(HiveTableScanExec.scala:166)
> at
> org.apache.spark.sql.hive.execution.HiveTableScanExec$$anonfun$11.apply(HiveTableScanExec.scala:192)
> at
> org.apache.spark.sql.hive.execution.HiveTableScanExec$$anonfun$11.apply(HiveTableScanExec.scala:192)
> at org.apache.spark.util.Utils$.withDummyCallSite(Utils.scala:2470)
> at
> org.apache.spark.sql.hive.execution.HiveTableScanExec.doExecute(HiveTableScanExec.scala:191)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
> at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
> at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
> at
> org.apache.spark.sql.execution.SparkPlan.getByteArrayRdd(SparkPlan.scala:247)
> at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:339)
> at
> org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:38)
> at
> org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collectFromPlan(Dataset.scala:3389)
> at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2550)
> at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2550)
> at org.apache.spark.sql.Dataset$$anonfun$52.apply(Dataset.scala:3370)
> at
> org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:78)
> at
> org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:125)
> at
>
