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https://issues.apache.org/jira/browse/SPARK-28632?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16901065#comment-16901065
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Juan commented on SPARK-28632:
------------------------------
Unfortunately, I have to develop based off the current version we have in
production.
I did find a workaround though, in my spark.sql logic, My where clause has the
partition column, I converted that to a String and now it is functioning
correctly, it's not ideal, but it'll do for now until we go to the higher
version.
Thanks,
Juan
> Cannot read from a partitioned table by Int
> -------------------------------------------
>
> Key: SPARK-28632
> URL: https://issues.apache.org/jira/browse/SPARK-28632
> Project: Spark
> Issue Type: Bug
> Components: Spark Shell, SQL, YARN
> Affects Versions: 2.1.1
> Environment: Dev env
> Reporter: Juan
> Priority: Major
> Original Estimate: 672h
> Remaining Estimate: 672h
>
> Getting the following error when reading count from the DataFrame:
> {code}
> scala> task189DF.select("ID_NBR").count()
> {code}
> {code}
> 19/08/05 17:16:20 WARN Utils: Truncated the string representation of a plan
> since it was too large. This behavior can be adjusted by setting
> 'spark.debug.maxToStringFields' in SparkEnv.conf.
> org.apache.spark.sql.catalyst.errors.package$TreeNodeException: execute, tree:
> Exchange SinglePartition
> +- *HashAggregate(keys=[], functions=[partial_count(1)], output=[count#78L])
> +- HiveTableScan MetastoreRelation schema, table_name,
> [isnotnull(day_nbr#12), isnotnull(mth_nbr#11), isnotnull(yr_nbr#10),
> (yr_nbr#10 = 2019), (mth_nbr#11 = 7), (day_nbr#12 = 24)]
> at org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:56)
> at
> org.apache.spark.sql.execution.exchange.ShuffleExchange.doExecute(ShuffleExchange.scala:112)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:117)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:117)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:138)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
> at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:135)
> at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:116)
> at
> org.apache.spark.sql.execution.InputAdapter.inputRDDs(WholeStageCodegenExec.scala:235)
> at
> org.apache.spark.sql.execution.aggregate.HashAggregateExec.inputRDDs(HashAggregateExec.scala:141)
> at
> org.apache.spark.sql.execution.WholeStageCodegenExec.doExecute(WholeStageCodegenExec.scala:368)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:117)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:117)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:138)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
> at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:135)
> at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:116)
> at
> org.apache.spark.sql.execution.SparkPlan.getByteArrayRdd(SparkPlan.scala:228)
> at
> org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:275)
> at
> org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$Dataset$$execute$1$1.apply(Dataset.scala:2386)
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57)
> at
> org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$withNewExecutionId(Dataset.scala:2788)
> at
> org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$execute$1(Dataset.scala:2385)
> at
> org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collect(Dataset.scala:2392)
> at org.apache.spark.sql.Dataset$$anonfun$count$1.apply(Dataset.scala:2420)
> at org.apache.spark.sql.Dataset$$anonfun$count$1.apply(Dataset.scala:2419)
> at org.apache.spark.sql.Dataset.withCallback(Dataset.scala:2801)
> at org.apache.spark.sql.Dataset.count(Dataset.scala:2419)
> ... 48 elided
> Caused by: java.lang.RuntimeException: Caught Hive MetaException attempting
> to get partition metadata by filter from Hive. You can set the Spark
> configuration setting spark.sql.hive.manageFilesourcePartitions to false to
> work around this problem, however this will result in degraded performance.
> Please report a bug: https://issues.apache.org/jira/browse/SPARK
> at
> org.apache.spark.sql.hive.client.Shim_v0_13.getPartitionsByFilter(HiveShim.scala:627)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$getPartitionsByFilter$1.apply(HiveClientImpl.scala:574)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$getPartitionsByFilter$1.apply(HiveClientImpl.scala:572)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$withHiveState$1.apply(HiveClientImpl.scala:279)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl.liftedTree1$1(HiveClientImpl.scala:226)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl.retryLocked(HiveClientImpl.scala:225)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl.withHiveState(HiveClientImpl.scala:268)
> at
> org.apache.spark.sql.hive.client.HiveClientImpl.getPartitionsByFilter(HiveClientImpl.scala:572)
> at
> org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$listPartitionsByFilter$1.apply(HiveExternalCatalog.scala:1020)
> at
> org.apache.spark.sql.hive.HiveExternalCatalog$$anonfun$listPartitionsByFilter$1.apply(HiveExternalCatalog.scala:1003)
> at
> org.apache.spark.sql.hive.HiveExternalCatalog.withClient(HiveExternalCatalog.scala:97)
> at
> org.apache.spark.sql.hive.HiveExternalCatalog.listPartitionsByFilter(HiveExternalCatalog.scala:1003)
> at
> org.apache.spark.sql.hive.MetastoreRelation.getHiveQlPartitions(MetastoreRelation.scala:160)
> at
> org.apache.spark.sql.hive.execution.HiveTableScanExec$$anonfun$10.apply(HiveTableScanExec.scala:151)
> at
> org.apache.spark.sql.hive.execution.HiveTableScanExec$$anonfun$10.apply(HiveTableScanExec.scala:150)
> at org.apache.spark.util.Utils$.withDummyCallSite(Utils.scala:2458)
> at
> org.apache.spark.sql.hive.execution.HiveTableScanExec.doExecute(HiveTableScanExec.scala:149)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:117)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:117)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:138)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
> at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:135)
> at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:116)
> at
> org.apache.spark.sql.execution.InputAdapter.inputRDDs(WholeStageCodegenExec.scala:235)
> at
> org.apache.spark.sql.execution.aggregate.HashAggregateExec.inputRDDs(HashAggregateExec.scala:141)
> at
> org.apache.spark.sql.execution.WholeStageCodegenExec.doExecute(WholeStageCodegenExec.scala:368)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:117)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:117)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:138)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
> at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:135)
> at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:116)
> at
> org.apache.spark.sql.execution.exchange.ShuffleExchange.prepareShuffleDependency(ShuffleExchange.scala:85)
> at
> org.apache.spark.sql.execution.exchange.ShuffleExchange$$anonfun$doExecute$1.apply(ShuffleExchange.scala:121)
> at
> org.apache.spark.sql.execution.exchange.ShuffleExchange$$anonfun$doExecute$1.apply(ShuffleExchange.scala:112)
> at org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:52)
> ... 75 more
> 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:614)
> ... 110 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:2216)
> at
> org.apache.hadoop.hive.metastore.api.ThriftHiveMetastore$Client.get_partitions_by_filter(ThriftHiveMetastore.java:2200)
> at
> org.apache.hadoop.hive.metastore.HiveMetaStoreClient.listPartitionsByFilter(HiveMetaStoreClient.java:1103)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at
> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
> at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:498)
> at
> org.apache.hadoop.hive.metastore.RetryingMetaStoreClient.invoke(RetryingMetaStoreClient.java:156)
> at com.sun.proxy.$Proxy21.listPartitionsByFilter(Unknown Source)
> at
> org.apache.hadoop.hive.ql.metadata.Hive.getPartitionsByFilter(Hive.java:2254)
> ... 115 more
> {code}
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