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Posted to issues@spark.apache.org by "Grigory Skvortsov (Jira)" <ji...@apache.org> on 2020/09/15 18:41:00 UTC
[jira] [Created] (SPARK-32894) Timestamp cast in exernal ocr table
Grigory Skvortsov created SPARK-32894:
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Summary: Timestamp cast in exernal ocr table
Key: SPARK-32894
URL: https://issues.apache.org/jira/browse/SPARK-32894
Project: Spark
Issue Type: Bug
Components: Java API
Affects Versions: 3.0.0
Environment: Spark 3.0.0
Java 1.8
Hadoop 3.3.0
Hive 3.1.2
Python 3.7 (from pyspark)
Reporter: Grigory Skvortsov
I have the external hive table stored as orc. I want to work with timestamp column in my table using pyspark.
For example, I try this:
spark.sql('select id, time_ from mydb.table1`).show()
Py4JJavaError: An error occurred while calling o2877.showString.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 4.0 failed 4 times, most recent failure: Lost task 0.3 in stage 4.0 (TID 19, 172.29.14.241, executor 1): java.lang.ClassCastException: org.apache.spark.unsafe.types.UTF8String cannot be cast to java.lang.Long
at scala.runtime.BoxesRunTime.unboxToLong(BoxesRunTime.java:107)
at org.apache.spark.sql.catalyst.expressions.MutableLong.update(SpecificInternalRow.scala:148)
at org.apache.spark.sql.catalyst.expressions.SpecificInternalRow.update(SpecificInternalRow.scala:228)
at org.apache.spark.sql.hive.HiveInspectors.$anonfun$unwrapperFor$53(HiveInspectors.scala:730)
at org.apache.spark.sql.hive.HiveInspectors.$anonfun$unwrapperFor$53$adapted(HiveInspectors.scala:730)
at org.apache.spark.sql.hive.orc.OrcFileFormat$.$anonfun$unwrapOrcStructs$4(OrcFileFormat.scala:351)
at scala.collection.Iterator$$anon$10.next(Iterator.scala:459)
at scala.collection.Iterator$$anon$10.next(Iterator.scala:459)
at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.next(FileScanRDD.scala:96)
at scala.collection.Iterator$$anon$10.next(Iterator.scala:459)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:729)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:340)
at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:872)
at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:872)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:313)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:127)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:444)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:447)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2023)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:1972)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:1971)
at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1971)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:950)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:950)
at scala.Option.foreach(Option.scala:407)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:950)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2203)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2152)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2141)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:752)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2093)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2114)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2133)
at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:467)
at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:420)
at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:47)
at org.apache.spark.sql.Dataset.collectFromPlan(Dataset.scala:3625)
at org.apache.spark.sql.Dataset.$anonfun$head$1(Dataset.scala:2695)
at org.apache.spark.sql.Dataset.$anonfun$withAction$1(Dataset.scala:3616)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:100)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:160)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:87)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:763)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64)
at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3614)
at org.apache.spark.sql.Dataset.head(Dataset.scala:2695)
at org.apache.spark.sql.Dataset.take(Dataset.scala:2902)
at org.apache.spark.sql.Dataset.getRows(Dataset.scala:300)
at org.apache.spark.sql.Dataset.showString(Dataset.scala:337)
at sun.reflect.GeneratedMethodAccessor80.invoke(Unknown Source)
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:748)
Caused by: java.lang.ClassCastException: org.apache.spark.unsafe.types.UTF8String cannot be cast to java.lang.Long
at scala.runtime.BoxesRunTime.unboxToLong(BoxesRunTime.java:107)
at org.apache.spark.sql.catalyst.expressions.MutableLong.update(SpecificInternalRow.scala:148)
at org.apache.spark.sql.catalyst.expressions.SpecificInternalRow.update(SpecificInternalRow.scala:228)
at org.apache.spark.sql.hive.HiveInspectors.$anonfun$unwrapperFor$53(HiveInspectors.scala:730)
at org.apache.spark.sql.hive.HiveInspectors.$anonfun$unwrapperFor$53$adapted(HiveInspectors.scala:730)
at org.apache.spark.sql.hive.orc.OrcFileFormat$.$anonfun$unwrapOrcStructs$4(OrcFileFormat.scala:351)
at scala.collection.Iterator$$anon$10.next(Iterator.scala:459)
at scala.collection.Iterator$$anon$10.next(Iterator.scala:459)
at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.next(FileScanRDD.scala:96)
at scala.collection.Iterator$$anon$10.next(Iterator.scala:459)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:729)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:340)
at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:872)
at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:872)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:313)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:127)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:444)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:447)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
... 1 more
I have the external hive table stored as orc. I want to work with timestamp column in my table using pyspark.
For example, I try this:
{{spark.sql('select id, time_ from mydb.table1`).show()}}
And get following output:
{{Py4JJavaError: An error occurred while calling o2877.showString.: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 4.0 failed 4 times, most recent failure: Lost task 0.3 in stage 4.0 (TID 19, 172.29.14.241, executor 1): java.lang.ClassCastException: org.apache.spark.unsafe.types.UTF8String cannot be cast to java.lang.Long at scala.runtime.BoxesRunTime.unboxToLong(BoxesRunTime.java:107) at org.apache.spark.sql.catalyst.expressions.MutableLong.update(SpecificInternalRow.scala:148) at org.apache.spark.sql.catalyst.expressions.SpecificInternalRow.update(SpecificInternalRow.scala:228) at org.apache.spark.sql.hive.HiveInspectors.$anonfun$unwrapperFor$53(HiveInspectors.scala:730) at org.apache.spark.sql.hive.HiveInspectors.$anonfun$unwrapperFor$53$adapted(HiveInspectors.scala:730) at org.apache.spark.sql.hive.orc.OrcFileFormat$.$anonfun$unwrapOrcStructs$4(OrcFileFormat.scala:351) at scala.collection.Iterator$$anon$10.next(Iterator.scala:459) at scala.collection.Iterator$$anon$10.next(Iterator.scala:459) at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.next(FileScanRDD.scala:96) at scala.collection.Iterator$$anon$10.next(Iterator.scala:459) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source) at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:729) at org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:340) at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:872) at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:872) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349) at org.apache.spark.rdd.RDD.iterator(RDD.scala:313) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) at org.apache.spark.scheduler.Task.run(Task.scala:127) at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:444) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:447) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) at java.lang.Thread.run(Thread.java:748)Driver stacktrace: at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2023) at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:1972) at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:1971) at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62) at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55) at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49) at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1971) at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:950) at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:950) at scala.Option.foreach(Option.scala:407) at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:950) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2203) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2152) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2141) at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49) at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:752) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2093) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2114) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2133) at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:467) at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:420) at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:47) at org.apache.spark.sql.Dataset.collectFromPlan(Dataset.scala:3625) at org.apache.spark.sql.Dataset.$anonfun$head$1(Dataset.scala:2695) at org.apache.spark.sql.Dataset.$anonfun$withAction$1(Dataset.scala:3616) at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:100) at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:160) at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:87) at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:763) at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64) at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3614) at org.apache.spark.sql.Dataset.head(Dataset.scala:2695) at org.apache.spark.sql.Dataset.take(Dataset.scala:2902) at org.apache.spark.sql.Dataset.getRows(Dataset.scala:300) at org.apache.spark.sql.Dataset.showString(Dataset.scala:337) at sun.reflect.GeneratedMethodAccessor80.invoke(Unknown Source) 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:748)Caused by: java.lang.ClassCastException: org.apache.spark.unsafe.types.UTF8String cannot be cast to java.lang.Long at scala.runtime.BoxesRunTime.unboxToLong(BoxesRunTime.java:107) at org.apache.spark.sql.catalyst.expressions.MutableLong.update(SpecificInternalRow.scala:148) at org.apache.spark.sql.catalyst.expressions.SpecificInternalRow.update(SpecificInternalRow.scala:228) at org.apache.spark.sql.hive.HiveInspectors.$anonfun$unwrapperFor$53(HiveInspectors.scala:730) at org.apache.spark.sql.hive.HiveInspectors.$anonfun$unwrapperFor$53$adapted(HiveInspectors.scala:730) at org.apache.spark.sql.hive.orc.OrcFileFormat$.$anonfun$unwrapOrcStructs$4(OrcFileFormat.scala:351) at scala.collection.Iterator$$anon$10.next(Iterator.scala:459) at scala.collection.Iterator$$anon$10.next(Iterator.scala:459) at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.next(FileScanRDD.scala:96) at scala.collection.Iterator$$anon$10.next(Iterator.scala:459) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source) at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:729) at org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:340) at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:872) at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:872) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349) at org.apache.spark.rdd.RDD.iterator(RDD.scala:313) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) at org.apache.spark.scheduler.Task.run(Task.scala:127) at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:444) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:447) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)... 1 more}}
Also I tried to read orc file like {{spark.read.load('hdfs://host:9000/user/hive/..../part1=*/part2=*/*.orc')}}, but had the same exception.
I try to cast types, but all my attempts failed.
Also I tried to create atemporary table as select from the original external. After that I I was able to see and work with {{time_}} table as expected.
What I should with to working with timestamp columns from orc files?
P.S. I can correctly see if I select columns with HiveCli. Also If can create table (internal) as select * from original& In this situation I can correctly work with timestamo column in pyspark.
Maybe it is bug? How to fix it!
{{}}
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