[
https://issues.apache.org/jira/browse/SPARK-37196?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
ASF GitHub Bot updated SPARK-37196:
-----------------------------------
Labels: pull-request-available (was: )
> NPE in
> org.apache.spark.sql.hive.HiveShim$.toCatalystDecimal(HiveShim.scala:106)
> --------------------------------------------------------------------------------
>
> Key: SPARK-37196
> URL: https://issues.apache.org/jira/browse/SPARK-37196
> Project: Spark
> Issue Type: Bug
> Components: Input/Output
> Affects Versions: 3.0.1
> Reporter: Sergey Yavorski
> Assignee: angerszhu
> Priority: Major
> Labels: pull-request-available
> Fix For: 3.1.3, 3.0.4, 3.2.1, 3.3.0
>
>
> Still reproducible in Spark 3.0.1.
> +*How to reproduce:*+
> *SHELL*
> > export SPARK_MAJOR_VERSION=3
> *SPARK PART 1*
> > spark-shell --master local
> SPARK_MAJOR_VERSION is set to 3, using Spark3
> Setting default log level to "WARN".
> To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use
> setLogLevel(newLevel).
> 21/10/25 11:43:58 WARN Utils: Service 'SparkUI' could not bind on port 4040.
> Attempting port 4041.
> 21/10/25 11:43:58 WARN Utils: Service 'SparkUI' could not bind on port 4041.
> Attempting port 4042.
> Spark context Web UI available at <server>:4042
> Spark context available as 'sc' (master = local, app id =
> local-1635151438558).
> Spark session available as 'spark'.
> Welcome to
> ____ __
> / __/__ ___ _____/ /__
> _\ \/ _ \/ _ `/ __/ '_/
> /___/ .__/\_,_/_/ /_/\_\ version 3.0.1
> /_/
> Using Scala version 2.12.10 (OpenJDK 64-Bit Server VM, Java 1.8.0_302)
> Type in expressions to have them evaluated.
> Type :help for more information.
> scala> val df = spark.sql("select 'dummy' as name,
> 1000000000000000000010.7000000000000010 as value")
> df: org.apache.spark.sql.DataFrame = [name: string, value: decimal(38,16)]
> scala> df.write.mode("Overwrite").parquet("test.parquet")
> *HIVE*
> hive> create external table test_precision(name string, value Decimal(18,6))
> STORED AS PARQUET LOCATION 'test';
> OK
> Time taken: 0.067 seconds
> *SPARK PART 2*
>
> scala> spark.conf.set("spark.sql.hive.convertMetastoreParquet","false");
> scala> val df_hive = spark.sql("select * from test_precision");
> df_hive: org.apache.spark.sql.DataFrame = [name: string, value: decimal(18,6)]
> scala> df_hive.show;
> 21/10/25 12:04:51 ERROR Executor: Exception in task 0.0 in stage 2.0 (TID 2)/
> 1]
> *{color:red}java.lang.NullPointerException
> at
> org.apache.spark.sql.hive.HiveShim$.toCatalystDecimal(HiveShim.scala:106){color}*
> at
> org.apache.spark.sql.hive.HadoopTableReader$.$anonfun$fillObject$13(TableReader.scala:465)
> at
> org.apache.spark.sql.hive.HadoopTableReader$.$anonfun$fillObject$13$adapted(TableReader.scala:464)
> at
> org.apache.spark.sql.hive.HadoopTableReader$.$anonfun$fillObject$18(TableReader.scala:493)
> at scala.collection.Iterator$$anon$10.next(Iterator.scala:459)
> at scala.collection.Iterator$$anon$10.next(Iterator.scala:459)
> at
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown
> Source)
> at
> org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
> at
> org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:729)
> at
> org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:340)
> at
> org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:872)
> at
> org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:872)
> at
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:313)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
> at org.apache.spark.scheduler.Task.run(Task.scala:127)
> at
> org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:446)
> at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377)
> at
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:449)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
> at java.lang.Thread.run(Thread.java:748)
> 21/10/25 12:04:51 WARN TaskSetManager: Lost task 0.0 in stage 2.0 (TID 2,
> tklis-kappd0005.dev.df.sbrf.ru, executor driver):
> java.lang.NullPointerException
> at
> org.apache.spark.sql.hive.HiveShim$.toCatalystDecimal(HiveShim.scala:106)
> at
> org.apache.spark.sql.hive.HadoopTableReader$.$anonfun$fillObject$13(TableReader.scala:465)
> at
> org.apache.spark.sql.hive.HadoopTableReader$.$anonfun$fillObject$13$adapted(TableReader.scala:464)
> at
> org.apache.spark.sql.hive.HadoopTableReader$.$anonfun$fillObject$18(TableReader.scala:493)
> at scala.collection.Iterator$$anon$10.next(Iterator.scala:459)
> at scala.collection.Iterator$$anon$10.next(Iterator.scala:459)
> at
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown
> Source)
> at
> org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
> at
> org.apache.spark.sql.execution.WholeStageCodegenExec$$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$3(Executor.scala:446)
> at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377)
> at
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:449)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
> at java.lang.Thread.run(Thread.java:748)
> 21/10/25 12:04:51 ERROR TaskSetManager: Task 0 in stage 2.0 failed 1 times;
> aborting job
> org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in
> stage 2.0 failed 1 times, most recent failure: Lost task 0.0 in stage 2.0
> (TID 2, tklis-kappd0005.dev.df.sbrf.ru, executor driver):
> java.lang.NullPointerException
> at
> org.apache.spark.sql.hive.HiveShim$.toCatalystDecimal(HiveShim.scala:106)
> at
> org.apache.spark.sql.hive.HadoopTableReader$.$anonfun$fillObject$13(TableReader.scala:465)
> at
> org.apache.spark.sql.hive.HadoopTableReader$.$anonfun$fillObject$13$adapted(TableReader.scala:464)
> at
> org.apache.spark.sql.hive.HadoopTableReader$.$anonfun$fillObject$18(TableReader.scala:493)
> at scala.collection.Iterator$$anon$10.next(Iterator.scala:459)
> at scala.collection.Iterator$$anon$10.next(Iterator.scala:459)
> at
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$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:446)
> at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377)
> at
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:449)
> 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:2059)
> at
> org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2008)
> at
> org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2007)
> 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:2007)
> at
> org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:973)
> at
> org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:973)
> at scala.Option.foreach(Option.scala:407)
> at
> org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:973)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2239)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2188)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2177)
> at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
> at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:775)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2099)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2120)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2139)
> at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:467)
> at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:420)
> at
> org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:47)
> at org.apache.spark.sql.Dataset.collectFromPlan(Dataset.scala:3627)
> at org.apache.spark.sql.Dataset.$anonfun$head$1(Dataset.scala:2697)
> at org.apache.spark.sql.Dataset.$anonfun$withAction$1(Dataset.scala:3618)
> at
> org.apache.spark.sql.execution.SQLExecution$.$anonfun$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$1(SQLExecution.scala:87)
> at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:764)
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64)
> at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3616)
> at org.apache.spark.sql.Dataset.head(Dataset.scala:2697)
> at org.apache.spark.sql.Dataset.take(Dataset.scala:2904)
> at org.apache.spark.sql.Dataset.getRows(Dataset.scala:300)
> at org.apache.spark.sql.Dataset.showString(Dataset.scala:337)
> at org.apache.spark.sql.Dataset.show(Dataset.scala:824)
> at org.apache.spark.sql.Dataset.show(Dataset.scala:783)
> at org.apache.spark.sql.Dataset.show(Dataset.scala:792)
> ... 47 elided
> Caused by: java.lang.NullPointerException
> at org.apache.spark.sql.hive.HiveShim$.toCatalystDecimal(HiveShim.scala:106)
> at
> org.apache.spark.sql.hive.HadoopTableReader$.$anonfun$fillObject$13(TableReader.scala:465)
> at
> org.apache.spark.sql.hive.HadoopTableReader$.$anonfun$fillObject$13$adapted(TableReader.scala:464)
> at
> org.apache.spark.sql.hive.HadoopTableReader$.$anonfun$fillObject$18(TableReader.scala:493)
> at scala.collection.Iterator$$anon$10.next(Iterator.scala:459)
> at scala.collection.Iterator$$anon$10.next(Iterator.scala:459)
> at
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$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$3(Executor.scala:446)
> at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:449)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
> at java.lang.Thread.run(Thread.java:748)
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