apache / apache/parquet-java

A NullPointerException in DictionaryValuesWriter when writing Parquet

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Component: Parquet Priority: Major Type: bug
Langage dominant
Java
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3.1k
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Merge moyen
3 j 12 h
PR mergées (30 j)
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Description

A NullReference Exception happens when writing a large partitioned Spark dataframe to Parquet.

The job is running in AWS EMR 5.8.0 (Spark 2.1.1).

Exception:

```
17/09/05 16:40:33 ERROR Utils: Aborting task
java.lang.NullPointerException
at org.apache.parquet.it.unimi.dsi.fastutil.objects.Object2IntLinkedOpenHashMap.getInt(Object2IntLinkedOpenHashMap.java:590)
at org.apache.parquet.column.values.dictionary.DictionaryValuesWriter$PlainFixedLenArrayDictionaryValuesWriter.writeBytes(DictionaryValuesWriter.java:307)
at org.apache.parquet.column.values.fallback.FallbackValuesWriter.writeBytes(FallbackValuesWriter.java:162)
at org.apache.parquet.column.impl.ColumnWriterV1.write(ColumnWriterV1.java:201)
at org.apache.parquet.io.MessageColumnIO$MessageColumnIORecordConsumer.addBinary(MessageColumnIO.java:467)
at org.apache.spark.sql.execution.datasources.parquet.ParquetWriteSupport$$anonfun$org$apache$spark$sql$execution$datasources$parquet$ParquetWriteSupport$$makeWriter$10.apply(ParquetWriteSupport.scala:184)
at org.apache.spark.sql.execution.datasources.parquet.ParquetWriteSupport$$anonfun$org$apache$spark$sql$execution$datasources$parquet$ParquetWriteSupport$$makeWriter$10.apply(ParquetWriteSupport.scala:172)
at org.apache.spark.sql.execution.datasources.parquet.ParquetWriteSupport$$anonfun$org$apache$spark$sql$execution$datasources$parquet$ParquetWriteSupport$$writeFields$1.apply$mcV$sp(ParquetWriteSupport.scala:124)
at org.apache.spark.sql.execution.datasources.parquet.ParquetWriteSupport.org$apache$spark$sql$execution$datasources$parquet$ParquetWriteSupport$$consumeField(ParquetWriteSupport.scala:437)
at org.apache.spark.sql.execution.datasources.parquet.ParquetWriteSupport.org$apache$spark$sql$execution$datasources$parquet$ParquetWriteSupport$$writeFields(ParquetWriteSupport.scala:123)
at org.apache.spark.sql.execution.datasources.parquet.ParquetWriteSupport$$anonfun$write$1.apply$mcV$sp(ParquetWriteSupport.scala:114)
at org.apache.spark.sql.execution.datasources.parquet.ParquetWriteSupport.consumeMessage(ParquetWriteSupport.scala:425)
at org.apache.spark.sql.execution.datasources.parquet.ParquetWriteSupport.write(ParquetWriteSupport.scala:113)
at org.apache.spark.sql.execution.datasources.parquet.ParquetWriteSupport.write(ParquetWriteSupport.scala:51)
at org.apache.parquet.hadoop.InternalParquetRecordWriter.write(InternalParquetRecordWriter.java:123)
at org.apache.parquet.hadoop.ParquetRecordWriter.write(ParquetRecordWriter.java:180)
at org.apache.parquet.hadoop.ParquetRecordWriter.write(ParquetRecordWriter.java:46)
at org.apache.spark.sql.execution.datasources.parquet.ParquetOutputWriter.write(ParquetOutputWriter.scala:40)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$DynamicPartitionWriteTask$$anonfun$execute$2.apply(FileFormatWriter.scala:465)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$DynamicPartitionWriteTask$$anonfun$execute$2.apply(FileFormatWriter.scala:440)
at scala.collection.Iterator$class.foreach(Iterator.scala:893)
at org.apache.spark.sql.catalyst.util.AbstractScalaRowIterator.foreach(AbstractScalaRowIterator.scala:26)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$DynamicPartitionWriteTask.execute(FileFormatWriter.scala:440)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:258)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:256)
at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1375)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:261)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1$$anonfun$apply$mcV$sp$1.apply(FileFormatWriter.scala:191)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1$$anonfun$apply$mcV$sp$1.apply(FileFormatWriter.scala:190)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:108)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:335)
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)}}
```

**Reporter**: [Irina Truong](https://issues.apache.org/jira/secure/ViewProfile.jspa?name=irinatruong)

**Note**: *This issue was originally created as [PARQUET-1089](https://issues.apache.org/jira/browse/PARQUET-1089). Please see the [migration documentation](https://issues.apache.org/jira/browse/PARQUET-2502) for further details.*

Guide de contribution

Aucun guide de contribution indexé pour ce dépôt

Piste de recherche

Commencez dans parquet-column/src/main/java/org/apache/parquet/column/values/dictionary/DictionaryValuesWriter.java, en particulier dans le chemin writeBytes à l’emplacement indiqué par la stack trace. Reproduisez l’échec avec un dataframe Spark volumineux et partitionné écrivant au format Parquet avec les versions de Spark et AWS EMR indiquées, puis suivez l’interaction avec FallbackValuesWriter. Le travail est terminé lorsque la NullPointerException est comprise et empêchée, avec un test de régression couvrant le cas signalé.

Rédigé par le modèle d'indexation à partir du texte de l'issue.

Évaluation

Stack technique
aws, java, spark
Domaine
data-engineering
Type d'issue
Bug
Difficulté
4/5
Temps estimé
3-5 jours
Activité
À l'abandon
Clarté
À clarifier
Accessibilité débutants
25/100

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