apache / apache/parquet-java

Buffer int overflow in CapacityByteArrayOutputStream, SnappyCompressor

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#2,528 0 comentarios 0 reacciones 0 asignados Ver en GitHub
Component: Java Component: Parquet Priority: Major Type: bug
Lenguaje dominante
Java
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3 d 12 h
PR fusionados (30 d)
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Descripción

During an attempted write operation, a buffer position integer overflow is resulting in a IllegalArgumentException: Negative capacity: -2147336621 exception.

 
```

20/10/06 15:30:39 INFO HadoopRDD: Input split: s3a:///part-00015-96362e5d-d047-4f31-812b-38ff79f6919c-c000.txt.bz2:268435456+33554432
20/10/06 17:23:37 ERROR Utils: Aborting task
java.lang.IllegalArgumentException: Negative capacity: -2147336621
at java.nio.Buffer.(Buffer.java:199)
at java.nio.ByteBuffer.(ByteBuffer.java:281)
at java.nio.ByteBuffer.(ByteBuffer.java:289)
at java.nio.MappedByteBuffer.(MappedByteBuffer.java:89)
at java.nio.DirectByteBuffer.(DirectByteBuffer.java:119)
at java.nio.ByteBuffer.allocateDirect(ByteBuffer.java:311)
at org.apache.parquet.hadoop.codec.SnappyCompressor.setInput(SnappyCompressor.java:97)
at org.apache.parquet.hadoop.codec.NonBlockedCompressorStream.write(NonBlockedCompressorStream.java:48)
at org.apache.parquet.bytes.CapacityByteArrayOutputStream.writeToOutput(CapacityByteArrayOutputStream.java:227)
at org.apache.parquet.bytes.CapacityByteArrayOutputStream.writeTo(CapacityByteArrayOutputStream.java:247)
at org.apache.parquet.bytes.BytesInput$CapacityBAOSBytesInput.writeAllTo(BytesInput.java:405)
at org.apache.parquet.bytes.BytesInput$SequenceBytesIn.writeAllTo(BytesInput.java:296)
at org.apache.parquet.hadoop.CodecFactory$HeapBytesCompressor.compress(CodecFactory.java:164)
at org.apache.parquet.hadoop.ColumnChunkPageWriteStore$ColumnChunkPageWriter.writePage(ColumnChunkPageWriteStore.java:95)
at org.apache.parquet.column.impl.ColumnWriterV1.writePage(ColumnWriterV1.java:147)
at org.apache.parquet.column.impl.ColumnWriterV1.flush(ColumnWriterV1.java:235)
at org.apache.parquet.column.impl.ColumnWriteStoreV1.flush(ColumnWriteStoreV1.java:122)
at org.apache.parquet.hadoop.InternalParquetRecordWriter.flushRowGroupToStore(InternalParquetRecordWriter.java:172)
at org.apache.parquet.hadoop.InternalParquetRecordWriter.checkBlockSizeReached(InternalParquetRecordWriter.java:148)
at org.apache.parquet.hadoop.InternalParquetRecordWriter.write(InternalParquetRecordWriter.java:130)
at org.apache.parquet.hadoop.ParquetRecordWriter.write(ParquetRecordWriter.java:182)
at org.apache.parquet.hadoop.ParquetRecordWriter.write(ParquetRecordWriter.java:44)
at org.apache.spark.sql.execution.datasources.parquet.ParquetOutputWriter.write(ParquetOutputWriter.scala:40)
at org.apache.spark.sql.execution.datasources.SingleDirectoryDataWriter.write(FileFormatDataWriter.scala:137)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:242)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:239)
at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1394)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:245)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:169)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:168)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:121)
at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:402)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:408)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
```
2,147,483,647 (max int) - 2147336621 (negative capacity) = 147026.

The input bz2 files are all roughly 900 MiB in size. The target parquet part files are 1.7 GiB in size.

Increasing the partition count from 64 to 1024 fixes the issue. The output parquet part files drop to 100MiB in size.

However, it's unclear to me what the root cause is and why increasing partition count helps. Was it an unlucky row grouping that bumped the buffer size over by 147KB, i.e, any change up or down in parittion count would have helped? Is it approaching the parquet part file size limit?

This issue seems related to PARQUET-1632 but it's not using the ConcatenatingByteArrayCollector, which potentially means a distinct root cause. The input dataset does have large string columns (up to 10MB) but nothing close to the signed int max of 2.4G that was produced in PARQUET-1632.

 

 

 

 

**Reporter**: [Artem Shnayder](https://issues.apache.org/jira/secure/ViewProfile.jspa?name=shndr)

**Note**: *This issue was originally created as [PARQUET-1919](https://issues.apache.org/jira/browse/PARQUET-1919). Please see the [migration documentation](https://issues.apache.org/jira/browse/PARQUET-2502) for further details.*

Guía de contribución

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Línea de trabajo

Comienza con CapacityByteArrayOutputStream.writeToOutput, SnappyCompressor.setInput y NonBlockedCompressorStream.write de la traza de pila reportada; después, sigue cómo los grupos de filas grandes llegan al compresor. Reproduce el problema con una entrada grande y compara los tamaños de las particiones; se considera terminado cuando se haya identificado el límite de desbordamiento y se haya añadido una comprobación de regresión que impida el fallo de capacidad negativa.

Escrito por el modelo de indexación a partir del texto del issue.

Evaluación

Stack tecnológico
java
Área
data-engineering
Tipo de issue
Error
Dificultad
4/5
Tiempo estimado
3-5 días
Estado de actividad
Estancado
Claridad
Necesita aclaración
Aptitud para principiantes
35/100

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