apache / apache/parquet-java

Buffer int overflow in CapacityByteArrayOutputStream, SnappyCompressor

オープン
#2,528 コメント 0 件 リアクション 0 件 担当者 0 名 GitHub で見る
Component: Java Component: Parquet Priority: Major Type: bug
主要言語
Java
スター
3.1k
フォーク
1.6k
平均マージ
3日 12時間
マージ済み PR(30日)
33

説明

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.*

コントリビューションガイド

このリポジトリのコントリビューションガイドは索引されていません

調査の方向性

報告されたスタックトレースにある CapacityByteArrayOutputStream.writeToOutput、SnappyCompressor.setInput、NonBlockedCompressorStream.write から始め、サイズの大きい行グループがどのようにコンプレッサーへ到達するかを追跡します。大きな入力で再現し、パーティションサイズを比較します。オーバーフロー境界を特定し、負の容量による失敗を防ぐリグレッションチェックを追加できれば完了です。

索引モデルが issue の本文から書いたものです。

評価

技術スタック
java
領域
data-engineering
issue の種類
バグ
難易度
4/5
見積もり時間
3〜5日
活発さ
停滞
明瞭さ
説明が足りない
初心者へのやさしさ
35/100

新しい issue をメールで受け取る

初心者向けの GitHub issue を短くまとめたダイジェスト。