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https://issues.apache.org/jira/browse/PARQUET-1633?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17347405#comment-17347405
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ASF GitHub Bot commented on PARQUET-1633:
-----------------------------------------
eadwright commented on pull request #902:
URL: https://github.com/apache/parquet-mr/pull/902#issuecomment-843866914
Not a unit test yet, but I have at least found a reliable way to create a
parquet file in python which causes Java to break when reading it. For this we
require a huge number of rows, and a string column with very high entropy to
avoid the use dictionary lookup or compression. Not these conditions can be
real-world - records containing long SHA3 hashes for example.
This python code needs more than 16GB of RAM to execute.
```import pandas as pd
import numpy as np
rand_array = np.random.rand(75000000, 4)
df = pd.DataFrame(rand_array, columns=['number1', 'number2', 'number3',
'number4'])
df['string1'] = df['number1'].astype(str) + df['number2'].astype(str) +
df['number3'].astype(str)
df.to_parquet("random.parquet", compression='snappy', engine='pyarrow')```
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> Integer overflow in ParquetFileReader.ConsecutiveChunkList
> ----------------------------------------------------------
>
> Key: PARQUET-1633
> URL: https://issues.apache.org/jira/browse/PARQUET-1633
> Project: Parquet
> Issue Type: Bug
> Components: parquet-mr
> Affects Versions: 1.10.1
> Reporter: Ivan Sadikov
> Priority: Major
>
> When reading a large Parquet file (2.8GB), I encounter the following
> exception:
> {code:java}
> Caused by: org.apache.parquet.io.ParquetDecodingException: Can not read value
> at 0 in block -1 in file
> dbfs:/user/hive/warehouse/demo.db/test_table/part-00014-tid-1888470069989036737-593c82a4-528b-4975-8de0-5bcbc5e9827d-10856-1-c000.snappy.parquet
> at
> org.apache.parquet.hadoop.InternalParquetRecordReader.nextKeyValue(InternalParquetRecordReader.java:251)
> at
> org.apache.parquet.hadoop.ParquetRecordReader.nextKeyValue(ParquetRecordReader.java:207)
> at
> org.apache.spark.sql.execution.datasources.RecordReaderIterator.hasNext(RecordReaderIterator.scala:40)
> at
> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1$$anon$2.getNext(FileScanRDD.scala:228)
> ... 14 more
> Caused by: java.lang.IllegalArgumentException: Illegal Capacity: -212
> at java.util.ArrayList.<init>(ArrayList.java:157)
> at
> org.apache.parquet.hadoop.ParquetFileReader$ConsecutiveChunkList.readAll(ParquetFileReader.java:1169){code}
>
> The file metadata is:
> * block 1 (3 columns)
> ** rowCount: 110,100
> ** totalByteSize: 348,492,072
> ** compressedSize: 165,689,649
> * block 2 (3 columns)
> ** rowCount: 90,054
> ** totalByteSize: 3,243,165,541
> ** compressedSize: 2,509,579,966
> * block 3 (3 columns)
> ** rowCount: 105,119
> ** totalByteSize: 350,901,693
> ** compressedSize: 144,952,177
> * block 4 (3 columns)
> ** rowCount: 48,741
> ** totalByteSize: 1,275,995
> ** compressedSize: 914,205
> I don't have the code to reproduce the issue, unfortunately; however, I
> looked at the code and it seems that integer {{length}} field in
> ConsecutiveChunkList overflows, which results in negative capacity for array
> list in {{readAll}} method:
> {code:java}
> int fullAllocations = length / options.getMaxAllocationSize();
> int lastAllocationSize = length % options.getMaxAllocationSize();
>
> int numAllocations = fullAllocations + (lastAllocationSize > 0 ? 1 : 0);
> List<ByteBuffer> buffers = new ArrayList<>(numAllocations);{code}
>
> This is caused by cast to integer in {{readNextRowGroup}} method in
> ParquetFileReader:
> {code:java}
> currentChunks.addChunk(new ChunkDescriptor(columnDescriptor, mc, startingPos,
> (int)mc.getTotalSize()));
> {code}
> which overflows when total size of the column is larger than
> Integer.MAX_VALUE.
> I would appreciate if you could help addressing the issue. Thanks!
>
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