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Posted to jira@arrow.apache.org by "Georeth Zhou (Jira)" <ji...@apache.org> on 2022/10/31 12:44:00 UTC
[jira] [Updated] (ARROW-18198) IndexOutOfBoundsException when loading compressed IPC format
[ https://issues.apache.org/jira/browse/ARROW-18198?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Georeth Zhou updated ARROW-18198:
---------------------------------
Environment:
Linux and Windows.
Apache Arrow Java version: 10.0.0, 9.0.0, 4.0.1.
Pandas 1.4.2 using pyarrow 8.0.0 (anaconda3-2022.05)
was:
Linux and Windows.
Apache Arrow Java version: 10.0.0, 9.0.0, 4.0.1.
Pandas 1.4.2. (anaconda3-2022.05)
> IndexOutOfBoundsException when loading compressed IPC format
> ------------------------------------------------------------
>
> Key: ARROW-18198
> URL: https://issues.apache.org/jira/browse/ARROW-18198
> Project: Apache Arrow
> Issue Type: Bug
> Components: Java
> Affects Versions: 4.0.1, 9.0.0, 10.0.0
> Environment: Linux and Windows.
> Apache Arrow Java version: 10.0.0, 9.0.0, 4.0.1.
> Pandas 1.4.2 using pyarrow 8.0.0 (anaconda3-2022.05)
> Reporter: Georeth Zhou
> Priority: Major
>
> I encountered this bug when I loaded a dataframe stored in the Arrow IPC format.
>
> {code:java}
> // Java Code from "Apache Arrow Java Cookbook"
> File file = new File("example.arrow");
> try (
> BufferAllocator rootAllocator = new RootAllocator();
> FileInputStream fileInputStream = new FileInputStream(file);
> ArrowFileReader reader = new ArrowFileReader(fileInputStream.getChannel(), rootAllocator)
> ) {
> System.out.println("Record batches in file: " + reader.getRecordBlocks().size());
> for (ArrowBlock arrowBlock : reader.getRecordBlocks()) {
> reader.loadRecordBatch(arrowBlock);
> VectorSchemaRoot vectorSchemaRootRecover = reader.getVectorSchemaRoot();
> System.out.print(vectorSchemaRootRecover.contentToTSVString());
> }
> } catch (IOException e) {
> e.printStackTrace();
> } {code}
> Call stack:
> {noformat}
> Exception in thread "main" java.lang.IndexOutOfBoundsException: index: 0, length: 2048 (expected: range(0, 2024))
> at org.apache.arrow.memory.ArrowBuf.checkIndex(ArrowBuf.java:701)
> at org.apache.arrow.memory.ArrowBuf.setBytes(ArrowBuf.java:955)
> at org.apache.arrow.vector.BaseFixedWidthVector.reAlloc(BaseFixedWidthVector.java:451)
> at org.apache.arrow.vector.BaseFixedWidthVector.setValueCount(BaseFixedWidthVector.java:732)
> at org.apache.arrow.vector.VectorSchemaRoot.setRowCount(VectorSchemaRoot.java:240)
> at org.apache.arrow.vector.VectorLoader.load(VectorLoader.java:86)
> at org.apache.arrow.vector.ipc.ArrowReader.loadRecordBatch(ArrowReader.java:220)
> at org.apache.arrow.vector.ipc.ArrowFileReader.loadNextBatch(ArrowFileReader.java:166)
> at org.apache.arrow.vector.ipc.ArrowFileReader.loadRecordBatch(ArrowFileReader.java:197){noformat}
> This bug can be reproduced by a simple dataframe created by pandas:
>
> {code:java}
> pd.DataFrame({'a': range(10000)}).to_feather('example.arrow') {code}
> Pandas compresses the dataframe by default. If the compression is turned off, Java can load the dataframe. Thus, I guess the bounds checking code is buggy when loading compressed file.
>
> That dataframe can be loaded in polars, pandas and pyarrow, so it's unlikely to be a pandas bug.
>
>
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