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https://issues.apache.org/jira/browse/ARROW-17984?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17625884#comment-17625884
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Weston Pace commented on ARROW-17984:
-------------------------------------
Can you share the full output of {{thread apply all bt}}? The core dump itself
isn't too portable without the binaries that generated it. E.g...
{noformat}
warning: Can't open file /usr/bin/python3.8 during file-backed mapping note
processing
warning: Can't open file /usr/lib/x86_64-linux-gnu/libresolv-2.31.so during
file-backed mapping note processing
warning: Can't open file
/home/ubuntu/.local/lib/python3.8/site-packages/pyarrow/libarrow_python_flight.so.900
during file-backed mapping note processing
{noformat}
So I just get:
{noformat}
(gdb) thread apply all bt
Thread 42 (LWP 10252):
#0 0x00007fd4adf28f37 in ?? ()
#1 0x0000000000000024 in ?? ()
#2 0x00007fd4a5ff31e0 in ?? ()
#3 0x0000000000000000 in ?? ()
Thread 41 (LWP 10072):
#0 0x00007fd4ae05676d in ?? ()
#1 0x00007fd1f3864396 in ?? ()
#2 0x0000000000000000 in ?? ()
...
{noformat}
> pq.read_table doesn't seem to be thread safe
> --------------------------------------------
>
> Key: ARROW-17984
> URL: https://issues.apache.org/jira/browse/ARROW-17984
> Project: Apache Arrow
> Issue Type: Bug
> Components: Parquet
> Affects Versions: 9.0.0
> Reporter: Ziheng Wang
> Priority: Major
> Attachments: _usr_bin_python3.8.1000.crash
>
>
> Before PR: [https://github.com/apache/arrow/pull/13799] gets merged in
> master, I am using multithreading to improve read bandwidth from S3. Even
> after that PR gets merged, I probably will still try to use multithreading to
> some extent.
> However pq.read_table from S3 doesn't seem to be thread safe. Seems like it
> uses the new dataset reader under the hood. I cannot provide a reproduction,
> not a stable one anyway. But this is roughly the script I have been using
> ~~~
> def get_next_batch(self, mapper_id, pos=None):
> def download(file):
> return pq.read_table("s3://" + self.bucket + "/" + file,
> columns=self.columns, filters=self.filters)
>
> executor = concurrent.futures.ThreadPoolExecutor(max_workers=self.workers)
> futures= \{executor.submit(download, file): file for file in my_files}
> for future inconcurrent.futures.as_completed(futures):
> yield future.result()
> ~~~
> The errors all have to do with malloc segfaults which makes me suspect the
> connection object is being reused across different pq.read_table invocations
> in different threads
> ```
> (InputReaderNode pid=25001, ip=172.31.60.29) malloc_consolidate(): invalid
> chunk size
> (InputReaderNode pid=25001, ip=172.31.60.29) *** SIGABRT received at
> time=1665464922 on cpu 9 ***
> (InputReaderNode pid=25001, ip=172.31.60.29) PC: @ 0x7f9a480a803b
> (unknown) raise
> (InputReaderNode pid=25001, ip=172.31.60.29) @ 0x7f9a480a80c0
> 4160 (unknown)
> (InputReaderNode pid=25001, ip=172.31.60.29) @ 0x7f9a480fa32c
> (unknown) (unknown)
> ```
> Note, this multithreaded code is running inside a Ray actor process, but that
> shouldn't be a problem.
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