[jira] [Created] (ARROW-17984) pq.read_table doesn't seem to be thread safe

["Ziheng Wang (Jira)" <ji...@apache.org>]

Ziheng Wang created ARROW-17984:
-----------------------------------

             Summary: 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


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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