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Posted to jira@arrow.apache.org by "Ziheng Wang (Jira)" <ji...@apache.org> on 2022/10/11 05:33:00 UTC
[jira] [Updated] (ARROW-17984) pq.read_table doesn't seem to be thread safe
[ https://issues.apache.org/jira/browse/ARROW-17984?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Ziheng Wang updated ARROW-17984:
--------------------------------
Description:
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.
was:
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.
> 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
>
> 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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