Skip to content

Add warning about HDFStore concurrent reads #7944

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Closed
wants to merge 1 commit into from
Closed

Add warning about HDFStore concurrent reads #7944

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
3 changes: 3 additions & 0 deletions doc/source/io.rst
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -2956,6 +2956,9 @@ Notes & Caveats
need to serialize these operations in a single thread in a single
process. You will corrupt your data otherwise. See the issue
(:`2397`) for more information.
- ``HDFStore`` may not support concurrent reads either, depending on the
underlying version of ``PyTables`` being used. See issue (:`7838`)
Copy link
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

I thought it was dependent on the version of HDF5 not PyTables.

Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

that's right, its techincally the HDF5 version (though PyTables does have some differences, e.g. < 3.1 does allow concurrent reads, while 3.1 is pretty strict).

Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

@yikelu actually if you don't mind, can you break this out into a separate section (maybe before Caveats), related to issue: #7838 (e.g. take some of the info from their too)...then can close that issue

for more information.
- If you use locks to manage write access between multiple processes, you
may want to use :py:func:`~os.fsync` before releasing write locks. For
convenience you can use ``store.flush(fsync=True)`` to do this for you.
Expand Down