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From what I can tell in my browse of this there are the following existing issues:
In the distributed case casacore::tables rely on OS-supported flocks (sysctl) which are not guaranteed to be safe to use in shared storage between machines (there is no awareness of node IP or other identifying criteria. Looking at this: https://github.com/ratt-ru/dask-ms/blob/master/daskms/table_executor.py#L38-L54 if multiple dask processes each backed with a threadpool and queue pointing to a database on a shared filesystem are started on multiple nodes there is no guarantee that the flocks will hold.
The same "user-style" read and write locking will need to be applied for xarray-backed datasets as far as I can tell via context management, although I'm not sure how finely the arrays are "bucketed" in the array specification for this to work.
The text was updated successfully, but these errors were encountered:
bennahugo
changed the title
How to deal with locks propper in a distributed environment
How to deal with file locks propper in a distributed environment
Mar 24, 2022
JSKenyon
changed the title
How to deal with file locks propper in a distributed environment
How to deal with file locks properly in a distributed environment
Mar 30, 2022
Just plotting down ideas for discussion for now:
From what I can tell in my browse of this there are the following existing issues:
The text was updated successfully, but these errors were encountered: