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Impact of the new feature
Global WorkQueue CherryPy thread
Is your feature request related to a problem? Please describe.
This feature needs to be deployed together with: #11620
As we move from full to partial pileup container support within WM, we need to ensure that the Global WorkQueue LocationUpdateTask thread starts executing pileup location look-up based on the pileup blocks (rucio datasets), such that their location can be properly reflected in the workqueue elements.
Describe the solution you'd like
Granularity of the pileup data location needs to be refactored from Rucio container to dataset level. In addition, we need to adopt a concurrent library to ensure that this task can properly scale with the very large pileup containers (e.g. 30k rucio datasets).
Data availability follows this logic:
if the workqueue element is set to NoPileupUpdate=true, then we do not need to perform and data location update; otherwise
each RSE that hosts at least 1 rucio dataset should be marked as an actual location for that pileup dataset.
Note that if http requests fail, there is nothing to be done and we retry it in the next cycle.
Describe alternatives you've considered
For the http library, we can either use pycurl_manager or asyncio.
Additional context
This is part of the meta issue: #11537
The text was updated successfully, but these errors were encountered:
@d-ylee Hi Dennis, yes. I am in favor of adopting MSPileup data everywhere in the WM system that pileup location needs to be resolved.
For this CherryPy thread, it will likely be one HTTP call to fetch the pileup information; the rest is only local processing of that data and the usual pileup location update within the workflows (workqueue elements).
If you prefer, I am happy to have a chat to go over the details as well. Just ping me on Mattermost.
Impact of the new feature
Global WorkQueue CherryPy thread
Is your feature request related to a problem? Please describe.
This feature needs to be deployed together with: #11620
As we move from full to partial pileup container support within WM, we need to ensure that the Global WorkQueue LocationUpdateTask thread starts executing pileup location look-up based on the pileup blocks (rucio datasets), such that their location can be properly reflected in the workqueue elements.
Describe the solution you'd like
Granularity of the pileup data location needs to be refactored from Rucio container to dataset level. In addition, we need to adopt a concurrent library to ensure that this task can properly scale with the very large pileup containers (e.g. 30k rucio datasets).
Data availability follows this logic:
NoPileupUpdate=true
, then we do not need to perform and data location update; otherwiseNote that if http requests fail, there is nothing to be done and we retry it in the next cycle.
Describe alternatives you've considered
For the http library, we can either use pycurl_manager or asyncio.
Additional context
This is part of the meta issue: #11537
The text was updated successfully, but these errors were encountered: