Optimize token revocation process in EntityFramework stores #2360
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
|
Thanks for your PR! That's indeed a good idea. Can you just split the Cheers. |
Thank you for your feedback! I've made the changes as per your suggestions and updated the pull request. |
|
Merged. Congrats for your first contribution to OpenIddict! 🎉 |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
I think it's possible to create a scenario where someone intentionally uses the same token twice to trigger the revocation process, leading to a large number of updates and excessive resource usage.
This pull request optimizes the token revocation process by filtering out already revoked tokens, reducing memory usage and unnecessary updates. The current implementation loads all tokens into memory and manually updates each one, which can lead to excessive data being loaded and a high number of unnecessary update operations. By filtering out already revoked tokens, we reduce memory usage and improve performance.