Fetch revisions in small batches. #13
Closed
Conversation
This file contains 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
If there are a large number of revisions to fetch (e.g., 20,000) then the request can time out and the process can run out of memory. Fixes markjaquith#9
Previously, if a large number of revisions were being fetched (e.g., 100,000), the number of duplicates would grow exponentially and the process could run out of memory before it purged them at the end of the loop. Purging them on each iteration is more expensive, but necessary to keep the process alive in those circumstances. See markjaquith#9
|
FWIW, I've been holding onto a slightly more robust version of batching for this for a couple of months. I submitted the PR over on #14 if you're interested in a different take. Whoops :) |
|
Closing in favor of #14 |
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Outdated suggestions cannot be applied.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.
If there are a large number of revisions to fetch (e.g., 20,000) then the request can time out and the process can run out of memory.
Fixes #9