[storm-client] Add missing logging to TridentBoltExecutor on tuple count mismatch failures#8414
Merged
rzo1 merged 1 commit intoapache:masterfrom Mar 2, 2026
Merged
Conversation
reiabreu
approved these changes
Mar 1, 2026
Contributor
reiabreu
left a comment
reiabreu
left a comment
There was a problem hiding this comment.
Thanks for the contribution @Ironankit525
rzo1
approved these changes
Mar 2, 2026
Contributor
|
Thanks! |
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
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
3 participants
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Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be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.
Addresses Issue #3 from static analysis.
When verifying if a Trident batch finish condition is met, the executor checks if the number of received tuples matches the number of actual tuple counts. If there is a mismatch, the executor invokes failBatch(tracked) and rejects the tuple, but without any logging indicating the mismatch.
This PR adds an SLF4J
LOG.warnexplaining the mismatch so that operators can correctly diagnose data loss or malformed batches.