[improve](routine load) delay schedule EOF tasks to avoid too many small transactions (#39975) #40509
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
…all transactions (#39975) We encountered a scenario where a large number of small transactions were generated, resulting in an impact on query performance: Kafka's data comes in batches of very small data every very short time, which leads to tasks being frequently scheduled and ending very quickly, resulting in a large number of small transactions. To solve this problem, we delay the scheduling of tasks that perceive EOF, which would not delay data consumption, for perceiving EOF indicates that the consumption speed is greater than the production speed.
|
Thank you for your contribution to Apache Doris. Since 2024-03-18, the Document has been moved to doris-website. |
Contributor
Author
|
run buildall |
Closed
Closed
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Outdated suggestions cannot be applied.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.
pick (#39975)
We encountered a scenario where a large number of small transactions were generated, resulting in an impact on query performance: Kafka's data comes in batches of very small data every very short time, which leads to tasks being frequently scheduled and ending very quickly, resulting in a large number of small transactions.
To solve this problem, we delay the scheduling of tasks that perceive EOF, which would not delay data consumption, for perceiving EOF indicates that the consumption speed is greater than the production speed.