[fix](cloud) fix routine load job progress cache incorrect in cloud mode #39313
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
|
Thank you for your contribution to Apache Doris. Since 2024-03-18, the Document has been moved to doris-website. |
|
run buildall |
TPC-H: Total hot run time: 40003 ms |
TPC-DS: Total hot run time: 186090 ms |
ClickBench: Total hot run time: 31.16 s |
|
PR approved by at least one committer and no changes requested. |
github-actions
bot
added
approved
|
PR approved by anyone and no changes requested. |
wyxxxcat
pushed a commit
to wyxxxcat/doris
that referenced
this pull request
Aug 14, 2024
…ode (apache#39313) Routine load job progress cache incorrect in cloud mode in the following scenario: 1. schedule thread update cloud progress, get old transaction value in fdb. 2. routine load task commit transaction and update progress cache. 3. update cloud progress RPC return, and change progress value to old value which is incorrect. This PR solves the problem that may occur in the storage computation separation mode by not allowing small values to overwrite large values.
dataroaring
pushed a commit
that referenced
this pull request
Aug 17, 2024
…ode (#39313) Routine load job progress cache incorrect in cloud mode in the following scenario: 1. schedule thread update cloud progress, get old transaction value in fdb. 2. routine load task commit transaction and update progress cache. 3. update cloud progress RPC return, and change progress value to old value which is incorrect. This PR solves the problem that may occur in the storage computation separation mode by not allowing small values to overwrite large values.
16 tasks
dataroaring
pushed a commit
that referenced
this pull request
Jan 7, 2025
…46149) In cloud mode, routine load loss data when fe master node restart. When updating progress, in order to avoid small values covering large values, we introduced pr #39313, Due to the pr that the routine load replays progress metadata by first obtaining the set default offset and then pulling metadata from meta service to update the local value, if the metadata pulled from meta service is not larger than the set default offset, the correct value cannot be assigned to memory. To solve this problem, pulling metadata from meta service when restart, determine whether to obtain default offset from Kafka based on the pulled value.
github-actions bot
pushed a commit
that referenced
this pull request
Jan 7, 2025
…46149) In cloud mode, routine load loss data when fe master node restart. When updating progress, in order to avoid small values covering large values, we introduced pr #39313, Due to the pr that the routine load replays progress metadata by first obtaining the set default offset and then pulling metadata from meta service to update the local value, if the metadata pulled from meta service is not larger than the set default offset, the correct value cannot be assigned to memory. To solve this problem, pulling metadata from meta service when restart, determine whether to obtain default offset from Kafka based on the pulled value.
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.
Routine load job progress cache incorrect in cloud mode in the following scenario:
This PR solves the problem that may occur in the storage computation separation mode by not allowing small values to overwrite large values.