Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

[Improvement]: Improve query speed for Mixed tables in Spark #1349

Closed
3 tasks done
shidayang opened this issue Apr 14, 2023 · 0 comments · Fixed by #1351
Closed
3 tasks done

[Improvement]: Improve query speed for Mixed tables in Spark #1349

shidayang opened this issue Apr 14, 2023 · 0 comments · Fixed by #1351
Labels
module:mixed-spark Spark module for Mixed Format type:improvement
Milestone
Release 0.5.0

Comments

@shidayang
Copy link
Contributor

shidayang commented Apr 14, 2023 •
edited
Loading

Search before asking

  • I have searched in the issues and found no similar issues.

What would you like to be improved?

I want to improve the performance of MOR
It spend 4s when querying static table, but it spend 40s when querying a table containing delete file

How should we improve?

No response

Are you willing to submit PR?

  • Yes I am willing to submit a PR!

Subtasks

No response

Code of Conduct
@shidayang shidayang mentioned this issue Apr 14, 2023
Merged
3 tasks
@zhoujinsong zhoujinsong added this to the Release 0.5.0 milestone Apr 17, 2023
@zhoujinsong zhoujinsong added the module:mixed-spark Spark module for Mixed Format label Apr 17, 2023
@zhoujinsong zhoujinsong mentioned this issue Apr 17, 2023
Closed
27 tasks
@zhoujinsong zhoujinsong changed the title [Improvement]: Spark MOR too slow [Improvement]: Improve query speed for Mixed tables in Spark Aug 2, 2023
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Assignees
No one assigned
Labels
module:mixed-spark Spark module for Mixed Format type:improvement
Projects
None yet
Milestone
Release 0.5.0
2 participants
@zhoujinsong @shidayang