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[fix](compaction) reduce memory cost for cloud compaction of mow table #43502

Merged
merged 2 commits into from
Nov 11, 2024
Merged

[fix](compaction) reduce memory cost for cloud compaction of mow table #43502

merged 2 commits into from
Nov 11, 2024

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zhannngchen
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@zhannngchen zhannngchen commented Nov 8, 2024 •
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What problem does this PR solve?

Issue Number: close #xxx

Related PR: #36865

Problem Summary:

#36865 reduced the memory cost for compactions of MoW table
But when we merge the codes for cloud, such optimization is not applied for cloud compaction
We found several cases that compaction of MoW table consume lots of memory on cloud, this PR try to fix this issue

Release note

None

Check List (For Author)

  • Test

    • Regression test
    • Unit Test
    • Manual test (add detailed scripts or steps below)
    • No need to test or manual test. Explain why:
      • This is a refactor/code format and no logic has been changed.
      • Previous test can cover this change.
      • No code files have been changed.
      • Other reason: memory consumption is not easy to test on regression test, it's already tested in our test environment.

  • Behavior changed:

    • No.
    • Yes.

  • Does this need documentation?

    • No.
    • Yes.

Check List (For Reviewer who merge this PR)

  • Confirm the release note
  • Confirm test cases
  • Confirm document
  • Add branch pick label

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Thank you for your contribution to Apache Doris.
Don't know what should be done next? See How to process your PR.

Please clearly describe your PR:

  1. What problem was fixed (it's best to include specific error reporting information). How it was fixed.
  2. Which behaviors were modified. What was the previous behavior, what is it now, why was it modified, and what possible impacts might there be.
  3. What features were added. Why was this function added?
  4. Which code was refactored and why was this part of the code refactored?
  5. Which functions were optimized and what is the difference before and after the optimization?

@zhannngchen
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run buildall

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github-actions bot commented Nov 8, 2024

clang-tidy review says "All clean, LGTM! 👍"

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github-actions bot commented Nov 8, 2024

clang-tidy review says "All clean, LGTM! 👍"

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TeamCity be ut coverage result:
Function Coverage: 37.90% (9863/26026)
Line Coverage: 29.09% (82242/282761)
Region Coverage: 28.23% (42318/149928)
Branch Coverage: 24.77% (21425/86484)
Coverage Report: http://coverage.selectdb-in.cc/coverage/35ca3020da93a5e7b3294da6193559bfd1b39667_35ca3020da93a5e7b3294da6193559bfd1b39667/report/index.html

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run buildall

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TeamCity be ut coverage result:
Function Coverage: 37.91% (9866/26027)
Line Coverage: 29.08% (82244/282788)
Region Coverage: 28.23% (42335/149941)
Branch Coverage: 24.79% (21440/86500)
Coverage Report: http://coverage.selectdb-in.cc/coverage/feae15eaef306f228177757793c350eeabb3f20a_feae15eaef306f228177757793c350eeabb3f20a/report/index.html

dataroaring
dataroaring approved these changes Nov 11, 2024
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LGTM

@github-actions github-actions bot added the approved Indicates a PR has been approved by one committer. label Nov 11, 2024
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PR approved by at least one committer and no changes requested.

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PR approved by anyone and no changes requested.

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run p0

@zhannngchen zhannngchen merged commit 68aa0d0 into apache:master Nov 11, 2024
25 of 28 checks passed
zhannngchen added a commit to zhannngchen/incubator-doris that referenced this pull request Nov 11, 2024
@zhannngchen
[fix](compaction) reduce memory cost for cloud compaction of mow table (
f6956b7 
apache#43502)

Related PR: apache#36865

Problem Summary:

But when we merge the codes for cloud, such optimization is not applied
for cloud compaction
We found several cases that compaction of MoW table consume lots of
memory on cloud, this PR try to fix this issue

Co-authored-by: Chen Zhang <zhangchen@selectdb.com>
@zhannngchen zhannngchen mentioned this pull request Nov 11, 2024
Merged
zhannngchen added a commit that referenced this pull request Nov 12, 2024
@zhannngchen
[fix](compaction) reduce memory cost for cloud compaction of mow table (
f72ff09 
#43502) (#43633)

cherry-pick #43502
zzzxl1993 pushed a commit to zzzxl1993/doris that referenced this pull request Nov 12, 2024
@zhannngchen @zzzxl1993
[fix](compaction) reduce memory cost for cloud compaction of mow table (
e03d32f 
apache#43502)

Related PR: apache#36865

Problem Summary:

apache#36865 reduced the memory cost for compactions of MoW table
But when we merge the codes for cloud, such optimization is not applied
for cloud compaction
We found several cases that compaction of MoW table consume lots of
memory on cloud, this PR try to fix this issue

Co-authored-by: Chen Zhang <zhangchen@selectdb.com>
924060929 pushed a commit to 924060929/incubator-doris that referenced this pull request Nov 12, 2024
@zhannngchen @924060929
[fix](compaction) reduce memory cost for cloud compaction of mow table (
a77f975 
apache#43502)

Related PR: apache#36865

Problem Summary:

apache#36865 reduced the memory cost for compactions of MoW table
But when we merge the codes for cloud, such optimization is not applied
for cloud compaction
We found several cases that compaction of MoW table consume lots of
memory on cloud, this PR try to fix this issue

Co-authored-by: Chen Zhang <zhangchen@selectdb.com>
py023 pushed a commit to py023/doris that referenced this pull request Nov 13, 2024
@zhannngchen @py023
[fix](compaction) reduce memory cost for cloud compaction of mow table (
4a81be9 
apache#43502)

Related PR: apache#36865

Problem Summary:

apache#36865 reduced the memory cost for compactions of MoW table
But when we merge the codes for cloud, such optimization is not applied
for cloud compaction
We found several cases that compaction of MoW table consume lots of
memory on cloud, this PR try to fix this issue

Co-authored-by: Chen Zhang <zhangchen@selectdb.com>
BiteTheDDDDt pushed a commit to BiteTheDDDDt/incubator-doris that referenced this pull request Feb 7, 2025
@zhannngchen @gavinchou
[fix](compaction) reduce memory cost for cloud compaction of mow table (
35fb132 
apache#43502) (apache#43633)

cherry-pick apache#43502
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@gavinchou gavinchou gavinchou approved these changes

@dataroaring dataroaring dataroaring approved these changes

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