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fix: improve runtime complexity of post-job checkpoint handling#3096

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johanneskoester merged 2 commits intomainfrom
fix/checkpoint-handling-perf
Sep 20, 2024
Merged

fix: improve runtime complexity of post-job checkpoint handling#3096
johanneskoester merged 2 commits intomainfrom
fix/checkpoint-handling-perf

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@johanneskoester johanneskoester commented Sep 19, 2024 •
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QC

  • The PR contains a test case for the changes or the changes are already covered by an existing test case.
  • The documentation (docs/) is updated to reflect the changes or this is not necessary (e.g. if the change does neither modify the language nor the behavior or functionalities of Snakemake).

Summary by CodeRabbit

  • New Features

    • Introduced an internal state management mechanism for checkpoint jobs, enhancing the tracking and clarity of job execution status.

  • Bug Fixes

    • Improved logic for managing temporary file deletions based on the presence of checkpoint jobs, resulting in more efficient operations.

  • Improvements

    • Simplified logging for job scheduling, focusing on essential information and removing unnecessary details for better clarity.
    • Added comments to clarify complexities in job selection processes, ensuring better understanding of the code operations.

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coderabbitai bot commented Sep 19, 2024 •
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Walkthrough

The changes introduce a new internal state management system for checkpoint jobs in the Snakemake job dependency graph. A set named _checkpoint_jobs is created to track these jobs, populated during the update_needrun function. The checkpoint_jobs property is modified to return this set directly. The finish method is updated to remove finished jobs from _checkpoint_jobs, and the logic for checking checkpoint jobs is simplified, enhancing clarity and efficiency in managing job states.

Changes

Files Change Summary
snakemake/dag.py - Added _checkpoint_jobs to track checkpoint jobs.
- Modified checkpoint_jobs to return _checkpoint_jobs.
- Updated update_needrun to manage _checkpoint_jobs.
- Revised finish to remove finished checkpoint jobs from _checkpoint_jobs.
snakemake/scheduler.py - Simplified logging for ready jobs and job completion.
- Streamlined job selection logic and resource management logging.
- Added comments to clarify complexity of operations.

Possibly related PRs

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Commits

Files that changed from the base of the PR and between ad40df2 and 774d785.

Files selected for processing (2)
  • snakemake/dag.py (6 hunks)
  • snakemake/scheduler.py (3 hunks)
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  • snakemake/dag.py
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snakemake/scheduler.py (1)

Pattern **/*.py: Do not try to improve formatting.
Do not suggest type annotations for functions that are defined inside of functions or methods.
Do not suggest type annotation of the self argument of methods.
Do not suggest type annotation of the cls argument of classmethods.
Do not suggest return type annotation if a function or method does not contain a return statement.

Additional comments not posted (4)
snakemake/scheduler.py (4)

266-273: LGTM!

The added debug logging statements provide useful insights into the job selection process without altering the core logic. The check for self._last_job_selection_empty is a nice optimization to avoid redundant info messages.

332-334: Useful performance note!

The comment is a helpful reminder to keep the loop operations efficient and avoid quadratic complexity. It's important to be mindful of performance, especially as the number of jobs scales up. Good catch!

625-625: Appropriate fallback mechanism!

The warning log and fallback to the greedy solver provide a robust mechanism to handle cases where the ILP solver fails to find an optimal solution. This ensures that job scheduling can continue while keeping the user informed about the solver's status.

Line range hint 1-800: Overall assessment: Approved!

The changes made in this file focus on enhancing the logging, performance, and robustness of the job scheduler without altering its core functionality. The added debug logs provide valuable insights into the job selection process, making it easier to monitor and troubleshoot. The performance note comment serves as a helpful reminder to keep loop operations efficient and avoid quadratic complexity. Additionally, the fallback mechanism ensures that job scheduling can proceed even if the ILP solver fails to find an optimal solution.

Overall, these changes contribute positively to the maintainability, observability, and reliability of the job scheduler. Great work!

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Actionable comments posted: 1

Review details

Configuration used: CodeRabbit UI
Review profile: CHILL

Commits

Files that changed from the base of the PR and between 56a1f20 and ad40df2.

Files selected for processing (1)
  • snakemake/dag.py (6 hunks)
Additional context used
Path-based instructions (1)
snakemake/dag.py (1)

Pattern **/*.py: Do not try to improve formatting.
Do not suggest type annotations for functions that are defined inside of functions or methods.
Do not suggest type annotation of the self argument of methods.
Do not suggest type annotation of the cls argument of classmethods.
Do not suggest return type annotation if a function or method does not contain a return statement.

Additional comments not posted (5)
snakemake/dag.py (5)

104-104: Proper initialization of _checkpoint_jobs

Initializing _checkpoint_jobs in the constructor ensures a clean state for tracking checkpoint jobs throughout the DAG lifecycle.

252-252: Efficient retrieval of checkpoint jobs

Returning self._checkpoint_jobs directly in the checkpoint_jobs property enhances performance by avoiding redundant computation.

1339-1339: Clearing _checkpoint_jobs before updating

Resetting _checkpoint_jobs at the start of update_needrun prevents stale checkpoint jobs from persisting across updates.

1418-1419: Accurate tracking of checkpoint jobs in update_needrun

By adding jobs where job.is_checkpoint is True to _checkpoint_jobs, we ensure that all checkpoint jobs are correctly tracked during the need-run analysis.

1906-1906: Removing finished checkpoint jobs from tracking

Updating _checkpoint_jobs with difference_update after job completion maintains the accuracy of the checkpoint job set.

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sonarqubecloud bot commented Sep 20, 2024

Quality Gate Passed Quality Gate passed

Issues
0 New issues
0 Accepted issues

Measures
0 Security Hotspots
0.0% Coverage on New Code
0.0% Duplication on New Code

See analysis details on SonarCloud

@johanneskoester johanneskoester merged commit ba30781 into main Sep 20, 2024
@johanneskoester johanneskoester deleted the fix/checkpoint-handling-perf branch September 20, 2024 08:35
@github-actions github-actions bot mentioned this pull request Sep 20, 2024
Merged
johanneskoester pushed a commit that referenced this pull request Sep 20, 2024
@github-actions
chore(main): release 8.20.4 (#3094)
4baebfb 
🤖 I have created a release *beep* *boop*
---


##
[8.20.4](v8.20.3...v8.20.4)
(2024-09-20)


### Bug Fixes

* cache conda envs to fix performance regression introduced in
#1300
([#3093](#3093))
([66600c4](66600c4))
* Flatten conda pip dependencies for report rule info
([#3085](#3085))
([56a1f20](56a1f20))
* improve runtime complexity of post-job checkpoint handling
([#3096](#3096))
([ba30781](ba30781))


### Documentation

* Clarify the lookup function docstring
([#3091](#3091))
([94177d5](94177d5))
* Update lookup signature
([#3090](#3090))
([655d6a1](655d6a1))

---
This PR was generated with [Release
Please](https://github.com/googleapis/release-please). See
[documentation](https://github.com/googleapis/release-please#release-please).

Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
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