Quantify Issues

Recent GitHub Issues Activity

_{Like all software activity quantification, these numbers are imperfect but sometimes useful. Comments, Labels, and Milestones refer to those issues opened in the timespan in question.}

Quantify commits

Quantified Commit Activity Over 30 Days

Developer	Avatar	Branches	PRs	Commits	Files	Changes
Jingsong Lee		2	20/19/0	37	265	8860
yunfengzhou-hub		1	4/2/0	2	68	5299
Xiduo You		1	13/12/1	12	59	1708
YeJunHao		1	18/15/3	15	60	1676
tsreaper		1	8/5/2	5	20	1656
HunterXHunter		1	8/7/1	7	33	1459
Kerwin		1	4/5/0	5	39	1181
xuzifu666		1	13/8/4	8	43	1019
herefree		1	7/6/1	6	19	971
mircodee		1	0/1/0	1	3	547
askwang		1	7/5/0	5	27	447
Fang Yong		1	4/3/0	3	8	395
Zouxxyy		1	9/5/1	5	12	304
LsomeYeah		1	3/3/0	3	17	255
yuzelin		1	8/5/1	5	39	238
Weijie Guo		1	2/1/0	1	3	223
chenxinwei		1	2/2/0	2	9	215
lipeng186		1	1/1/0	1	10	143
Joey		1	1/1/0	1	5	96
WenjunMin		1	2/2/0	2	5	93
Yann Byron		1	2/1/1	1	2	71
liming.1018		1	3/2/0	2	5	65
Yubin Li		1	1/1/0	1	2	56
monster		1	3/1/1	1	4	48
MOBIN		1	2/1/0	1	4	42
wangwj		1	2/1/0	1	1	18
Andrei Kaigorodov		1	1/1/0	1	2	11
chun.ji		1	1/1/0	1	1	10
Jie Feng		1	1/1/0	1	1	8
Harvey Yue		1	2/1/0	1	1	5
DBG		1	1/1/0	1	1	4
dongsj		1	1/1/0	1	1	2
None (dependabot[bot])		1	1/0/0	1	1	2
Hervé Boutemy		1	1/1/0	1	1	1
None (rfyu)		0	1/0/0	0	0	0
None (bknbkn)		0	1/0/0	0	0	0
xiangyu0xf (xiangyuf)		0	1/0/0	0	0	0
Ikko Eltociear Ashimine (eltociear)		0	1/0/0	0	0	0
Fantasy-Jay (zhuyaogai)		0	1/0/0	0	0	0
None (awol2005ex)		0	1/0/0	0	0	0
None (davedwwang)		0	1/0/0	0	0	0
None (zhourui999)		0	1/0/1	0	0	0
Daoyuan Wang (adrian-wang)		0	1/0/0	0	0	0
HeavenZH (discivigour)		0	1/0/0	0	0	0
None (fengDianDemaNong)		0	1/0/1	0	0	0

_{PRs: created by that dev and opened/merged/closed-unmerged during the period}

Report On: Fetch issues

Recent Activity Analysis

The recent GitHub issue activity for the Apache Paimon project shows a total of 345 open issues, with a notable influx of enhancements and bug reports. Recent issues highlight ongoing challenges with data synchronization, particularly in relation to CDC (Change Data Capture) functionalities, and the integration of various data formats. A recurring theme is the need for improved performance and stability, especially regarding partition management and query efficiency.

Several issues indicate that users are experiencing significant problems with data integrity and performance, such as unexpected exceptions during data writes and difficulties with handling schema changes in real-time environments. The project appears to be actively addressing these concerns, but the volume of issues suggests that there may be underlying architectural challenges that need to be resolved.

Issue Details

Here are some of the most recently created and updated issues:

1. Issue #4216: [Feature] Support for the create table like syntax of the spark sql engine

   • Priority: Enhancement
   • Status: Open
   • Created: 2 days ago
   • Last Updated: N/A

2. Issue #4209: [Feature] Support nested projection push down

   • Priority: Enhancement
   • Status: Open
   • Created: 2 days ago
   • Last Updated: N/A

3. Issue #4205: [Feature] In paimon catalog, add partition query and cache

   • Priority: Enhancement
   • Status: Open
   • Created: 3 days ago
   • Last Updated: N/A

4. Issue #4188: [Feature] ConfigOption add sinceVersion

   • Priority: Enhancement
   • Status: Open
   • Created: 7 days ago
   • Last Updated: 4 days ago

5. Issue #4182: [Bug] Different Serializing Name

   • Priority: Bug
   • Status: Open
   • Created: 9 days ago
   • Last Updated: N/A

6. Issue #4174: [Feature] Query SQL Audit

   • Priority: Enhancement
   • Status: Open
   • Created: 9 days ago
   • Last Updated: N/A

7. Issue #4166: [Bug] Branches Table created_from_snapshot field result error.

   • Priority: Bug
   • Status: Open
   • Created: 10 days ago
   • Last Updated: N/A

8. Issue #4163: [Bug] Incorrectly including tables matching excludingTablePattern in combined mode cdc.

   • Priority: Bug
   • Status: Open
   • Created: 11 days ago
   • Last Updated: N/A

Analysis of Notable Issues

• The enhancement requests (#4216, #4209, #4205) indicate a strong demand for more flexible querying capabilities and improved integration with existing SQL standards, which could enhance usability for developers transitioning from other systems.

• The bug reports (#4182, #4166, #4163) reflect critical issues that could impact data integrity and application stability. For instance, discrepancies in serialization names could lead to confusion during data processing, while incorrect handling of table patterns in CDC could result in missed updates or erroneous reads.

• The consistent focus on features related to SQL auditing and configuration options suggests that users are looking for more robust governance and management capabilities within Paimon.

Overall, while there is significant activity around enhancements and bug fixes, the volume of open issues indicates that the project may be facing challenges in scaling its architecture to meet user needs effectively.

Report On: Fetch pull requests

Overview

The provided datasets detail a range of pull requests (PRs) from the Apache Paimon project, showcasing various contributions, bug fixes, feature enhancements, and optimizations. The PRs cover a wide array of topics, including improvements to the core functionality, enhancements for specific integrations like Spark and Flink, and updates to documentation and testing frameworks.

Summary of Pull Requests

Recent Merged Pull Requests

• PR #4220: Fixed an issue where schema files were regenerated unnecessarily upon Flink CDC job restarts with unchanged table options.
• PR #4218: Updated Spark version from 3.5.2 to 3.5.3 to include bug fixes affecting Paimon.
• PR #4212: Corrected an error in documentation regarding primary key configuration during table creation.
• PR #4211: Addressed an issue with unspecified value parameters when using PaimonMetadataColumn.get method.
• PR #4210: Added test cases for reading nested types with pruning in format operations.
• PR #4207: Implemented distributed orphan file cleaning for Spark, enhancing performance and scalability.

Notable Closed Pull Requests

• PR #4206: Optimized IncrementalStartingScanner for better performance by utilizing thread pools for manifest file reading.
• PR #4203: Adjusted behavior of unaware bucket CDC sinks to prevent unnecessary chaining operations.
• PR #4202: Modified Kafka database synchronization to allow new tables without requiring primary keys initially.

Analysis of Pull Requests

The analysis reveals several key themes and areas of focus within the Apache Paimon project:

1. Performance Enhancements: Many PRs aim at optimizing existing functionalities, such as distributed processing for orphan file cleaning and parallel execution of snapshot scanning. These enhancements are crucial for handling large datasets efficiently.

2. Integration Improvements: There is a continuous effort to improve integrations with other systems like Spark and Flink. This includes updating dependencies (e.g., bumping Spark versions) and enhancing features that rely on these integrations (e.g., supporting distributed operations in Spark).

3. Bug Fixes and Stability Improvements: Several PRs address specific bugs or issues that affect the stability or correctness of the system. This includes fixing errors related to metadata handling, improving exception handling in compression algorithms, and ensuring correct behavior under various operational scenarios.

4. Community Contributions and Engagement: The diverse range of contributors and the active engagement in addressing issues and enhancing features reflect a healthy open-source community around Apache Paimon. Contributions range from core functionality improvements to documentation updates, showcasing a collaborative effort towards project growth.

5. Focus on Usability and Developer Experience: Enhancements like better error messages, improved documentation, and more intuitive configurations (e.g., allowing customization of table locations) indicate a focus on improving usability for both end-users and developers working on Paimon.

In conclusion, the pull requests demonstrate Apache Paimon's commitment to continuous improvement through performance optimizations, robust integrations, active community engagement, and a focus on usability. These efforts position Paimon as a strong contender in the lakehouse architecture space, catering to modern data processing needs with real-time capabilities.

Report On: Fetch commits

Repo Commits Analysis

Development Team and Recent Activity

Team Members and Activities

1. codeTai

   • Recent Activity: 1 commit, focused on avoiding duplicate schema file generation.
   • Collaborators: None noted.

2. Xiduo You (ulysses-you)

   • Recent Activity: 12 commits, including:
   • Implemented distributed orphan file clean for Spark.
   • Bumped Spark version.
   • Supported partition and bucket metadata column.
   • Fixed compact unreasonable log info.
   • Collaborators: Collaborated with various team members across multiple features.

3. Jingsong Lee (JingsongLi)

   • Recent Activity: 37 commits, including:
   • Optimized IncrementalStartingScanner.
   • Unaware bucket CDC sink changes.
   • Introduced metrics for unaware append table compaction.
   • Various hotfixes and optimizations.
   • Collaborators: Worked with multiple team members on various features.

4. Kerwin (zhuangchong)

   • Recent Activity: 5 commits, including a hotfix for PaimonMetadataColumn and improvements in schema management.
   • Collaborators: None noted.

5. dongsj (eric9204)

   • Recent Activity: 1 commit, fixed documentation regarding primary key configuration.
   • Collaborators: None noted.

6. askwang

   • Recent Activity: 5 commits, including enhancements to compaction procedures and fixes for logging issues.
   • Collaborators: None noted.

7. Hervé Boutemy (hboutemy)

   • Recent Activity: 1 commit, dropped non-reproducible Git-Branch.
   • Collaborators: None noted.

8. Zouxxyy

   • Recent Activity: 5 commits, added test cases and fixed issues related to format read nested types.
   • Collaborators: None noted.

9. yuzelin

   • Recent Activity: 5 commits, including fixes for Kafka database sync and other enhancements.
   • Collaborators: None noted.

10. YeJunHao (leaves12138)

    • Recent Activity: 15 commits, focusing on metrics addition, bug fixes, and performance improvements across various components.
    • Collaborators: Collaborated with multiple team members.

11. liming30

    • Recent Activity: 2 commits related to core optimizations and hotfixes.
    • Collaborators: None noted.

12. harveyyue

    • Recent Activity: 1 commit focused on avoiding loading zstd-jni collisions.
    • Collaborators: None noted.

13. xuzifu666

    • Recent Activity: 8 commits related to Spark integration and enhancements in CDC configurations.
    • Collaborators: Collaborated with various team members.

14. yunfengzhou-hub

    • Recent Activity: 2 commits enhancing procedure support in Flink.
    • Collaborators: None noted.

15. Yann Byron

    • Recent Activity: 1 commit fixing reported statistics issues in Spark integration.
    • Collaborators: None noted.

16. Shadowell

    • Recent Activity: 1 commit adding exception handling in the Zstd compressor.
    • Collaborators: None noted.

17. tsreaper

    • Recent Activity: 5 commits focused on performance improvements and bug fixes across components.
    • Collaborators: Collaborated with various team members.

18. Aitozi

    • Recent Activity: 2 commits related to documentation improvements.
    • Collaborators: None noted.

19. LsomeYeah

    • Recent Activity: 3 commits focused on performance optimizations in Flink procedures.
    • Collaborators: None noted.

20. Additional contributors made minor contributions or updates primarily focused on documentation or specific bug fixes.

Patterns and Themes

• The recent activity reflects a strong focus on optimizing existing features, particularly around orphan file management, CDC integrations, and Spark compatibility enhancements.
• A significant number of contributions are related to fixing bugs and improving documentation, indicating a commitment to quality and usability of the project.
• Collaboration among team members is evident, particularly with Jingsong Lee leading multiple initiatives that involve cross-functional contributions from different developers.
• The volume of changes from certain contributors (e.g., Jingsong Lee and Xiduo You) suggests they are heavily involved in ongoing development efforts, likely indicating their roles as key maintainers or leads within the project.

Conclusion

The development team is actively engaged in enhancing the Apache Paimon project through a mix of feature development, bug fixes, and documentation improvements. The collaborative nature of the team's efforts is evident in the overlapping contributions across different functionalities, showcasing a robust development environment aimed at continuous improvement of the software's capabilities.