taosdata/TDengine
Mar 2025 – May 2026
15 Months active
Languages Used
CC++CMakeMarkdownPythonSQLyaccINI
Technical Skills
Backend DevelopmentBug FixBug FixingBuild SystemC ProgrammingC programming
Jing Sima
PROFILE
Jing Sima
Over 15 months, this developer advanced core features and reliability for taosdata/TDengine, focusing on virtual tables, streaming, and time-series analytics. They engineered robust query optimization and schema validation, delivering enhancements such as decimal data type support, pushdown aggregation, and two-phase window query splitting. Their work included performance tuning, memory management, and error handling improvements, using C, C++, and Python across backend and database internals. By contributing to both code and documentation, they enabled faster analytics, improved data integrity, and streamlined onboarding for developers and DBAs, ensuring TDengine’s virtual table and streaming capabilities met demanding real-time analytics requirements.
Overall Statistics
Feature vs Bugs
66%Features
Repository Contributions
348Total
Bugs
54
Commits
348
Features
105
Lines of code
1,621,154
Activity Months15
Your Network
88 peopleShared Repositories
88
Work History
May 2026
1 Commits • 1 Features
May 1, 2026Month: 2026-05 — TDengine Virtual Table Query Optimization Documentation delivered to guide performance tuning for Industrial IoT workloads. The doc covers Pushdown Aggregation and Two-Phase Window Query Splitting and provides actionable guidance for developers and DBAs. Commit 91ddc16751558120fa71aa9f935960fbb70392f3 documents the change under internal (#35330). No major bugs fixed in taosdata/TDengine this month. Overall impact: improves onboarding, reduces time-to-value for optimization work, and strengthens TDengine's performance guidance. Technologies/skills demonstrated include technical writing, performance optimization concepts, TDengine internals understanding, and git-based collaboration.
1 Commits • 1 Features
May 1, 2026Month: 2026-05 — TDengine Virtual Table Query Optimization Documentation delivered to guide performance tuning for Industrial IoT workloads. The doc covers Pushdown Aggregation and Two-Phase Window Query Splitting and provides actionable guidance for developers and DBAs. Commit 91ddc16751558120fa71aa9f935960fbb70392f3 documents the change under internal (#35330). No major bugs fixed in taosdata/TDengine this month. Overall impact: improves onboarding, reduces time-to-value for optimization work, and strengthens TDengine's performance guidance. Technologies/skills demonstrated include technical writing, performance optimization concepts, TDengine internals understanding, and git-based collaboration.
May 2026
April 2026
2 Commits • 1 Features
Apr 1, 2026April 2026 monthly summary highlighting key features delivered and bugs fixed in taosdata/TDengine, focusing on business value and technical achievements. The main work centered on virtual tables enhancements to improve data precision and schema integrity, along with robust validation to prevent misalignment between virtual child tables and their super tables.
April 2026
2 Commits • 1 Features
Apr 1, 2026April 2026 monthly summary highlighting key features delivered and bugs fixed in taosdata/TDengine, focusing on business value and technical achievements. The main work centered on virtual tables enhancements to improve data precision and schema integrity, along with robust validation to prevent misalignment between virtual child tables and their super tables.
March 2026
13 Commits • 2 Features
Mar 1, 2026March 2026 — TDengine development focused on performance improvements, stability, and reliability for virtual table operations and overall memory safety. Delivered substantial enhancements to virtual table query optimization and robustness, hardening memory management, and strengthening system integrity, along with improved test validation to ensure reliability in production. These changes drive faster analytic workloads, lower memory pressure, and reduced operational risk, enabling more robust cross-database analytics and more predictable performance.
13 Commits • 2 Features
Mar 1, 2026March 2026 — TDengine development focused on performance improvements, stability, and reliability for virtual table operations and overall memory safety. Delivered substantial enhancements to virtual table query optimization and robustness, hardening memory management, and strengthening system integrity, along with improved test validation to ensure reliability in production. These changes drive faster analytic workloads, lower memory pressure, and reduced operational risk, enabling more robust cross-database analytics and more predictable performance.
March 2026
February 2026
3 Commits • 1 Features
Feb 1, 2026February 2026 – TDengine (taosdata/TDengine). Delivered performance-oriented enhancements to virtual table queries and stabilized core query utilities, enabling faster analytics and more reliable deployments for customers relying on virtual table abstractions.
February 2026
3 Commits • 1 Features
Feb 1, 2026February 2026 – TDengine (taosdata/TDengine). Delivered performance-oriented enhancements to virtual table queries and stabilized core query utilities, enabling faster analytics and more reliable deployments for customers relying on virtual table abstractions.
January 2026
9 Commits • 2 Features
Jan 1, 2026January 2026 TDengine — Delivered core Virtual Tables enhancements and robust error handling for table operations, driving improved query flexibility, reliability, and developer experience. Key outcomes include performance and presentation improvements to Virtual Tables, time-range push-down optimization, higher max references, and corrected show create outputs, along with clearer error handling and targeted error codes for table operations. The changes reduce debugging time, improve data discovery, and strengthen system stability under production workloads.
9 Commits • 2 Features
Jan 1, 2026January 2026 TDengine — Delivered core Virtual Tables enhancements and robust error handling for table operations, driving improved query flexibility, reliability, and developer experience. Key outcomes include performance and presentation improvements to Virtual Tables, time-range push-down optimization, higher max references, and corrected show create outputs, along with clearer error handling and targeted error codes for table operations. The changes reduce debugging time, improve data discovery, and strengthen system stability under production workloads.
January 2026
December 2025
16 Commits • 8 Features
Dec 1, 2025December 2025 TDengine monthly summary focusing on reliability, scalability, and performance of virtual tables and streaming features. Delivered a broad set of feature enhancements and critical bug fixes with clear business value, including improved data integrity, larger virtual table schemas, and more predictable streaming behavior. Key accomplishments include: - Virtual Tables datatype consistency checks and improved error handling during queries (commit references: a353aee17decefee8f54c55826a8ef8310b85182; 9cdae7b025ccb1fe7d8e5bf0f11d40b82fad2443; 2131c8c67c677e149324ac929791a550df68881d). - Flexible virtual table references enabling same column to be used as a reference, with updated data block creation (commits: 4c2c0378fdd7571126fbfb9a4467b8e50d9be0cc; 5044b431b91ef43c163c3c804eca2764086fbf70). - Virtual Super Table enhancements for aggregation performance and correct last(timestamp) behavior (commits: 220d625fc88f8c8858cf807ea0d5fb3f0c26d976; 87a65eb204b1585aae31f432021e6611356155ad). - Memory leak fix in createPartAggNode (commit: b2eed794838aebf1c1a038fd5a95d8a982780836). - Virtual Tables timestamp precision consistency and column limit expansion (commits: ba8749513a1a478118c8a737d1585ce206f7e7b6; 982999def08f6778e220a7dda50c656a651fab21). - Stream creation enhancements including IGNORE_NODATA_TRIGGER option (commits: d5572b03d0c25ca6a189d10611822732ba26a751; 4c0980a71a49a142635fcfac6b00956f6d9d44c8). - Operator parameter serialization improvements for reuse flags and batching with better logging (commit: 5fb86d7b125711cec2b494d5c28fe4ad6f911e29). - Optimized state windows processing in virtual table queries for batch efficiency (commit: 3cb2c4602b97151c728c4ef75f78b0f1a51f0de3). - Merge sort row size bug fixes to ensure correct data handling (commits: 7445697378019a5246fc2aa9b54c804bfe621c7b; d50d486ad38a5b5cd0aeaff28b74680dfe984494). Overall impact: - Increased data integrity and reliability of virtual tables, enabling larger schemas (up to 32767 columns) without compromising accuracy. - Improved performance for virtual tables and streaming workloads, reducing query latency and resource usage. - Reduced memory risk and clearer diagnostics, accelerating incident response and maintenance. Technologies/skills demonstrated: - Deepening expertise in virtual table architecture, streaming semantics, and data block creation. - Performance optimization, memory management, and serialization/deserialization improvements. - Structured commit-based delivery, testing, and documentation alignment for release readiness.
December 2025
16 Commits • 8 Features
Dec 1, 2025December 2025 TDengine monthly summary focusing on reliability, scalability, and performance of virtual tables and streaming features. Delivered a broad set of feature enhancements and critical bug fixes with clear business value, including improved data integrity, larger virtual table schemas, and more predictable streaming behavior. Key accomplishments include: - Virtual Tables datatype consistency checks and improved error handling during queries (commit references: a353aee17decefee8f54c55826a8ef8310b85182; 9cdae7b025ccb1fe7d8e5bf0f11d40b82fad2443; 2131c8c67c677e149324ac929791a550df68881d). - Flexible virtual table references enabling same column to be used as a reference, with updated data block creation (commits: 4c2c0378fdd7571126fbfb9a4467b8e50d9be0cc; 5044b431b91ef43c163c3c804eca2764086fbf70). - Virtual Super Table enhancements for aggregation performance and correct last(timestamp) behavior (commits: 220d625fc88f8c8858cf807ea0d5fb3f0c26d976; 87a65eb204b1585aae31f432021e6611356155ad). - Memory leak fix in createPartAggNode (commit: b2eed794838aebf1c1a038fd5a95d8a982780836). - Virtual Tables timestamp precision consistency and column limit expansion (commits: ba8749513a1a478118c8a737d1585ce206f7e7b6; 982999def08f6778e220a7dda50c656a651fab21). - Stream creation enhancements including IGNORE_NODATA_TRIGGER option (commits: d5572b03d0c25ca6a189d10611822732ba26a751; 4c0980a71a49a142635fcfac6b00956f6d9d44c8). - Operator parameter serialization improvements for reuse flags and batching with better logging (commit: 5fb86d7b125711cec2b494d5c28fe4ad6f911e29). - Optimized state windows processing in virtual table queries for batch efficiency (commit: 3cb2c4602b97151c728c4ef75f78b0f1a51f0de3). - Merge sort row size bug fixes to ensure correct data handling (commits: 7445697378019a5246fc2aa9b54c804bfe621c7b; d50d486ad38a5b5cd0aeaff28b74680dfe984494). Overall impact: - Increased data integrity and reliability of virtual tables, enabling larger schemas (up to 32767 columns) without compromising accuracy. - Improved performance for virtual tables and streaming workloads, reducing query latency and resource usage. - Reduced memory risk and clearer diagnostics, accelerating incident response and maintenance. Technologies/skills demonstrated: - Deepening expertise in virtual table architecture, streaming semantics, and data block creation. - Performance optimization, memory management, and serialization/deserialization improvements. - Structured commit-based delivery, testing, and documentation alignment for release readiness.
November 2025
16 Commits • 3 Features
Nov 1, 2025November 2025 monthly summary for taosdata/TDengine: Focused on reliability, correctness, and performance of time-series features. Delivered key features and stability fixes across external windows, virtual tables, exchange operator, and time window integrity, translating into tangible business value for time-based analytics and CI efficiency.
16 Commits • 3 Features
Nov 1, 2025November 2025 monthly summary for taosdata/TDengine: Focused on reliability, correctness, and performance of time-series features. Delivered key features and stability fixes across external windows, virtual tables, exchange operator, and time window integrity, translating into tangible business value for time-based analytics and CI efficiency.
November 2025
October 2025
9 Commits • 5 Features
Oct 1, 2025Monthly summary for 2025-10 focusing on delivering robust query capabilities, scalable time-series features, and CI improvements in TDengine. Highlights include improvements to time range handling, virtual table scan efficiency, TSMA capacity expansion, CI test refactor, and stream creation precision support.
October 2025
9 Commits • 5 Features
Oct 1, 2025Monthly summary for 2025-10 focusing on delivering robust query capabilities, scalable time-series features, and CI improvements in TDengine. Highlights include improvements to time range handling, virtual table scan efficiency, TSMA capacity expansion, CI test refactor, and stream creation precision support.
September 2025
10 Commits • 1 Features
Sep 1, 2025September 2025 TDengine monthly summary focused on delivering new analytics capability, stabilizing streaming workloads, and improving documentation to reduce misuse. Key outcomes include delivering TSMA support, hardening the stream engine for production reliability, fixing nanosecond precision issues, and clarifying documentation to align expectations with capabilities.
10 Commits • 1 Features
Sep 1, 2025September 2025 TDengine monthly summary focused on delivering new analytics capability, stabilizing streaming workloads, and improving documentation to reduce misuse. Key outcomes include delivering TSMA support, hardening the stream engine for production reliability, fixing nanosecond precision issues, and clarifying documentation to align expectations with capabilities.
September 2025
August 2025
12 Commits • 3 Features
Aug 1, 2025Month: 2025-08 — TDengine development delivered measurable business value by enhancing stream processing robustness, improving virtual table reliability, and elevating code quality across the repository. The work reduces ingestion latency, improves query correctness, and provides clearer diagnostics for operators, enabling faster issue resolution and more reliable real-time analytics.
August 2025
12 Commits • 3 Features
Aug 1, 2025Month: 2025-08 — TDengine development delivered measurable business value by enhancing stream processing robustness, improving virtual table reliability, and elevating code quality across the repository. The work reduces ingestion latency, improves query correctness, and provides clearer diagnostics for operators, enabling faster issue resolution and more reliable real-time analytics.
July 2025
95 Commits • 32 Features
Jul 1, 2025July 2025 performance summary for taosdata/TDengine focusing on TS-6100 improvements, time-range correctness, external window handling, memory management, and streaming performance. The team delivered end-to-end time range handling across scans and windows, enhanced external window support with plan-level optimizations, stabilized memory/vgroup propagation in subplans, refactored stream processing for better maintainability and performance, and extended query capabilities with IGNORE_NODATA_TRIGGER. These changes improved time-based analytics accuracy, streaming reliability, and overall query/planning efficiency, enabling customers to build more robust time-series workloads while reducing runtime errors and maintenance costs.
95 Commits • 32 Features
Jul 1, 2025July 2025 performance summary for taosdata/TDengine focusing on TS-6100 improvements, time-range correctness, external window handling, memory management, and streaming performance. The team delivered end-to-end time range handling across scans and windows, enhanced external window support with plan-level optimizations, stabilized memory/vgroup propagation in subplans, refactored stream processing for better maintainability and performance, and extended query capabilities with IGNORE_NODATA_TRIGGER. These changes improved time-based analytics accuracy, streaming reliability, and overall query/planning efficiency, enabling customers to build more robust time-series workloads while reducing runtime errors and maintenance costs.
July 2025
June 2025
61 Commits • 31 Features
Jun 1, 2025June 2025 TDengine monthly highlights focusing on TS-6100 work around CREATE STREAM SQL parsing, plan generation, and stability improvements. Delivered extensive parsing and generation enhancements, stronger data integrity checks, and broader streaming capabilities. Implemented trigger window checks, tbname handling, primary key validation, and numerous fixes and refactors to improve correctness, performance, and maintainability. Expanded TSMA support, virtual table and external window handling, and serialization/deserialization for stream queries. Added unit tests and improved error messaging to reduce debugging time. Result: more reliable stream creation, broader syntax coverage, and faster troubleshooting for real-time analytics workloads.
June 2025
61 Commits • 31 Features
Jun 1, 2025June 2025 TDengine monthly highlights focusing on TS-6100 work around CREATE STREAM SQL parsing, plan generation, and stability improvements. Delivered extensive parsing and generation enhancements, stronger data integrity checks, and broader streaming capabilities. Implemented trigger window checks, tbname handling, primary key validation, and numerous fixes and refactors to improve correctness, performance, and maintainability. Expanded TSMA support, virtual table and external window handling, and serialization/deserialization for stream queries. Added unit tests and improved error messaging to reduce debugging time. Result: more reliable stream creation, broader syntax coverage, and faster troubleshooting for real-time analytics workloads.
May 2025
69 Commits • 10 Features
May 1, 2025In May 2025, the TDengine project advanced the TS-6100 platform’s Create Stream SQL workflow, delivering a robust end-to-end solution from SCMCreateStreamReq processing to rich SQL generation and runtime features, while enhancing reliability and developer productivity. The month focused on delivering business-value features, stabilizing virtual tables, and improving cross-platform build resilience to support customers adopting ver-6 Stream APIs.
69 Commits • 10 Features
May 1, 2025In May 2025, the TDengine project advanced the TS-6100 platform’s Create Stream SQL workflow, delivering a robust end-to-end solution from SCMCreateStreamReq processing to rich SQL generation and runtime features, while enhancing reliability and developer productivity. The month focused on delivering business-value features, stabilizing virtual tables, and improving cross-platform build resilience to support customers adopting ver-6 Stream APIs.
May 2025
April 2025
16 Commits • 2 Features
Apr 1, 2025April 2025 monthly summary for taosdata/TDengine: Delivered stability and foundational capabilities across virtual tables and streaming features, focusing on reliability, memory safety, and future-ready streaming. Key work included: stability and correctness fixes for Virtual Tables (origin metadata retrieval, vtable memory management, and safe drop semantics) with tests; extensive Stream Creation and Processing Enhancements (build create request, SCMCreateStreamReq processing, serialization/deserialization, planning, and trigger/window configuration) that lay groundwork for advanced streaming and improved query planning; Virtual Tables Documentation Update to clarify creation and permission rules; and a MetaQuery memory management bug fix to remove unnecessary free and improve stability. Across these efforts, added targeted tests, addressed cross-platform compile issues, and aligned with TS-6100/TD-34631/TD-6094 storylines, delivering improvements in stability, test coverage, and platform readiness.
April 2025
16 Commits • 2 Features
Apr 1, 2025April 2025 monthly summary for taosdata/TDengine: Delivered stability and foundational capabilities across virtual tables and streaming features, focusing on reliability, memory safety, and future-ready streaming. Key work included: stability and correctness fixes for Virtual Tables (origin metadata retrieval, vtable memory management, and safe drop semantics) with tests; extensive Stream Creation and Processing Enhancements (build create request, SCMCreateStreamReq processing, serialization/deserialization, planning, and trigger/window configuration) that lay groundwork for advanced streaming and improved query planning; Virtual Tables Documentation Update to clarify creation and permission rules; and a MetaQuery memory management bug fix to remove unnecessary free and improve stability. Across these efforts, added targeted tests, addressed cross-platform compile issues, and aligned with TS-6100/TD-34631/TD-6094 storylines, delivering improvements in stability, test coverage, and platform readiness.
March 2025
16 Commits • 3 Features
Mar 1, 2025March 2025 TDengine monthly summary focused on Virtual Tables work in taosdata/TDengine. Core functionality and safety for Virtual Tables were delivered along with cross-database querying support, enhanced reliability, and expanded testing readiness. Significant stability improvements were achieved for child tables after altering super virtual tables, together with broader testing and macOS validation. Documentation updates were completed to improve comprehension and cross-database usage notes.
16 Commits • 3 Features
Mar 1, 2025March 2025 TDengine monthly summary focused on Virtual Tables work in taosdata/TDengine. Core functionality and safety for Virtual Tables were delivered along with cross-database querying support, enhanced reliability, and expanded testing readiness. Significant stability improvements were achieved for child tables after altering super virtual tables, together with broader testing and macOS validation. Documentation updates were completed to improve comprehension and cross-database usage notes.
March 2025
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Quality Metrics
Correctness86.8%
Maintainability83.0%
Architecture81.4%
Performance75.8%
AI Usage21.8%
Skills & Technologies
Programming Languages
CC++CMakeINIMarkdownPythonSQLShellYAMLyacc
Technical Skills
API DesignAPI DevelopmentAbstract Syntax Tree (AST)Backend DevelopmentBug FixBug FixingBug fixingBuild SystemCC ProgrammingC programmingC++C++ DevelopmentC++ programmingC/C++
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline