February 2026 - Apache Doris: Implemented Query Cache Enhancements and Correctness (sorting/one-phase aggregation, digest adjustments, safeguards against dynamic session variables and UDFs) with tests; Fixed Nested Column Pruning crash; Optimized Set Operation Plan Translation by enabling colocate for local shuffle; Resolved MacOS backend compilation issues to improve cross-platform build reliability. These efforts deliver improved query performance and correctness, greater planning stability, and smoother developer experience on MacOS.

January 2026 (2026-01) summary focused on delivering key features with improved correctness and performance, strengthening cross-platform reliability, and increasing data consistency and regression test stability in Doris. The month’ s work emphasizes business value through faster, more reliable distributed query processing, safer build on macOS, robust SQL caching, and more stable end-to-end validation during stream loads and DDL changes.

December 2025: Delivered significant enhancements to data processing reliability, query coordination, and UI fidelity, while strengthening stability in distributed execution. Key features and improvements include broadening command execution through universal NereidsCoordinator support across all command paths (e.g., UpdateCommand), introducing a Partition Pruning Cache Refresh Interval to optimize pruning efficiency, and expanding pruning capabilities for nested columns via lateral view and explode functions. A UI enhancement was completed to display complete user profile information by updating the profile data structure. Parallel bug fixes and stability improvements include backend fixes for forward insert statements with local shuffle union, robust handling of map/nested types for pruning and dereference expressions, and fixes to query cache null string scenarios. Additional testing infrastructure improvements to stabilize SimpleScheduler unit tests were implemented. These changes collectively improve data correctness, reduce planning/execution latency, and enhance end-user experience, while demonstrating strong proficiency in caching, pruning strategies, distributed coordination, UI data modeling, and testing discipline.

Month: 2025-11 Key features delivered: - Explain Plan Visualization Enhancement: add visual markers and improved tree representation to clarify SQL execution plans for faster debugging. - Pruning Nested Columns: enable pruning of nested columns to reduce scan and shuffle bytes; included tests to ensure correctness. - Dereference Expression Support for Nested Data: support dereference expressions for map/struct/variant enabling more complex queries. - Random Local Shuffle in Union Operations: add support to optimize data distribution and reduce network overhead within a backend. Major bugs fixed: - TVF Union All Stability Fix: fixed exception in union all with TVFs and ensured proper job generation for fragments. - Job Processing and Timeout Robustness: fixed unstable insert exception in job status reporting and improved timeout handling by canceling queries reliably. Overall impact and accomplishments: - Improved reliability and performance across query execution, caching, and pipeline orchestration. Plan interpretability improved for faster debugging and feature delivery. Nested data operations are more expressive and efficient, with reduced data transfer from pruning. Resource usage trimmed through earlier RPC termination and more balanced data distribution. Technologies/skills demonstrated: - Nereids, explain plan processing, planner optimizations, SQL cache correctness, coordinator/broadcast mechanisms, and nested data support (map/struct/variant).

October 2025: Delivered SQL Cache reliability improvements in Jibing-Li/incubator-doris, focusing on test validation and explain plan stability. Resolved regression in SQL cache hit tests, fixed NullPointerException during explain plan processing with SQL cache (including explain level variations), and added tests for explain plans with SQL cache. Demonstrated skills in SQL cache integration, explain plan handling, test automation, and robust error handling. Business value: more reliable query performance, reduced regression risk, and easier maintenance.

September 2025: Delivered substantial improvements to the Nereids-based processing path and SQL caching in the incubator-doris repository, with a focus on reliability, performance, and test coverage. Key outcomes include enabling SQL caching by default with robust cache invalidation and session-variable handling (including Hive external table scenarios); fixes to distributed processing for correct bucket assignments; targeted optimizations for large string casts and point-query schema retrieval; and a critical URL validation bug fix for export tasks that prevents NPEs and improves error messaging.

In 2025-08, delivered key features and fixes across Doris repos, focusing on correctness, performance, and developer experience. Major improvements include Nereids SQL parser correctness, optimized OLAP insert parallelism for auto-partitioned tables, and string range simplifications in optimizer, plus documentation clarity for map/struct_element case sensitivity. These work items enhance query accuracy, ingestion throughput, and planning efficiency, contributing to business value through more robust, scalable, and faster analytics capabilities.

July 2025: Delivered debugging tooling, reliability, and performance improvements across Doris FE and Nereids. Key outcomes include FE Arthas integration with licensing update and profiling documentation; cross-OS CPU core reporting fixes; Nereids planner fragmentation optimization; and robust error handling and pruning fixes that improve stability and query performance across workloads.

June 2025 performance summary for Jibing-Li/incubator-doris. Focused on correctness, reliability, and performance improvements in the Nereids parser and engine to deliver tangible business value in data processing and error diagnosis. Delivered targeted fixes to parsing, plus substantial engine optimizations that speed up small SQL queries and provide clearer error locations.

May 2025 monthly summary for Jibing-Li/incubator-doris focusing on correctness, reliability, and maintainability of the distributed query engine. Delivered two critical bug fixes with unit tests, improving cross-backend data retrieval and subquery processing, which enhance data accuracy, reduce runtime errors, and strengthen information_schema behavior. The changes reflect strong debugging discipline, effective use of existing test infrastructure, and clear commit history to support long-term stability and developer productivity.

April 2025 focused on correctness in datetime handling within the Nereids query engine. Delivered a bug fix for the Datetime Fold Constant Rule Precision to ensure SQL queries return the correct datetime precision. The fix was implemented in the Jibing-Li/incubator-doris repository and linked to PR #50142 (commit c679c831e5a32b83a8c17c562790e2924c24d039). Impact: improved query accuracy and reliability, reducing potential user-visible inconsistencies in datetime results. Skills demonstrated: debugging, precise problem isolation, cross-functional code changes in the Nereids module, and adherence to code-review-driven delivery.

March 2025 monthly progress for Jibing-Li/incubator-doris focused on measurable business value: enabling deeper memory analysis, accelerating query planning for large InPredicate workloads, and hardening stability and correctness across the Nereids stack. The work delivered supports faster diagnosis, lower latency on complex queries, and more reliable SQL execution with regression coverage.

February 2025: Delivered critical Nereids stability improvements and enhanced partition pruning for the incubator-doris project, with targeted bug fixes and improved error messaging. Implemented binary-search-based pruning, refined range evaluation, added regression tests, and strengthened the overall performance and reliability of the query planner.

January 2025 highlights for Jibing-Li/incubator-doris: focused on elevating query planning performance, enhancing cache reliability, and strengthening cloud-mode deployments. Delivered targeted optimizer and testing improvements, fixed critical frontend planning issues, and expanded cloud readiness to support scalable production workloads.

December 2024 monthly summary for Jibing-Li/incubator-doris focused on reliability, performance, and scalability improvements in the Nereids query engine. Key work included stabilizing query interruption behavior, introducing orthogonal bitmap aggregate support, accelerating materialized view synchronization, optimizing insert workflows, and enhancing partition pruning. These changes deliver tangible business value by reducing query interruptions, speeding data ingestion and MV maintenance, and enabling faster analytics over larger datasets.

November 2024 monthly summary for Jibing-Li/incubator-doris focused on delivering meaningful business value through performance, reliability, and correctness improvements across the Nereids distributed planner, build environment, and SQL/time processing. Key outcomes include: (1) substantial performance improvements in the Nereids distributed planner with profiling configurability, enabling deeper visibility and faster planning for distributed workloads; (2) improved cross-OS build stability, notably macOS, via targeted type adjustments and minor fixes to ensure reliable compiles; (3) corrected stability and correctness issues in distributed joins (STORAGE_BUCKETED) and in SQL caching with from_unixtime formatting, each accompanied by regression tests to prevent recurrence; (4) corrected date arithmetic calculations in SimplifyArithmeticComparisonRule to ensure accurate months/years add/sub operations and added tests. These changes collectively reduce regression risk, accelerate analytics, and improve user-facing reliability for production workloads.