May 2026 (2026-05): Focused on enhancing the TiDB planner's statistics usage collection to improve performance and clarity. Delivered a refactor that removes redundant visited table state in the Stats usage collector and introduces visitedLogicalTblIDs, enabling clearer tracking and faster execution. The work aligns with ongoing performance optimization and more maintainable code in the planner/stats module. The change closes related issue pingcap/tidb#67912 as part of PR #68166. No major bugs fixed this month; the primary value comes from a more efficient and reliable stats collection path that supports larger workloads and more accurate plan decisions.

In April 2026, delivered robustness and stability improvements for statistics loading in pingcap/tidb. Focused on preserving the captured state and environment consistency after plan replay, and preventing errors by excluding internal pseudo columns from the async load queue. These changes reduced variability in statistics loading and improved data processing performance, contributing to more reliable query optimization and a smoother user experience.

March 2026 (2026-03) monthly summary for pingcap/tidb: Overhauled the Statistics Subsystem by removing the extended statistics feature and hardening statistics handling to prevent duplicate entries in stats_histograms when analyzing all columns after adding new columns. This work improves data integrity, reduces maintenance overhead, and enhances optimizer reliability and performance for large schemas.

February 2026 (2026-02) monthly summary for pingcap/tidb: Delivered a focused observability enhancement by implementing Slow Log Statistics Labeling. This feature adds explicit labels to slow log stats, improving readability, filtering, and correlation with queries, enabling faster root-cause analysis in production. Key commit 8bee66cb5678a723ed89dd5b97907d7ebae388f1 (sessionctx: improve slow log stats format with explicit labels (#66305); closes pingcap/tidb#63206). Impact: reduced debugging time, clearer metrics for monitoring pipelines, and more actionable insights for SREs and developers. Technologies: Go, logging/observability instrumentation, code instrumentation, and review processes.