Month: 2026-04 — Monthly summary for StarRocks/starrocks dev work focusing on correctness and stability of pushdown optimization. Key achievement: fixed a in-place mutation bug in PushDownAggregateRewriter that caused incorrect aggregation results when multiple aggregations referenced the same column. The fix ensures shared CaseWhenOperator and CallOperator instances are not mutated in place, preserving isolation across aggregations and preventing cross-query corruption. Impact: eliminates a class of incorrect results in complex aggregate queries, improving reliability of query execution paths that rely on pushdown aggregation. The change reduces data correctness risk and enhances stability for analytics workloads. Process and collaboration: committed the fix to StarRocks/starrocks (commit f90720c96e2e2cc6cc72416a8ad189984e33976b) and progressed through code review and validation to prevent regressions. Technologies/skills demonstrated: C++ code corrections in the query planner/execution path, debugging shared-object mutation, patch verification, and collaborative code review.

March 2026 monthly summary for StarRocks/starrocks development focused on improving query optimization and correctness through materialization hints in CTEs. This period delivered a targeted feature with validation for recursive CTEs and SQL generation updates to honor materialization status, enabling more efficient query planning and potential runtime performance gains.

February 2026 monthly performance summary focusing on performance optimizations in profiling workflows and log management across cross-repo work. Focus remained on business value, stability, and scalable telemetry. Deliverables contributed to reduced profiling overhead and improved log/resource efficiency, enabling better resource utilization and lower storage costs.

Month: 2025-10. Focused on delivering a key performance engineering feature in StarRocks/starrocks: a Query Profile Analysis UI Enhancements that enables analysts to inspect query profiles, view and format SQL, and configure the display length. This work strengthens debugging workflows and accelerates performance investigations.