October 2025 (Month: 2025-10) focused on correctness and reliability of query results in the Nereids optimizer for Apache Doris. Delivered a critical fix to AVG type casting for SUM(DISTINCT)/COUNT(DISTINCT) aggregations, addressing a data type mismatch that could affect AVG results. The change ensures the derived division result is cast to the original AVG data type, improving accuracy of analytics workloads and preventing incorrect aggregations in production. The fix was implemented in the Nereids rule AvgDistinctToSumDivCount and merged as part of PR #56887, with commit 16c62be4598bc2687490f2a5e5bac067c21c12f1. This work strengthens query correctness in Doris 2025.10, particularly for distinct aggregate patterns. Repositories involved: apache/doris.

In September 2025, delivered targeted Nereids enhancements and stability improvements in apache/doris. Key deliverables include a refactor of the aggregation strategy with improved distinct handling and optimized plan generation; expanded rewrite capability of EliminateGroupByKeyByUniform inside CTEs; and a stats-aware default for multi_distinct aggregation to maintain performance when statistics are unavailable. Implemented robust fixes to multi_distinct aggregation correctness by normalizing multi_distinct functions and removing an obsolete mustUseMultiDistinct flag. Stabilized regression tests for aggregation strategy by configuring test backends and disabling certain propagation flags to ensure reliable results. These workstreams collectively improve query performance, correctness, and test reliability, delivering tangible value for production workloads with large-scale analytics.

July 2025 performance highlights: delivered codebase cleanup to reduce confusion in nereids rules analysis; improved query plan predictability by honoring the leading join order hints under the dphyper optimizer; introduced data skew handling transformation rules (SaltJoin, countDistinctSkewRewrite, and window skew rewrite) to boost SQL performance and resource distribution; resolved optimizer test regressions to stabilize CI and metrics.

June 2025 performance-focused monthly summary for apache/doris. Key outcomes include feature delivery around Nereids optimizer improvements and a critical bug fix that together enhance query accuracy and performance for analytical workloads. Key features delivered: - Nereids optimizer enhancements enabling predicate pull-up from aggregates (MIN, MAX, AVG) and improved predicate propagation from project operations, enabling more effective predicate pushdown and potential performance gains. Major bugs fixed: - Bug fix: Erroneous error when using sum0 with multiple distinct arguments; updated CheckMultiDistinct rule to correctly identify aggregate support for multi-distinct operations and prevent query errors. Overall impact and accomplishments: - Improved query correctness and robustness for complex aggregate queries involving multi-distinct and aggregated predicates. - Potential performance improvements due to increased predicate pushdown opportunities, reducing data scanned and improving latency in analytical workloads. - Demonstrated progress in core optimizer capabilities and multi-distinct handling, aligning with performance and reliability goals. Technologies/skills demonstrated: - Nereids optimizer, predicate pushdown, multi-distinct handling, and predicate propagation techniques. - Changes impacting core query planning and execution paths (CheckMultiDistinct rule and aggregate/predicate pipelines). - Strong emphasis on business value through reduced errors and improved analytics performance.

May 2025: Delivered substantive Nereids optimizer improvements with correctness enhancements, increased maintainability via centralizing window property derivation, and improved overall stability through targeted bug fixes in percentile handling, planner fallback, NULL literals in views, and regression test isolation. The work strengthens query correctness, reliability of plan fallback, and test stability, delivering direct business value through more accurate and robust query execution.

April 2025: Key reliability and performance improvements in Doris (apache/doris) focused on streaming data ingestion and query normalization (Nereids). Implemented explicit casting for generated columns in stream loads to ensure type correctness for string slots, with new tests that prevent load-time casting errors. Stabilized query optimization by ensuring constant group-by keys are consistently eliminated in NormalizeAggregate, reducing inconsistent executions and analysis errors. These changes improve data correctness, streaming reliability, and analytic query stability, delivering measurable business value in data integrity and user experience. Demonstrated proficiency in cast handling, test coverage, and Nereids-based optimization.

March 2025 monthly summary for apache/doris: Focused on reliability, stability, and correctness in the SQL/optimizer paths. Two high-impact bug fixes completed, improving test determinism and query normalization, contributing to more predictable releases and faster feedback loops in CI.

February 2025 (apache/doris) delivered targeted performance improvements, correctness fixes, and enhanced auditability. Key efforts focused on SQL query optimization and test hygiene to ensure stable, scalable BI workloads.

January 2025 performance summary for apache/doris: Delivered targeted enhancements to the Nereids optimizer and partition pruning, improving performance and reliability for complex queries. Key features delivered include monotonicity-aware date/time functions enabling stronger partition pruning, and a SplitMultiDistinct optimization to boost performance of queries with multiple DISTINCT operations. Major fixes addressed partition pruning correctness and overall optimizer robustness across set operations, repeats, distribution, and functional dependency propagation. These changes collectively enhance business value by faster query execution, more reliable planning, and reduced maintenance risk.

Month: 2024-12. This month focused on strengthening query performance, correctness, and developer-facing documentation across the Doris ecosystem. Key optimizer rewrites, pruning enhancements, and window-function handling were delivered, alongside expanded test coverage to improve robustness and reliability for large-scale workloads.

November 2024 — Apache Doris (Nereids) enhancements focused on reliability and performance. Key features delivered: - Unified Monotonic Function Handling in Nereids Partition Pruning: Replaced per-function visit methods in OneRangePartitionEvaluator with a unified Monotonic interface, simplifying pruning logic and improving scalability and predictability of pruning outcomes. Major bugs fixed: - Robust View Creation and Alteration with Optimizer-Specific Parsing: Fixed parsing failures for views when using the new optimizer by moving parsing checks from the central createView path into the optimizer classes, ensuring correct parsing with the active optimizer. Overall impact and accomplishments: - Strengthened reliability of query planning and view operations, reducing runtime errors and stabilizing performance under the new optimizer. Delivered maintainable refactors with clear ownership and better long-term maintenance. Technologies/skills demonstrated: - Java refactoring and optimizer integration, partition pruning architecture, code quality and maintainability, Git-based traceability.