October 2025: Delivered robust regression testing improvements, enhanced Nereids capabilities, and targeted performance and observability refinements. Changes reduce test flakiness, improve test execution control, enhance query planning fidelity, and lower runtime overhead, translating to faster cycles and more reliable production deployments.

September 2025 performance month focused on delivering end-to-end improvements to the Nereids-based path in Apache Doris, with emphasis on Top-N lazy materialization, runtime profiling, statistics derivation, and optimizer stability. Key outcomes include correctness and stability fixes, configurability enhancements, richer runtime diagnostics, and targeted test reliability improvements, all aimed at improving query latency for common workloads and the accuracy of the optimizer’s decisions.

Monthly performance summary for 2025-08 (apache/doris). The focus this month was stabilizing and enhancing the Nereids optimizer, improving cost estimation, and delivering performance-oriented features while maintaining high-quality test coverage. Key outcomes delivered across multiple commits include: - Nereids Optimizer: Correctness and Stability — fixed stable join reordering when row counts are unavailable, ensured proper tuple ID propagation, improved TopN handling through UNION, and robust nullability propagation for compound predicates. These fixes reduce plan instability and regression risk in production workloads. - Nereids Statistics and Cost Estimation Improvements — enhanced cost accuracy by deriving hot values, handling NaN in avgSizeByte with a default of 1, preventing negative row counts, and converting date literals to string literals for consistent processing. - TopN and Join Optimization Enhancements — introduced a lazy materialization threshold to avoid useless lazy materialization and enabled automatic salt-join selection for skew joins, improving latency on skewed data. - Optimizer Constant Folding Enhancement for Match Functions — extended FoldConstantRuleOnFE with a dedicated pattern for Match/MATH series functions to improve query processing efficiency. - Test Suite Maintenance — removed unused regression tests and directories to keep the regression suite clean and maintainable. Business value: more reliable and faster query plans, improved cost estimates reducing resource usage, and lower maintenance cost through a cleaner, leaner test suite.

July 2025 highlights for apache/doris (Nereids): Delivered key features that strengthen expression safety, execution planning, and analytics capabilities; fixed critical runtime filtering issues for CTEs; and advanced statistics/optimization to improve plan quality and performance. This period focused on business-value outcomes: more robust query correctness, faster analytics, and more scalable plans under complex workloads. Key features and improvements: - Expression depth/limit enforcement in Nereids with regression test: reintroduces checkLimit() to Expression.java and adds expression_depth_check.groovy regression coverage (commit d58e0688b887783fb8ae483fc082cf3a240c898c). - Enable top-n lazy materialization in execution plans: introduces PhysicalLazyMaterialize nodes and adjusts plan/scan usage to support lazy evaluation (commit 6c3812d0e76a4692f566e8feda00a538bbcba9ad). - Analytical window functions support for DISTINCT in COUNT and SUM: adds COUNT(DISTINCT A) and SUM(DISTINCT A) in window contexts via parser and rewrite rule to multi-distinct aggregates (commit f38e98b3e525719a07b9da70c08b87395f4937ba). - Optimizer and statistics derivation improvements: introduces StatsDerive, moves statistics derivation earlier, improves hot-value statistics handling, initializes join order optimization, and aligns tests; multiple commits across this area (e.g., 78ff9e5648966e1f102439c0fd3e20516a61e48e, 250584c0d5601325bb683800305397cfcb84e457, 7fbc798be1133109452bece67d3045e6541758f8, 4c6f12fb2bafb9f5135526a142d771a69de831ed, 0e8d77abf1a9304d1a811ef59396f8d527d562e2, 63595dbdf1b4989067e70d1e917a3b8fd773a2d8, b248da917ab38fd8dd9c8663d12b972ab7df117b, dc10c65a14835b6f93b6bf4bf8c2c0c2e549daa0, e13f1f1c9aa894156807a8afc43bf730497e36d4). - Fix: runtime filter target mapping to CTE consumers: ensures runtime filters apply to CTE consumers and adds regression tests (commit d6a3bdd60d766a8a53ef40f10350c498f5d2b781). Impact and value: - Performance: lazy top-N materialization reduces memory pressure and improves query latency for large result sets; early stats derivation sharpens plan choices. - Correctness: safer expression evaluation limits prevent pathological plans; window DISTINCT handling expands analytics capabilities without sacrificing correctness. - Reliability: regression tests across features and runtime filters reduce risk of regressions in complex workloads with CTEs. Technologies and skills demonstrated: - Nereids optimizer enhancements, plan shaping, and rewrite rules - Regression testing with Groovy-based suites - Advanced statistics derivation, hot-value stats handling, and join order initialization - CTE-aware runtime filter mapping and validation - Codebase growth in expressions, plan nodes, and statistics derivations

Month 2025-06 - Apache Doris (Nereids focus): Delivered a set of optimizer/planner improvements and bug fixes that enhance accuracy, performance, and maintainability. Key items include fixes to statistics reporting, LOAD literal handling, cost model consolidation, and runtime filters for set-based operations (EXCEPT/INTERSECT). These changes reduce incorrect statistics, improve correctness of query plans, and streamline the cost computation path, enabling better query performance and easier future maintenance.

May 2025 monthly summary for apache/doris focusing on reliability, stability, and optimizer improvements. Key work delivered: - Audit log streaming reliability under HTTPS: fixed stream loader behavior so the audit log stream plugin does not redirect HTTP to HTTPS for stream load operations when HTTPS is enabled. This prevents audit plugin process disruptions and ensures stream load succeeds regardless of HTTPS configuration, reducing production failures in data ingestion pipelines. - Regression test stability improvements: removed unstable test cases that caused flaky results (e.g., testFoldConst('select unix_timestamp()')) and adjusted test statistics to stabilize execution. Result: more deterministic CI outcomes and faster feedback loops. - Optimizer improvements for push-down aggregates through joins and cost modeling: implemented fixes and enhancements to PushDownAggThroughJoin rules, corrected type conversions, validated join children, and added a cost penalty for Nested Loop Join in aggregation scenarios to improve plan correctness and performance. Overall, the month delivered tangible business value through more reliable data ingestion, more stable testing, and improved query performance and plan quality.

April 2025: Delivered targeted performance and stability improvements for apache/doris. Implemented Constant Join Condition Elimination Optimization to simplify plans and reduce comparisons in inner/semi-joins. Reverted an unstable hash join optimization to restore correctness. Added robust exception handling around statistics calculation and expression estimation and fixed normalization issues to prevent query failures. Hardened runtime filter pruning when statistics are missing to preserve query performance. These changes enhance reliability, observability, and throughput for common workloads.

March 2025 (2025-03) performance review: Dedicated the month to strengthening the Nereids optimizer and overall query planning stack in apache/doris, with a focus on delivering measurable business value through more efficient plan generation, robust statistics, and stable query results. Key wins include propagating operative slots via a new OperativeColumnDerive rule, eliminating redundant constant-equality hash join conditions, and tightening statistics handling and runtime filter behavior. The work reduced unnecessary stats queries, improved estimate reliability for common aggregates, and stabilized UNION/top-N outcomes, contributing to faster, more predictable query plans in production.

February 2025: Focused on delivering performance improvements in the Doris Nereids query optimizer and stabilizing regression tests, leading to faster queries and more reliable releases.

January 2025 performance snapshot: Strengthened the Nereids optimizer and analytics reliability, with notable improvements across both optimization and regression coverage. Delivered key features to the Nereids optimizer, improved runtime filter and TopN handling, and hardened statistics/analysis workflows to ensure robust analytics even when stats are disabled. This month also expanded regression coverage for TPC-DS scenarios to prevent missed join conditions in regression tests, reinforcing production confidence and data quality.

2024-12 monthly summary for apache/doris focused on stability, performance, and developer productivity. Key outcomes include targeted optimizer improvements, increased debugging observability, and test-suite maintenance that together reduce risk, improve plan quality, and accelerate delivery of business value. Key deliverables for the month: - Nereids optimizer enhancements: including alias handling optimization for common subexpression elimination, adding an is_merge flag for data sinks to speed up transfers, improved sort key handling for aggregates, and support for single-phase sort in DeferMaterializeTopN. - Debugging improvements: plan/memo logging on shape check failures to capture full plan details, with regression test framework updates to surface complete plan information. - Test maintenance: reorganization and renaming of regression tests related to shape-checking and runtime filters to improve maintainability and discoverability. Major bugs fixed: - Regression: runtime filter regression in invalid_stats test resolved by turning the runtime filter off for that case to guarantee accurate test execution. - ExplainAction: fixed multiContains reporting to avoid undefined strings in the explain output, ensuring clear expected vs actual messaging. Overall impact and accomplishments: - Improved query reliability and predictability, reducing flaky tests and increasing stability of critical workloads. - Faster data movement and improved query planning efficiency through Nereids enhancements, enabling better throughput and lower tail latency on complex workloads. - Enhanced observability and debugging speed through comprehensive plan/memo logs on failure paths, accelerating root-cause analysis. Technologies/skills demonstrated: - Nereids optimizer engineering (subexpression aliasing, is_merge tagging, sort key corrections, one-phase sort support). - Regression testing strategy, test framework improvements, and test suite maintenance. - Runtime filter handling and explain output correctness. - Observability improvements through plan/memo logging and detailed failure capture.

Monthly summary for 2024-11: Delivered targeted Nereids optimizer fixes and performance enhancements in apache/doris, strengthening query correctness, throughput, and stability. Implemented regression test coverage to guard against invalid statistics affecting join reorder, and reinforced end-to-end testability with Groovy-based suites. The work delivered business value by improving complex query performance and reliability for production workloads, reducing risk of incorrect results, and enabling more aggressive push-down optimizations.