March 2026 monthly summary for facebookincubator/velox. Key feature delivered: real-time streaming support for kFinal and kSingle groupby in CudfHashAggregation, enabling processing of incoming data batches in real time via addInput and reducing latency for streaming workloads. This work aligns Velox's CudfHashAggregation with the existing streaming path and supports real-time analytics use cases.

February 2026: Delivered CUDA-driven performance improvements in cudf execution for Velox, focusing on stream management, subfield filter AST, and filter expression caching. Fixed default CUDA stream usages to reduce synchronization overhead and built a combined AST for subfield filters to accelerate predicate evaluation. Cached filter expressions for reuse across queries to amortize work. These changes improve GPU utilization and data processing throughput for cudf workloads, aligning with performance-for-scale goals.

January 2026 Monthly Summary — Velox (facebookincubator/velox) focused on robustness improvements for cuDF integration and edge-case handling in the query engine. What was delivered: - Implemented a targeted robustness fix for empty-table handling in cuDF query execution, ensuring correctness for queries with count(*) in scenarios where input tables are empty but non-zero in size. The fix touches FilterProject and HashAggregation paths and stabilizes execution when cuDF is disabled on certain plan nodes that would produce empty results. Key outcomes: - Improved correctness and reliability of query results for edge cases, reducing production failures when counting across empty datasets. - Strengthened Presto-CuDF integration within Velox by hardening empty-input handling and plan-node behavior. - Clear traceability and review: PR 15539 with commit 1211e66ef9f9a072c5e20a18585500c65904d615; review by kagamiori; Differential Revision: D91055186; pulled by juwentus1234. Business impact: - Higher reliability for analytical workloads that frequently encounter empty partitions or tables, leading to more consistent dashboards and fewer investigative toil. - Reduced risk of incorrect query results in production when using count(*) aggregations with empty inputs. Technologies/skills demonstrated: - cuDF integration and Velox query engine internals (FilterProject, HashAggregation) - Edge-case testing and robust defensive programming - Cross-team collaboration, code review discipline, and end-to-end PR workflow

Month 2025-12: Delivered robustness enhancements for CuDF integration within Velox, focusing on safe substitution of the FilterProject operator and correctness of expression evaluation. The changes reduce risk of incorrect results and improve reliability in cuDF-accelerated queries, with explicit signal on memory pool usage and driver adapter behavior.

November 2025 performance summary focusing on advancing GPU-accelerated paths and benchmarking in Velox. Delivered Coalesce support in the cuDF expression evaluator for oap-project/velox, enabling Coalesce as a precompute operation and enhancing CudfFilterProject with more complex filtering and projection; tests validate behavior across multiple scenarios. Introduced a GPU-accelerated TPC-H benchmark using cuDF in facebookincubator/velox, improving configuration management and extendability within the benchmarking framework. No major bugs reported this month. Impact: faster data processing via GPU paths, broader GPU-enabled workloads, and a more flexible benchmarking setup that helps quantify performance gains for customers. Technologies/skills demonstrated: CUDA/cuDF integration, GPU-accelerated query execution, Velox architecture, test automation, and benchmarking configuration.

October 2025 monthly summary for oap-project/velox: Delivered the CudfExpression interface enabling nesting of cuDF AST expressions and standalone cuDF functions, improving expression evaluation flexibility. Enhanced expression evaluation, function registration, and zero-copy access by returning ColumnOrView for nested expressions. Prepared the groundwork for JIT-based evaluation by supporting optional ASTExpression registration with prioritization. Refactored SubfieldFilterToAST and ASTExpression into separate source files to improve maintainability. No major bugs fixed this month; focus was on delivering core capabilities and setting up a scalable evaluation path. Business impact: enables more complex, efficient expressions and smoother cuDF integration, driving performance, scalability, and richer analytics capabilities across Velox.

September 2025 monthly summary for IBM/velox, highlighting delivery of cuDF-based data processing enhancements, Hive integration with CPU fallback, and stabilization work to CI/build and average aggregation behavior.

August 2025 (2025-08) performance summary for IBM/velox focusing on robustness and expression capabilities. Delivered a critical bug fix for empty-input handling in CudfHashAggregation and implemented VARCHAR literals handling in cudf expression trees, with accompanying tests to validate string literal expansion and usage in comparisons/projections. These changes enhance stability for empty datasets and broaden SQL compatibility (e.g., TPCH Q21 support in Presto).

June 2025 (IBM/velox) monthly summary focusing on delivering GPU-accelerated data processing and governance improvements that unlock faster analytics and streamlined reviews. Implemented cuDF-enabled operators and Parquet IO to enable end-to-end GPU-accelerated workloads, and updated Code Owners for the cudf adapter to clarify ownership and speed up reviews. No major bugs recorded in this period; primary value came from performance gains and maintainability improvements. Impact: higher query throughput, reduced CPU load, and faster review cycles due to clearer ownership. Technologies demonstrated: CUDA/cuDF, Parquet IO, Velox architecture, and Git-based governance.

May 2025 Monthly Summary for IBM/velox focusing on business value and technical achievements. Key feature delivered: CuDF-based HashAggregation Operator for Velox with enhanced NVTX profiling. This introduces GPU-accelerated aggregation support for Velox, enabling sum, min, max, count, and avg, and provides richer profiling labels for observability. Overall impact: Established GPU-accelerated aggregation capability in Velox, unlocking faster analytics workloads and improved performance debugging through enhanced NVTX labels. Lays a foundation for broader GPU-enabled analytics in the Velox stack and potential performance gains in customer use cases that rely on large-scale aggregations. Repository: IBM/velox Technologies/skills demonstrated: CUDA/cuDF integration, GPU-accelerated operator design, NVTX profiling, Velox operator development, code contribution and review practices. Commits noted: feat(cudf): Add cudf based HashAggregation operator (#13368) - f5dbfc5d0a9080cbc91787eefce4d6bab0790014

April 2025 monthly summary for IBM/velox focusing on key accomplishments and business impact. Implemented a CuDF-based GPU-accelerated OrderBy operator to replace the existing Velox sorting operators, enabling GPU-accelerated sorting for large datasets. This involved building cuDF data handling, driving interoperation between Velox and cuDF, and creating a driver adapter for seamless integration across components.