
Rexan contributed to large-scale data infrastructure by developing and refining core features in the IBM/velox and apache/incubator-gluten repositories. Over nine months, Rexan enhanced Spark SQL interoperability, implemented robust timestamp and decimal casting logic, and improved memory management for stable data processing. Using C++, Scala, and Java, Rexan addressed edge cases in date and time functions, optimized array sorting with lambda comparators, and fixed memory leaks in write paths. The work included rigorous unit testing, code refactoring, and benchmarking, resulting in more reliable analytics pipelines and safer runtime behavior for big data workloads across Spark and Velox integrations.
March 2026 performance summary for facebookincubator/velox focused on interoperability enhancements for decimal-to-string casting. Delivered support for scientific notation when casting tiny decimal values (abs < 1e-6) to align with Spark behavior, implemented in the Velox casting logic, and accompanied by documentation and benchmarks updates. The changes were introduced via commit 4e4b841ed855834bf9d86d5e37ed37f611424dcf and PR 14910 (Differential Revision: D93450802).
March 2026 performance summary for facebookincubator/velox focused on interoperability enhancements for decimal-to-string casting. Delivered support for scientific notation when casting tiny decimal values (abs < 1e-6) to align with Spark behavior, implemented in the Velox casting logic, and accompanied by documentation and benchmarks updates. The changes were introduced via commit 4e4b841ed855834bf9d86d5e37ed37f611424dcf and PR 14910 (Differential Revision: D93450802).
February 2026: Focused on stabilizing large-scale plan processing in the Gluten framework. Implemented OOM mitigation for large Spark plans, enhanced error handling and plan-transition messages to improve debugging and resilience with big datasets, and delivered focused stability improvements in the gluten repo. These changes reduce memory-related crashes, improve reliability for customers processing large workloads, and enable smoother operations in production.
February 2026: Focused on stabilizing large-scale plan processing in the Gluten framework. Implemented OOM mitigation for large Spark plans, enhanced error handling and plan-transition messages to improve debugging and resilience with big datasets, and delivered focused stability improvements in the gluten repo. These changes reduce memory-related crashes, improve reliability for customers processing large workloads, and enable smoother operations in production.
Month: 2026-01 — Focused on improving Parquet write path robustness in apache/incubator-gluten by fixing large value handling and adding tests. The change prevents overflow when configuring block size, block rows, and page size, delivering greater reliability for large data workloads and reducing risk of misconfiguration during writes. The work aligns with business value by ensuring stable, scalable Parquet writes and improving overall data pipeline reliability.
Month: 2026-01 — Focused on improving Parquet write path robustness in apache/incubator-gluten by fixing large value handling and adding tests. The change prevents overflow when configuring block size, block rows, and page size, delivering greater reliability for large data workloads and reducing risk of misconfiguration during writes. The work aligns with business value by ensuring stable, scalable Parquet writes and improving overall data pipeline reliability.
November 2025: Consolidated memory management improvements for key data-path components in apache/incubator-gluten to mitigate OOM risks and improve throughput. Implemented direct I/O stream handling by removing buffering of sorted partitions in the RSS writer and disabled compression in the Celeborn shuffle manager to reduce peak memory usage. Delivered via a focused code change addressing memory pressure (#11059).
November 2025: Consolidated memory management improvements for key data-path components in apache/incubator-gluten to mitigate OOM risks and improve throughput. Implemented direct I/O stream handling by removing buffering of sorted partitions in the RSS writer and disabled compression in the Celeborn shuffle manager to reduce peak memory usage. Delivered via a focused code change addressing memory pressure (#11059).
September 2025 performance-focused monthly summary highlighting key features delivered, major bugs fixed, overall impact, and technologies demonstrated across IBM/velox and apache/incubator-gluten. The month centered on advancing Spark compatibility and reliability in large-scale data processing pipelines with Lambda-based sorting and robust HDFS handling.
September 2025 performance-focused monthly summary highlighting key features delivered, major bugs fixed, overall impact, and technologies demonstrated across IBM/velox and apache/incubator-gluten. The month centered on advancing Spark compatibility and reliability in large-scale data processing pipelines with Lambda-based sorting and robust HDFS handling.
August 2025: Focused on reliability and stability for the Velox integration in the Apache Gluten write path. No new user-facing features were shipped this month; primary work targeted memory safety and stability in the write task execution, with a bug fix that guards against memory leaks.
August 2025: Focused on reliability and stability for the Velox integration in the Apache Gluten write path. No new user-facing features were shipped this month; primary work targeted memory safety and stability in the write task execution, with a bug fix that guards against memory leaks.
April 2025 monthly summary for IBM/velox focused on delivering a Spark interoperability enhancement: a new Spark CAST(timestamp as integral) feature. The feature enables casting Spark timestamps to integral types (tinyint, smallint, integer, bigint) by converting timestamps to microseconds, dividing by 1,000,000 (microseconds per second), and rounding down to epoch seconds. This change improves cross-system interoperability and enables more compact numeric representations for time-based analytics. Implemented end-to-end across CastExpr-inl.h, CastHooks.h, PrestoCastHooks.cpp, SparkCastHooks.cpp, and SparkCastExprTest.cpp, with unit tests validating correctness. The commit fc3c6eb573e845ff4b6132db7ea81439a20e6545 documents the change ("feat: Add Spark CAST(timestamp as integral) (#11468)").
April 2025 monthly summary for IBM/velox focused on delivering a Spark interoperability enhancement: a new Spark CAST(timestamp as integral) feature. The feature enables casting Spark timestamps to integral types (tinyint, smallint, integer, bigint) by converting timestamps to microseconds, dividing by 1,000,000 (microseconds per second), and rounding down to epoch seconds. This change improves cross-system interoperability and enables more compact numeric representations for time-based analytics. Implemented end-to-end across CastExpr-inl.h, CastHooks.h, PrestoCastHooks.cpp, SparkCastHooks.cpp, and SparkCastExprTest.cpp, with unit tests validating correctness. The commit fc3c6eb573e845ff4b6132db7ea81439a20e6545 documents the change ("feat: Add Spark CAST(timestamp as integral) (#11468)").
February 2025: Focused on strengthening Spark SQL time-handling and configuration safety across Velox and Gluten to drive reliable time-based analytics and safer runtime behavior. Delivered concrete features and fixes with measurable business value, including enhanced time casting, robust timestamp arithmetic, and reinforced buffer-size configuration parsing.
February 2025: Focused on strengthening Spark SQL time-handling and configuration safety across Velox and Gluten to drive reliable time-based analytics and safer runtime behavior. Delivered concrete features and fixes with measurable business value, including enhanced time casting, robust timestamp arithmetic, and reinforced buffer-size configuration parsing.
October 2024 Velox development highlights focused on correctness of date handling and expanded SQL capabilities, delivering business value through reliable data operations and improved interoperability with downstream systems.
October 2024 Velox development highlights focused on correctness of date handling and expanded SQL capabilities, delivering business value through reliable data operations and improved interoperability with downstream systems.

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