
Fengming Xiao contributed to the apache/celeborn repository by engineering robust backend features and stability improvements for distributed data processing. Over nine months, he delivered enhancements such as a unified partition data writer with tier-based storage policies, memory-first storage optimization, and Spark 4.0 compatibility. His work involved deep refactoring of storage and writer logic, IO and memory optimization, and the introduction of observability tooling, all implemented in Java and Scala. By focusing on configuration-driven design, test coverage, and fault tolerance, Fengming addressed reliability and performance challenges, resulting in a more maintainable, scalable, and efficient Celeborn system for production workloads.

Concise monthly summary for 2025-07 focused on delivering a memory-optimized storage path for key hot workloads in the Celeborn project.
Concise monthly summary for 2025-07 focused on delivering a memory-optimized storage path for key hot workloads in the Celeborn project.
June 2025 monthly summary for apache/celeborn focused on delivering observable reliability improvements, stabilizing storage paths, and optimizing build times. The team implemented a memory-efficient metrics logging path and refreshed observability tooling to reduce OOM risk during long-running workloads.
June 2025 monthly summary for apache/celeborn focused on delivering observable reliability improvements, stabilizing storage paths, and optimizing build times. The team implemented a memory-efficient metrics logging path and refreshed observability tooling to reduce OOM risk during long-running workloads.
May 2025 monthly summary focusing on key accomplishments for apache/celeborn. Delivered a focused memory-usage optimization for push failed batches in the push path, via aggregating failed batches by map ID and attempt ID and introducing LocationPushFailedBatches to manage failures more efficiently. This work improves stability and throughput in failure-prone push scenarios and aligns with CELEBORN-1995.
May 2025 monthly summary focusing on key accomplishments for apache/celeborn. Delivered a focused memory-usage optimization for push failed batches in the push path, via aggregating failed batches by map ID and attempt ID and introducing LocationPushFailedBatches to manage failures more efficiently. This work improves stability and throughput in failure-prone push scenarios and aligns with CELEBORN-1995.
April 2025 milestones for apache/celeborn focused on unifying partition write paths, improving IO efficiency, and ensuring correct storage tier behavior. Key features delivered include a PartitionDataWriter refactor with a tier-based storage policy for centralized, maintainable storage operations, and a Gather API-based optimization for the local flusher to reduce IO overhead when handling multiple small buffers. Additionally, relocation logic now honors configured storage types (celeborn.storage.availableTypes) with accompanying tests to verify correct partition placement. Overall, these changes improve maintainability, storage tier predictability, and IO efficiency, demonstrating strong value delivery with config-driven, test-covered engineering practices. Technologies/skills demonstrated include Java-based system refactors, performance optimization, and test-driven validation, aligned with business objectives to improve reliability and throughput.
April 2025 milestones for apache/celeborn focused on unifying partition write paths, improving IO efficiency, and ensuring correct storage tier behavior. Key features delivered include a PartitionDataWriter refactor with a tier-based storage policy for centralized, maintainable storage operations, and a Gather API-based optimization for the local flusher to reduce IO overhead when handling multiple small buffers. Additionally, relocation logic now honors configured storage types (celeborn.storage.availableTypes) with accompanying tests to verify correct partition placement. Overall, these changes improve maintainability, storage tier predictability, and IO efficiency, demonstrating strong value delivery with config-driven, test-covered engineering practices. Technologies/skills demonstrated include Java-based system refactors, performance optimization, and test-driven validation, aligned with business objectives to improve reliability and throughput.
February 2025 monthly update for apache/celeborn focusing on observability improvements and tiered-writer architecture. Delivered two primary updates: (1) Tier writer refactor introducing LocalTierWriter and DfsTierWriter with comprehensive tests to improve readability and extendability (CELEBORN-1847). Commit: 6f7647e4b4adf55156ac3f962e961725ee16335b. (2) Memory pressure log noise reduction by suppressing output when there is no memory pressure, improving log clarity (CELEBORN-1792). Commit: 2e4f36f9d4203cdd6e66ba59170a7ddd4e3c8d0c. Overall impact: more maintainable partition-writing architecture and clearer observability, enabling faster incident response and future enhancements. Technologies/skills demonstrated: refactoring, test-driven development, tiered-writer design, improved logging/observability.
February 2025 monthly update for apache/celeborn focusing on observability improvements and tiered-writer architecture. Delivered two primary updates: (1) Tier writer refactor introducing LocalTierWriter and DfsTierWriter with comprehensive tests to improve readability and extendability (CELEBORN-1847). Commit: 6f7647e4b4adf55156ac3f962e961725ee16335b. (2) Memory pressure log noise reduction by suppressing output when there is no memory pressure, improving log clarity (CELEBORN-1792). Commit: 2e4f36f9d4203cdd6e66ba59170a7ddd4e3c8d0c. Overall impact: more maintainable partition-writing architecture and clearer observability, enabling faster incident response and future enhancements. Technologies/skills demonstrated: refactoring, test-driven development, tiered-writer design, improved logging/observability.
January 2025 monthly summary for apache/celeborn focusing on build stability, refactoring, and groundwork for CIP-8.
January 2025 monthly summary for apache/celeborn focusing on build stability, refactoring, and groundwork for CIP-8.
December 2024 monthly summary for apache/celeborn focused on stability, performance, and observability enhancements in shuffle data handling and system scalability. Key outcomes include Spark 4.0 compatibility, enhanced metrics, and improved load balancing for more consistent performance across partitions and reducers.
December 2024 monthly summary for apache/celeborn focused on stability, performance, and observability enhancements in shuffle data handling and system scalability. Key outcomes include Spark 4.0 compatibility, enhanced metrics, and improved load balancing for more consistent performance across partitions and reducers.
November 2024 highlights for apache/celeborn: delivered shuffle fault tolerance and read reliability improvements, established Tez integration groundwork, hardened stability and packaging defaults, and updated user documentation. These efforts enhance resilience, enable broader deployment options, and reduce startup/shuffle risk for operators and users.
November 2024 highlights for apache/celeborn: delivered shuffle fault tolerance and read reliability improvements, established Tez integration groundwork, hardened stability and packaging defaults, and updated user documentation. These efforts enhance resilience, enable broader deployment options, and reduce startup/shuffle risk for operators and users.
Month: 2024-10 — Delivered stability improvements in the data write path for apache/celeborn by unifying FileInfo usage to prevent NPEs in PartitionDataWriter. This change ensures a single, consistent FileInfo instance is used across the writer lifecycle, eliminating null disk file info when writers are closed and improving overall state handling. The work reduces runtime exceptions and supports more reliable data processing in production.
Month: 2024-10 — Delivered stability improvements in the data write path for apache/celeborn by unifying FileInfo usage to prevent NPEs in PartitionDataWriter. This change ensures a single, consistent FileInfo instance is used across the writer lifecycle, eliminating null disk file info when writers are closed and improving overall state handling. The work reduces runtime exceptions and supports more reliable data processing in production.
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