January 2026 monthly summary for the spiceai/datafusion project focused on delivering and validating DataFusion ListFilesCache capabilities. Implemented a new CLI table function list_files_cache and introduced a per-table scoped cache to improve performance and resource management. Completed extensive tests to validate caching behavior and its impact on query performance, and added cache lifecycle handling to ensure stale entries are removed when tables are dropped. This work enhances metadata query performance, provides clear data access patterns for cached files, and establishes robust test coverage and operational visibility.

December 2025: Delivered three performance and maintainability-focused DataFusion enhancements that align with business value and developer experience. Key changes include a DataFrame caching strategy example using CacheFactory to demonstrate effective caching management, optimization of batch processing by integrating LimitedBatchCoalescer with non sort-preserving paths and removing RepartitionExec from the CoalesceBatches optimizer to reduce unnecessary repartitioning, and API consistency improvements by unifying make_array and Spark array implementations (adjusting return types for null data, refactoring shared logic). All work referenced corresponding PRs/issues, maintained tests, and included documentation where applicable. Overall impact is improved runtime throughput, lower resource usage, and clearer, more consistent APIs for users and contributors.

November 2025 monthly highlights for tarantool/datafusion: delivered key performance and quality improvements, fixed a subtle Spark array return-type bug, and expanded caching capabilities to give more control over execution plans. These changes improve runtime performance, reduce type errors at query planning, and provide more flexible, user-facing caching via the DataFrame API.