February 2026 monthly summary for repository: apache/spark. Focused on resolving a runtime exception scenario and strengthening VariantType support in the columnar pathway. Key work delivered addresses a specific gap in VariantType handling for batch-row copying, which previously caused runtime errors in streaming pipelines that rely on columnar batches from custom data sources. Key achievements focused on: 1) Robust VariantType support across the columnar row copies (ColumnarBatchRow.copy with PhysicalVariantType and MutableColumnarRow.copy/get VariantType branch); 2) Comprehensive test coverage validating VariantVal round-trip through copy() in ColumnarBatchSuite; 3) Stabilizing streaming data source interactions by eliminating a blocking runtime exception when copying rows with VariantType data. Impact: Enhanced reliability and correctness for streaming pipelines using VariantType columns; reduced runtime failures in production workloads; improved developer confidence and data surface stability for streaming integrations relying on Spark's columnar representations. Technologies/skills demonstrated: Spark internals (ColumnarBatchRow, MutableColumnarRow), VariantType handling, low-level data structures, unit testing (ColumnarBatchSuite), Scala/Java, code review practices, and end-to-end debugging of a streaming-related bug fix. Reference: Commit c4188b0e43182e4585ee09cbf3cd00d633ec72e7 addressing SPARK-55552; supports fix in PR related to VariantType governance and stability in copying of columnar rows (finalized fix closes related issue).