Chirag Singh enhanced the apache/spark repository by architecting foundational improvements to Spark SQL’s Sort-Partitioned Join (SPJ) capabilities. He refactored SPJ logic from BatchScanExec into a new KeyGroupedPartitionedScan base class, enabling modular SPJ usage and increasing reusability for connectors across scan types. Using Scala and Spark, Chirag also addressed a critical correctness issue by ensuring partial clustering respects a child query’s key-grouped distribution, thereby maintaining accurate query execution under required distribution constraints. His work demonstrated depth in distributed systems and data engineering, laying groundwork for broader SPJ deployment while resolving a complex bug affecting query correctness and modularity.