Out of memory errors terminate pipeline execution

Pipeline fails with OutOfMemoryError when executor memory is insufficient for processing batch size or data volume

Increase executor memory via system.resources.memory runtime argument (e.g., 4096), reduce source fetch size to process fewer records per batch, or increase Spark executor memory via system.spark.executor.memory (e.g., 8g)