A framework is introduced for computations with transformations on immutable data. Inspiration is taken from Apache Spark, however the model of computation is generalized from an emphasis on narrow and wide dependencies, to an arbitrary set of transformations that form a directed acyclic graph (DAG). A distributed scheduling algorithm is developed with resiliency mechanisms that can account for stopping failure. Furthermore some properties of the system are derived. Finally future work is discussed showing there is fertile ground for further research and development to extend this work.