In the Spark execution hierarchy, a Job is the coarsest level. A Job corresponds to a high-level action, such as count() or save(), that results in a set of parallel tasks executed by the Spark engine. Below the Job level, there are Stages, which are further divided into Tasks; Executors are the processes launched for executing tasks and Slots are resources allocated to tasks in executors.