What is the delayed scheduling in Spark?

Spark’s delayed scheduling is a scheduling strategy that allows tasks to wait a certain amount of time before starting execution, in order to merge more tasks together for execution. This helps reduce the overhead of task initialization and improves overall execution efficiency. Delayed scheduling can effectively reduce communication and data transfer costs among tasks, as well as increase the utilization of computational resources. In Spark, delayed scheduling is typically used in conjunction with dynamic partitioning to dynamically adjust task allocation and execution order based on task characteristics and resource conditions, maximizing the utilization of computational resources.