Spark Cross-Cluster Scheduling Explained

Cross-cluster scheduling in Spark refers to the process of scheduling and managing jobs between different Spark clusters. Typically, a Spark job runs within the same Spark cluster, but sometimes users may want to run jobs across different clusters, which requires cross-cluster scheduling. This can be achieved using tools and technologies such as YARN, Mesos, Kubernetes, etc. Through cross-cluster scheduling, users can better manage resources, improve job reliability, and efficiency.