In the context of Apache Spark, the term "Leader" usually refers to one of the roles in the architecture of a Spark cluster, particularly in the context of cluster managers like Apache Mesos or Kubernetes, or in standalone Spark deployments. Here’s a breakdown of the key roles usually involved in a Spark cluster: 1. **Master Node (Leader):** The master node in a Spark cluster is often referred to as the "leader." It is responsible for resource allocation and job scheduling.
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