platform

Apache Spark Standalone

Apache Spark Standalone is a simple cluster manager included with Apache Spark that allows users to deploy and manage Spark applications on a cluster of machines without requiring external cluster management software like YARN or Mesos. It provides a lightweight, built-in solution for resource allocation, job scheduling, and fault tolerance, enabling distributed data processing with Spark's core APIs. This mode is ideal for small to medium-sized clusters or development/testing environments where minimal setup is desired.

Also known as: Spark Standalone, Standalone Mode, Spark Standalone Cluster, Apache Spark Standalone Mode, Spark Built-in Cluster Manager
🧊Why learn Apache Spark Standalone?

Developers should use Apache Spark Standalone when they need a quick and easy way to set up a Spark cluster without the complexity of external cluster managers, such as for prototyping, small-scale production workloads, or educational purposes. It is particularly useful in scenarios where you want to avoid dependencies on Hadoop ecosystems or when deploying Spark on-premises or in cloud environments with simple infrastructure. However, for large-scale, multi-tenant production environments, external managers like YARN or Kubernetes are recommended for better resource isolation and scalability.

Compare Apache Spark Standalone

Learning Resources

Related Tools

Alternatives to Apache Spark Standalone