Google Cloud Serverless for Apache Spark documentation

Dataproc | Serverless for Apache Spark | Dataproc Metastore

Use Serverless for Apache Spark to run Spark batch workloads without provisioning and managing your own cluster. Specify workload parameters, and then submit the workload to the Serverless for Apache Spark service. The service will run the workload on a managed compute infrastructure, autoscaling resources as needed. Serverless for Apache Spark charges apply only to the time when the workload is executing.

Start your proof of concept with 300ドル in free credit

  • Get access to Gemini 2.0 Flash Thinking
  • Free monthly usage of popular products, including AI APIs and BigQuery
  • No automatic charges, no commitment

Keep exploring with 20+ always-free products

Access 20+ free products for common use cases, including AI APIs, VMs, data warehouses, and more.

Explore self-paced training, use cases, reference architectures, and code samples with examples of how to use and connect Google Cloud services.
Training
Training and tutorials

Serverless for Apache Spark Quickstart Interactive Tutorial

Interactive tutorial for getting started with Serverless for Apache Spark.

Use case
Use cases

Dataproc Templates on GitHub

Serverless for Apache Spark ready-to-use, config-driven Spark templates.

Use case
Use cases

Serverless for Apache Spark Labs on GitHub

Serverless for Apache Spark hands-on labs built around common use cases.

Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates.

Last updated 2025年11月06日 UTC.