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This document provides information about Serverless for Apache Spark staging buckets.
Serverless for Apache Spark creates a Cloud Storage staging bucket in your project
or reuses an existing staging bucket from previous batch
creation requests. This is the default bucket created by
Dataproc on Compute Engine clusters. For more
information, see
Dataproc staging and temp buckets.
Serverless for Apache Spark stores workload dependencies, config files, and
job driver console output in the staging bucket.
Serverless for Apache Spark sets regional staging buckets in
Cloud Storage locations
according to the Compute Engine zone where your workload is deployed,
and then creates and manages these project-level, per-location buckets.
Serverless for Apache Spark-created staging buckets are shared among
workloads in the same region, and are created with a
Cloud Storage soft delete retention
duration set to 0 seconds.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-09-13 UTC."],[],[],null,[]]
