Dataproc issues an ERROR_DUE_TO_UPDATE error when a cluster
update operation fails. This error places the cluster in a fail-safe state to
avoid data loss, and restricts further cluster operations: jobs can continue
to be submitted to the cluster, the cluster can be deleted, but further
cluster update operations are not permitted.
Recommendation: After receiving an ERROR_DUE_TO_UPDATE on a cluster,
recreate the cluster
by exporting the cluster configuration to create a new cluster, then delete the
failed cluster. If recreating the cluster fails, contact
Cloud Customer Care for help in restoring the cluster to a
RUNNING state.
Delete a cluster
You can delete a cluster via a Dataproc API
clusters.delete HTTP or programmatic request, using the Google Cloud CLI
gcloud
command-line tool locally in a terminal window or in Cloud Shell, or from the Google Cloud console.
Open the Dataproc
Clusters
page in the Google Cloud console. Select the cluster by checking the box
to the left of the cluster name, then Click Delete to
delete the cluster.
[[["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 2025-09-03 UTC."],[[["\u003cp\u003eDataproc clusters can be updated through the Dataproc API, the \u003ccode\u003egcloud\u003c/code\u003e command-line tool, or the Google Cloud console.\u003c/p\u003e\n"],["\u003cp\u003eUpdatable cluster parameters include the number of standard or secondary worker nodes, graceful decommissioning settings, and cluster labels.\u003c/p\u003e\n"],["\u003cp\u003eDeleting a Dataproc cluster can be accomplished using the Dataproc API, the \u003ccode\u003egcloud\u003c/code\u003e CLI tool, or the Google Cloud console.\u003c/p\u003e\n"],["\u003cp\u003eCluster deletion is irreversible; once a cluster is deleted, it cannot be recovered.\u003c/p\u003e\n"]]],[],null,["This page explains how to update and delete an existing Dataproc cluster.\n\nUpdate a cluster\n\nYou can update a cluster by issuing a Dataproc API\n[clusters.patch](/dataproc/docs/reference/rest/v1/projects.regions.clusters/patch) request, running\na [gcloud dataproc clusters update](/sdk/gcloud/reference/dataproc/clusters/update)\ncommand in a local terminal window or in\n[Cloud Shell](https://console.cloud.google.com/?cloudshell=true), or by editing cluster\nparameters from the Configuration tab of the Cluster details page for the\ncluster in the [Google Cloud console](https://console.cloud.google.com/dataproc/clusters).\n\nThe following cluster parameters can be updated:\n\n- the number of standard worker nodes in a cluster---see [Scaling clusters](/dataproc/docs/concepts/scaling-clusters)\n- the number of secondary worker nodes in a cluster--- see [Preemptible VMs](/dataproc/docs/concepts/preemptible-vms)\n- whether to use [graceful decommissioning](/dataproc/docs/concepts/configuring-clusters/scaling-clusters#graceful_decommissioning) to control shutting down a worker after its jobs are completed\n- adding or deleting cluster [labels](/dataproc/docs/concepts/labels)\n\nCluster update error\n\nDataproc issues an `ERROR_DUE_TO_UPDATE` error when a cluster\nupdate operation fails. This error places the cluster in a fail-safe state to\navoid data loss, and restricts further cluster operations: jobs can continue\nto be submitted to the cluster, the cluster can be deleted, but further\ncluster update operations are not permitted.\n\nRecommendation: After receiving an `ERROR_DUE_TO_UPDATE` on a cluster,\n[recreate the cluster](/dataproc/docs/guides/recreate-cluster#recreate_and_update_a_cluster)\nby exporting the cluster configuration to create a new cluster, then delete the\nfailed cluster. If recreating the cluster fails, contact\n[Cloud Customer Care](/support) for help in restoring the cluster to a\n`RUNNING` state.\n| **Note:** A cluster can enter the `ERROR_DUE_TO_UPDATE` state if you attempt to update cluster resources through Compute Engine API operations. To update cluster resources, use [Dataproc update](/dataproc/docs/guides/manage-cluster#update_a_cluster) operations.\n\nDelete a cluster\n\nYou can delete a cluster via a Dataproc API\n[clusters.delete](/dataproc/docs/reference/rest/v1/projects.regions.clusters/delete) HTTP or programmatic request, using the Google Cloud CLI\n[gcloud](/sdk/gcloud/reference/dataproc/clusters/delete)\ncommand-line tool locally in a terminal window or in [Cloud Shell](https://console.cloud.google.com/?cloudshell=true), or from the [Google Cloud console](https://console.cloud.google.com/dataproc/clusters).\n**Deletion is permanent:** Once deleted, clusters cannot be restored. You can, however, quickly create new Dataproc clusters as you need them. \n\ngcloud command\n\nTo delete a Dataproc cluster, use the gcloud CLI\n[gcloud dataproc clusters delete](/sdk/gcloud/reference/dataproc/clusters/delete)\ncommand locally in a terminal window or in\n[Cloud Shell](https://console.cloud.google.com/?cloudshell=true). \n\n```\ngcloud dataproc clusters delete cluster-name \\\n --region=region\n```\n\nREST API\n\nUse the Dataproc\n[clusters.delete](/dataproc/docs/reference/rest/v1/projects.regions.clusters/delete)\nAPI to delete a cluster.\n\nConsole\n\nOpen the Dataproc\n[Clusters](https://console.cloud.google.com/dataproc/clusters)\npage in the Google Cloud console. Select the cluster by checking the box\nto the left of the cluster name, then Click **Delete** to\ndelete the cluster."]]
