Vuelve a crear y actualizar un clúster de Dataproc
Organiza tus páginas con colecciones
Guarda y categoriza el contenido según tus preferencias.
Vuelve a crear y actualizar un clúster
Puedes usar la herramienta de línea de comandos de gcloud o la API de Dataproc para copiar la configuración de un clúster existente, actualizar la configuración copiada y, luego, crear un clúster nuevo con la configuración actualizada.
gcloud CLI
En las instrucciones de ejemplo, se muestra cómo actualizar la configuración de la versión de la imagen en la de un clúster. Puedes cambiar el ejemplo para actualizar diferentes parámetros de configuración del clúster.
Configura variables.
export PROJECT=project-idexport REGION=regionexport OLD_CLUSTER=old-cluster-nameexport NEW_CLUSTER=new-cluster-nameexport NEW_IMAGE_VERSION=image-version (for example, '2.2-debian12')
Exporta la configuración del clúster existente (anterior) a un archivo YAML.
Después de confirmar que tus cargas de trabajo se ejecutan en el clúster nuevo sin problemas, borra el clúster existente (anterior). IMPORTANTE: En este paso, se borran todos los datos almacenados en HDFS y en el disco local de tu clúster.
En las instrucciones de ejemplo, se muestra cómo actualizar el nombre del clúster y la configuración de la versión de la imagen en la configuración de un clúster. Puedes cambiar las variables de ejemplo para actualizar diferentes parámetros de configuración del clúster.
Configura variables.
export PROJECT=project-idexport REGION=regionexport OLD_CLUSTER=old-cluster-nameexport NEW_CLUSTER=new-cluster-nameexport NEW_IMAGE_VERSION=image-version (for example, '2.2-debian12')
Exporta la configuración del clúster existente (anterior) a un archivo JSON.
Después de confirmar que tus cargas de trabajo se ejecutan en el clúster nuevo sin problemas, borra el clúster existente (anterior). IMPORTANTE: En este paso, se borran todos los datos almacenados en HDFS y en el disco local de tu clúster.
[[["Fácil de comprender","easyToUnderstand","thumb-up"],["Resolvió mi problema","solvedMyProblem","thumb-up"],["Otro","otherUp","thumb-up"]],[["Difícil de entender","hardToUnderstand","thumb-down"],["Información o código de muestra incorrectos","incorrectInformationOrSampleCode","thumb-down"],["Faltan la información o los ejemplos que necesito","missingTheInformationSamplesINeed","thumb-down"],["Problema de traducción","translationIssue","thumb-down"],["Otro","otherDown","thumb-down"]],["Última actualización: 2025-09-04 (UTC)"],[[["\u003cp\u003eDataproc restricts the creation of clusters with image versions older than 1.3.95, 1.4.77, 1.5.53, and 2.0.27 due to Apache Log4j security vulnerabilities, and also prevents clusters for version 0.x, 1.0.x, 1.1.x, and 1.2.x.\u003c/p\u003e\n"],["\u003cp\u003eThe latest sub-minor image versions (2.0.29, 1.5.55, and 1.4.79, or later) are advised for creating Dataproc clusters to ensure the most recent security and performance updates, while 2.0.27, 1.5.53, and 1.4.77 are strongly recommended.\u003c/p\u003e\n"],["\u003cp\u003eYou can recreate and update a Dataproc cluster's configuration, including its image version, by exporting the existing cluster's settings, updating them via tools like \u003ccode\u003esed\u003c/code\u003e or \u003ccode\u003ejq\u003c/code\u003e, and then creating a new cluster with the modified configuration.\u003c/p\u003e\n"],["\u003cp\u003eFor production environments, specifying the \u003ccode\u003emajor.minor\u003c/code\u003e image version is recommended to ensure compatibility, and the sub-minor version and OS distributions are automatically set to the latest weekly release.\u003c/p\u003e\n"],["\u003cp\u003eAfter confirming workloads function correctly on the new cluster, the old cluster should be deleted, keeping in mind this deletes all data stored in HDFS and on local disk.\u003c/p\u003e\n"]]],[],null,["| Dataproc prevents the creation of clusters with image versions\n| prior to 1.3.95, 1.4.77, 1.5.53, and 2.0.27, which were affected by\n| [Apache Log4j security vulnerabilities](https://logging.apache.org/log4j/2.x/security.html). Dataproc also prevents cluster creation for Dataproc image versions 0.x, 1.0.x, 1.1.x, and 1.2.x.\n| Dataproc advises that, when possible, you create Dataproc\n| clusters with the latest sub-minor image versions.\n|\n| | Image version | log4j version | Customer guidance |\n| |------------------------------------------------|---------------|----------------------|\n| | 2.0.29, 1.5.55, and 1.4.79, or later of each | log4j.2.17.1 | Advised |\n| | 2.0.28, 1.5.54, and 1.4.78 | log4j.2.17.0 | Advised |\n| | 2.0.27, 1.5.53, and 1.4.77 | log4j.2.16.0 | Strongly recommended |\n| | 2.0.26, 1.5.52, and 1.4.76, or earlier of each | Older version | Discontinue use |\n|\n| See the\n| [Dataproc release notes](/dataproc/docs/release-notes)\n| for specific image and `log4j` update information.\n\nRecreate and update a cluster\n\nYou can use the `gcloud` command-line tool or the Dataproc API\nto copy configuration from an existing cluster, update the copied configuration,\nand then create a new cluster with the updated configuration. \n\ngcloud CLI\n\nThe example instructions show updating the image\nversion setting in a cluster configuration. You can change the\nexample to update different cluster configuration settings.\n| The recommended practice is to specify the `major.minor` image version for production environments or when compatibility with specific component versions is important. The sub-minor and OS distributions are automatically set to the latest weekly release.\n\n1. Set variables. \n\n ```\n export PROJECT=\u003cvar translate=\"no\"\u003eproject-id\u003c/var\u003e\n export REGION=\u003cvar translate=\"no\"\u003eregion\u003c/var\u003e\n export OLD_CLUSTER=\u003cvar translate=\"no\"\u003eold-cluster-name\u003c/var\u003e\n export NEW_CLUSTER=\u003cvar translate=\"no\"\u003enew-cluster-name\u003c/var\u003e\n export NEW_IMAGE_VERSION=\u003cvar translate=\"no\"\u003eimage-version (for example, '2.2-debian12')\u003c/var\u003e\n ```\n2. Export the existing (old) cluster configuration to a YAML file. \n\n ```\n gcloud dataproc clusters export $OLD_CLUSTER \\\n --project=$PROJECT \\\n --region=$REGION \u003e \"${OLD_CLUSTER}-config.yaml\"\n ```\n3. Update the configuration. The following example uses `sed` to update the image version. \n\n ```\n sed -E \"s|(^[[:blank:]]+)imageVersion: .+|\\1imageVersion: ${NEW_IMAGE_VERSION}|g\" \"${OLD_CLUSTER}-config.yaml\" | sed -E '/^[[:blank:]]+imageUri: /d' \u003e \"${NEW_CLUSTER}-config-updated.yaml\"\n ```\n4. Create a new cluster with a new name and the updated configuration. \n\n ```\n gcloud dataproc clusters import $NEW_CLUSTER \\\n --project=$PROJECT \\\n --region=$REGION \\\n --source=\"${NEW_CLUSTER}-config-updated.yaml\"\n ```\n5. After confirming your workloads run in the new cluster without issues, delete the existing (old) cluster. **IMPORTANT:** This step deletes all data stored in HDFS and on local disk in your cluster. \n\n ```\n gcloud dataproc clusters delete $OLD_CLUSTER \\\n --project=$PROJECT \\\n --region=$REGION\n ```\n\nREST API\n\nThe example instructions show updating the cluster name and the image\nversion settings in a cluster configuration. You can change the\nexample variables to update different cluster configuration settings.\n| The recommended practice is to specify the `major.minor` image version for production environments or when compatibility with specific component versions is important. The sub-minor and OS distributions are automatically set to the latest weekly release.\n\n1. Set variables. \n\n ```\n export PROJECT=\u003cvar translate=\"no\"\u003eproject-id\u003c/var\u003e\n export REGION=\u003cvar translate=\"no\"\u003eregion\u003c/var\u003e\n export OLD_CLUSTER=\u003cvar translate=\"no\"\u003eold-cluster-name\u003c/var\u003e\n export NEW_CLUSTER=\u003cvar translate=\"no\"\u003enew-cluster-name\u003c/var\u003e\n export NEW_IMAGE_VERSION=\u003cvar translate=\"no\"\u003eimage-version (for example, '2.2-debian12')\u003c/var\u003e\n\n ```\n2. Export the existing (old) cluster configuration to a JSON file. \n\n ```\n curl -X GET -H \"Authorization: Bearer $(gcloud auth print-access-token)\" \"https://dataproc.googleapis.com/v1/projects/${PROJECT}/regions/${REGION}/clusters/${OLD_CLUSTER}?alt=json\" \u003e \"${OLD_CLUSTER}-config.json\"\n ```\n3. Update the configuration. The following example uses `jq` to update the cluster name and the image version. \n\n ```\n jq \".clusterName = \\\"${NEW_CLUSTER}\\\" | .config.softwareConfig.imageVersion=\\\"${NEW_IMAGE_VERSION}\\\" | del(.config.workerConfig.imageUri) | del(.config.masterConfig.imageUri)\" \"${OLD_CLUSTER}-config.json\" \u003e \"${NEW_CLUSTER}-config-updated.json\"\n ```\n4. Import the updated cluster configuration to create a new cluster with the updated configuration. \n\n ```\n curl -i -X POST -H \"Authorization: Bearer $(gcloud auth print-access-token)\" -H \"Content-Type: application/json; charset=utf-8\" -d \"@${NEW_CLUSTER}-config-updated.json\" \"https://dataproc.googleapis.com/v1/projects/${PROJECT}/regions/${REGION}/clusters?alt=json\"\n ```\n5. After confirming your workloads run in the new cluster without issues, delete the existing (old) cluster. **IMPORTANT:** This step deletes all data stored in HDFS and on local disk in your cluster. \n\n ```\n curl -X DELETE -H \"Authorization: Bearer $(gcloud auth print-access-token)\" \"https://dataproc.googleapis.com/v1/projects/${PROJECT}/regions/${REGION}/clusters/${OLD_CLUSTER}\"\n ```\n\nConsole\n\nThe console does not support recreating a cluster by importing\na cluster configuration."]]
