Sign in to your Google Cloud account. If you're new to
Google Cloud,
create an account to evaluate how our products perform in
real-world scenarios. New customers also get $300 in free credits to
run, test, and deploy workloads.
In the Google Cloud console, on the project selector page,
select or create a Google Cloud project.
[[["易于理解","easyToUnderstand","thumb-up"],["解决了我的问题","solvedMyProblem","thumb-up"],["其他","otherUp","thumb-up"]],[["很难理解","hardToUnderstand","thumb-down"],["信息或示例代码不正确","incorrectInformationOrSampleCode","thumb-down"],["没有我需要的信息/示例","missingTheInformationSamplesINeed","thumb-down"],["翻译问题","translationIssue","thumb-down"],["其他","otherDown","thumb-down"]],["最后更新时间 (UTC)：2025-08-27。"],[[["\u003cp\u003eThis guide demonstrates how to create a Dataproc cluster using the \u003ccode\u003egcloud\u003c/code\u003e command-line tool.\u003c/p\u003e\n"],["\u003cp\u003eYou can use the \u003ccode\u003egcloud\u003c/code\u003e command to submit an Apache Spark job to a cluster to execute code, such as a sample job that calculates the value of \u003ccode\u003epi\u003c/code\u003e.\u003c/p\u003e\n"],["\u003cp\u003eThe number of workers within an existing Dataproc cluster can be adjusted with the \u003ccode\u003egcloud\u003c/code\u003e update command.\u003c/p\u003e\n"],["\u003cp\u003eAfter you are finished with your Dataproc cluster, it can be deleted using the \u003ccode\u003egcloud\u003c/code\u003e command to prevent continued resource usage charges.\u003c/p\u003e\n"]]],[],null,["# Quickstart: Create a Dataproc cluster by using the gcloud CLI\n\nCreate a Dataproc cluster by using the gcloud CLI\n=================================================\n\nThis page shows you how to use the Google Cloud CLI\n[gcloud](/sdk/gcloud/reference/dataproc) command-line tool to create a\nDataproc cluster, run a [Apache Spark](http://spark.apache.org/) job\nin the cluster, then modify the number of workers in the cluster.\n| A convenient way to run the `gcloud` command-line tool is from [Cloud Shell](https://console.cloud.google.com/?cloudshell=true), which has the Google Cloud CLI pre-installed. Cloud Shell is free for Google Cloud customers. To use Cloud Shell, you need a Google Cloud project.\n\nYou can find out how to do the same or similar tasks with\n[Quickstarts Using the API Explorer](/dataproc/docs/quickstarts/create-cluster-template),\nthe Google Cloud console in\n[Create a Dataproc cluster by using the Google Cloud console](/dataproc/docs/quickstarts/create-cluster-console),\nand using the client libraries in\n[Create a Dataproc cluster by using client libraries](/dataproc/docs/quickstarts/create-cluster-client-libraries).\n\nBefore you begin\n----------------\n\n- Sign in to your Google Cloud account. If you're new to Google Cloud, [create an account](https://console.cloud.google.com/freetrial) to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.\n- In the Google Cloud console, on the project selector page,\n select or create a Google Cloud project.\n\n | **Note**: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.\n\n [Go to project selector](https://console.cloud.google.com/projectselector2/home/dashboard)\n-\n [Verify that billing is enabled for your Google Cloud project](/billing/docs/how-to/verify-billing-enabled#confirm_billing_is_enabled_on_a_project).\n\n-\n\n\n Enable the Dataproc API.\n\n\n [Enable the API](https://console.cloud.google.com/flows/enableapi?apiid=dataproc&redirect=https://console.cloud.google.com)\n\n- In the Google Cloud console, on the project selector page,\n select or create a Google Cloud project.\n\n | **Note**: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.\n\n [Go to project selector](https://console.cloud.google.com/projectselector2/home/dashboard)\n-\n [Verify that billing is enabled for your Google Cloud project](/billing/docs/how-to/verify-billing-enabled#confirm_billing_is_enabled_on_a_project).\n\n-\n\n\n Enable the Dataproc API.\n\n\n [Enable the API](https://console.cloud.google.com/flows/enableapi?apiid=dataproc&redirect=https://console.cloud.google.com)\n\n\u003cbr /\u003e\n\nCreate a cluster\n----------------\n\nTo create a cluster called `example-cluster`, run the following command: \n\n```\ngcloud dataproc clusters create example-cluster --region=REGION\n```\n\nThe command output confirms cluster creation: \n\n```\nWaiting for cluster creation operation...done.\nCreated [... example-cluster]\n```\n\n\u003cbr /\u003e\n\nFor information on selecting a region, see\n[Available regions \\& zones](/compute/docs/regions-zones/regions-zones#available).\nTo see a list of available regions, you can run the\n`gcloud compute regions list` command.\nTo learn about regional endpoints, see\n[Regional endpoints](/dataproc/docs/concepts/regional-endpoints).\n\nSubmit a job\n------------\n\nTo submit a sample Spark job that calculates a rough value for `pi`, run the\nfollowing command: \n\n```\ngcloud dataproc jobs submit spark --cluster example-cluster \\\n --region=REGION \\\n --class org.apache.spark.examples.SparkPi \\\n --jars file:///usr/lib/spark/examples/jars/spark-examples.jar -- 1000\n```\n\nThis command specifies the following:\n\n- You want to run a [`spark`](/sdk/gcloud/reference/dataproc/jobs/submit/spark) job on the `example-cluster` cluster in the specified region\n- The `class` containing the main method for the job's pi-calculating application\n- The location of the jar file containing your job's code\n- Any parameters you want to pass to the job---in this case the number of tasks, which is `1000`\n\n| Parameters passed to the job must follow a double dash (`--`). For more information, see the [Google Cloud CLI documentation](/sdk/gcloud/reference/dataproc/jobs/submit/spark).\n\nThe job's running and final output is displayed in the terminal window: \n\n```\nWaiting for job output...\n...\nPi is roughly 3.14118528\n...\nJob finished successfully.\n```\n\nUpdate a cluster\n----------------\n\nTo change the number of workers in the cluster to five, run the\nfollowing command: \n\n```\ngcloud dataproc clusters update example-cluster \\\n --region=REGION \\\n --num-workers 5\n```\n\nThe command output displays your cluster's details. For example: \n\n```\nworkerConfig:\n...\n instanceNames:\n - example-cluster-w-0\n - example-cluster-w-1\n - example-cluster-w-2\n - example-cluster-w-3\n - example-cluster-w-4\n numInstances: 5\nstatusHistory:\n...\n- detail: Add 3 workers.\n```\n\nTo decrease the number of worker nodes to the original value, use the same\ncommand: \n\n```\ngcloud dataproc clusters update example-cluster \\\n --region=REGION \\\n --num-workers 2\n```\n\nClean up\n--------\n\n\nTo avoid incurring charges to your Google Cloud account for\nthe resources used on this page, follow these steps.\n\n1. To delete your `example-cluster`, run the\n [`clusters delete`](/sdk/gcloud/reference/dataproc/clusters/delete)\n command:\n\n ```\n gcloud dataproc clusters delete example-cluster \\\n --region=REGION\n ```\n\n \u003cbr /\u003e\n\n2. To confirm and complete the cluster deletion, press \u003ckbd\u003ey\u003c/kbd\u003e and then\n press \u003ckbd\u003eEnter\u003c/kbd\u003e when prompted.\n\nWhat's next\n-----------\n\n- Learn how to [write and run a Spark Scala job](/dataproc/docs/tutorials/spark-scala)."]]
