Create a Dataproc cluster by using the gcloud CLI

This page shows you how to use the Google Cloud CLI gcloud command-line tool to create a Dataproc cluster, run a Apache Spark job in the cluster, then modify the number of workers in the cluster.

You can find out how to do the same or similar tasks with Quickstarts Using the API Explorer, the Google Cloud console in Create a Dataproc cluster by using the Google Cloud console, and using the client libraries in Create a Dataproc cluster by using client libraries.

Before you begin

  1. 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.

  2. In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

    Go to project selector

  3. Make sure that billing is enabled for your Google Cloud project.

  4. Enable the Dataproc API.

    Enable the API

    5.

  5. In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

    Go to project selector

  6. Make sure that billing is enabled for your Google Cloud project.

  7. Enable the Dataproc API.

    Enable the API

    8.

Create a cluster

To create a cluster called example-cluster, run the following command:

gcloud dataproc clusters create example-cluster --region=REGION

The command output confirms cluster creation: 

Waiting for cluster creation operation...done.
Created [... example-cluster]

For information on selecting a region, see Available regions & zones. To see a list of available regions, you can run the gcloud compute regions list command. To learn about regional endpoints, see Regional endpoints.

Submit a job

To submit a sample Spark job that calculates a rough value for pi, run the following command:

gcloud dataproc jobs submit spark --cluster example-cluster \
    --region=REGION \
    --class org.apache.spark.examples.SparkPi \
    --jars file:///usr/lib/spark/examples/jars/spark-examples.jar -- 1000

This command specifies the following:

  • You want to run a spark job on the example-cluster cluster in the specified region
  • The class containing the main method for the job's pi-calculating application
  • The location of the jar file containing your job's code
  • Any parameters you want to pass to the job—in this case the number of tasks, which is 1000

The job's running and final output is displayed in the terminal window:

Waiting for job output...
...
Pi is roughly 3.14118528
...
Job finished successfully.

Update a cluster

To change the number of workers in the cluster to five, run the following command:

gcloud dataproc clusters update example-cluster \
    --region=REGION \
    --num-workers 5

The command output displays your cluster's details. For example:

workerConfig:
...
  instanceNames:
  - example-cluster-w-0
  - example-cluster-w-1
  - example-cluster-w-2
  - example-cluster-w-3
  - example-cluster-w-4
  numInstances: 5
statusHistory:
...
- detail: Add 3 workers.

To decrease the number of worker nodes to the original value, use the same command:

gcloud dataproc clusters update example-cluster \
    --region=REGION \
    --num-workers 2

Clean up

To avoid incurring charges to your Google Cloud account for the resources used on this page, follow these steps.

  1. To delete your example-cluster, run the clusters delete command: 

    gcloud dataproc clusters delete example-cluster \
    --region=REGION

  2. To confirm and complete the cluster deletion, press y and then press Enter when prompted.

What's next