Create a Dataproc cluster
Submit a job
Dataproc: Qwik Start - Command Line
Cloud Dataproc is a fast, easy-to-use, fully-managed cloud service for running Apache Spark and Apache Hadoop clusters in a simpler, more cost-efficient way. Operations that used to take hours or days take seconds or minutes instead. Create Cloud Dataproc clusters quickly and resize them at any time, so you don't have to worry about your data pipelines outgrowing your clusters.
This lab shows you how to use gcloud on the Google Cloud to create a Google Cloud Dataproc cluster, run a simple Apache Spark job in the cluster, then modify the number of workers in the cluster.
Setup and requirements
Before you click the Start Lab button
Read these instructions. Labs are timed and you cannot pause them. The timer, which starts when you click Start Lab, shows how long Google Cloud resources will be made available to you.
This hands-on lab lets you do the lab activities yourself in a real cloud environment, not in a simulation or demo environment. It does so by giving you new, temporary credentials that you use to sign in and access Google Cloud for the duration of the lab.
To complete this lab, you need:
- Access to a standard internet browser (Chrome browser recommended).
- Time to complete the lab---remember, once you start, you cannot pause a lab.
How to start your lab and sign in to the Google Cloud Console
Click the Start Lab button. If you need to pay for the lab, a pop-up opens for you to select your payment method. On the left is the Lab Details panel with the following:
- The Open Google Console button
- Time remaining
- The temporary credentials that you must use for this lab
- Other information, if needed, to step through this lab
Click Open Google Console. The lab spins up resources, and then opens another tab that shows the Sign in page.
Tip: Arrange the tabs in separate windows, side-by-side.
Note: If you see the Choose an account dialog, click Use Another Account.
If necessary, copy the Username from the Lab Details panel and paste it into the Sign in dialog. Click Next.
Copy the Password from the Lab Details panel and paste it into the Welcome dialog. Click Next.
Important: You must use the credentials from the left panel. Do not use your Google Cloud Skills Boost credentials. Note: Using your own Google Cloud account for this lab may incur extra charges.
Click through the subsequent pages:
- Accept the terms and conditions.
- Do not add recovery options or two-factor authentication (because this is a temporary account).
- Do not sign up for free trials.
After a few moments, the Cloud Console opens in this tab.
Activate Cloud Shell
Cloud Shell is a virtual machine that is loaded with development tools. It offers a persistent 5GB home directory and runs on the Google Cloud. Cloud Shell provides command-line access to your Google Cloud resources.
Click Activate Cloud Shell at the top of the Google Cloud console.
It takes a few moments to provision and connect to the environment. When you are connected, you are already authenticated, and the project is set to your PROJECT_ID. The output contains a line that declares the PROJECT_ID for this session:
gcloud is the command-line tool for Google Cloud. It comes pre-installed on Cloud Shell and supports tab-completion.
(Optional) You can list the active account name with this command:
(Optional) You can list the project ID with this command:
gcloud, in Google Cloud, refer to the gcloud CLI overview guide.
Task 1. Create a cluster
In Cloud Shell, run the following command to set the Region:
Run the following command to create a cluster called
example-clusterwith default Cloud Dataproc settings:
- If asked to confirm a zone for your cluster. Enter Y.
Your cluster will build for a couple of minutes.
When you see a "Created" message, you're ready to move on.
Test completed task
Click Check my progress to verify your performed task. If you have successfully created a Dataproc cluster, you will see an assessment score.
Task 2. Submit a job
Run this command to submit a sample Spark job that calculates a rough value for pi:
The command specifies:
- That you want to run a spark job on the
classcontaining the main method for the job's pi-calculating application
- The location of the jar file containing your job's code
- The parameters you want to pass to the job—in this case, the number of tasks, which is
The job's running and final output is displayed in the terminal window:
Test completed task
Click Check my progress to verify your performed task. If you have successfully submitted a job, you will see an assessment score.
Task 3. Update a cluster
To change the number of workers in the cluster to four, run the following command:
Your cluster's updated details are displayed in the command's output:
You can use the same command to decrease the number of worker nodes:
Now you can create a Dataproc cluster and adjust the number of workers from the
gcloud command line on the Google Cloud.
Task 4. Test your understanding
Below are multiple-choice questions to reinforce your understanding of this lab's concepts. Answer them to the best of your abilities.
You explored how to use gcloud on the Google Cloud by creating a Google Cloud Dataproc cluster.
Finish your quest
This self-paced lab is part of the Baseline: Data, ML, AI quest. A quest is a series of related labs that form a learning path. Completing this quest earns you a badge to recognize your achievement. You can make your badge or badges public and link to them in your online resume or social media account. Enroll in this quest and get immediate completion credit. Refer to the Google Cloud Skills Boost catalog for all available quests.
Next steps / Learn more
This lab is also part of a series of labs called Qwik Starts. These labs are designed to give you a little taste of the many features available with Google Cloud. Search for "Qwik Starts" in the lab catalog to find the next lab you'd like to take!
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Manual Last Updated August 3, 2022
Lab Last Tested July 13, 2022
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