GSP104

Overview

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).

Note: Use an Incognito or private browser window to run this lab. This prevents any conflicts between your personal account and the Student account, which may cause extra charges incurred to your personal account.

• Time to complete the lab---remember, once you start, you cannot pause a lab.

Note: If you already have your own personal Google Cloud account or project, do not use it for this lab to avoid extra charges to your account.

How to start your lab and sign in to the Google Cloud Console

1. 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

2. 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.

3. If necessary, copy the Username from the Lab Details panel and paste it into the Sign in dialog. Click Next.

4. 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.

5. 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.

Note: You can view the menu with a list of Google Cloud Products and Services by clicking the Navigation menu at the top-left.

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.

1. Click Activate Cloud Shell at the top of the Google Cloud console.

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:

Your Cloud Platform project in this session is set to YOUR_PROJECT_ID

gcloud is the command-line tool for Google Cloud. It comes pre-installed on Cloud Shell and supports tab-completion.

2. (Optional) You can list the active account name with this command:

gcloud auth list

3. Click Authorize.

4. Your output should now look like this:

Output:

ACTIVE: * ACCOUNT: student-01-xxxxxxxxxxxx@qwiklabs.net To set the active account, run: $ gcloud config set account `ACCOUNT`

5. (Optional) You can list the project ID with this command:

gcloud config list project

Output:

[core] project = <project_ID>

Example output:

[core] project = qwiklabs-gcp-44776a13dea667a6 Note: For full documentation of gcloud, in Google Cloud, refer to the gcloud CLI overview guide.

Task 1. Create a cluster

1. In Cloud Shell, run the following command to set the Region:

gcloud config set dataproc/region us-east1

2. Run the following command to create a cluster called example-cluster with default Cloud Dataproc settings:

gcloud dataproc clusters create example-cluster --worker-boot-disk-size 500

3. If asked to confirm a zone for your cluster. Enter Y.

Your cluster will build for a couple of minutes.

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

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.

Create a Dataproc cluster

Task 2. Submit a job

• Run this command to submit a sample Spark job that calculates a rough value for pi:

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

The command specifies:

• That you want to run a spark job on the example-cluster cluster
• The class containing 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 1000

Note: Parameters passed to the job must follow a double dash (--). See the gcloud documentation for more information.

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

Waiting for job output... ... Pi is roughly 3.14118528 ... state: FINISHED

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.

Submit a job

Task 3. Update a cluster

1. To change the number of workers in the cluster to four, run the following command:

gcloud dataproc clusters update example-cluster --num-workers 4

Your cluster's updated details are displayed in the command's output:

Waiting on operation [projects/qwiklabs-gcp-7f7aa0829e65200f/regions/global/operations/b86892cc-e71d-4e7b-aa5e-6030c945ea67]. Waiting for cluster update operation...done.

2. You can use the same command to decrease the number of worker nodes:

gcloud dataproc clusters update example-cluster --num-workers 2

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.

Congratulations!

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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