GSP104

Overview

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 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 the command line to create a Dataproc cluster, run a simple Apache Spark job in the cluster, and then modify the number of workers in the cluster.

What you'll do

In this lab, you learn how to:

• Create a Dataproc cluster using the command line
• Run a simple Apache Spark job
• 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 are made available to you.

This hands-on lab lets you do the lab activities in a real cloud environment, not in a simulation or demo environment. It does so by giving you new, temporary credentials 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

1. Click the Start Lab button. If you need to pay for the lab, a dialog opens for you to select your payment method. On the left is the Lab Details pane with the following:

   • The Open Google Cloud 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 Cloud console (or right-click and select Open Link in Incognito Window if you are running the Chrome browser).

   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 below and paste it into the Sign in dialog.

   {{{user_0.username | "Username"}}}

   You can also find the Username in the Lab Details pane.

4. Click Next.

5. Copy the Password below and paste it into the Welcome dialog.

   {{{user_0.password | "Password"}}}

   You can also find the Password in the Lab Details pane.

6. Click Next.

   Important: You must use the credentials the lab provides you. Do not use your Google Cloud account credentials. Note: Using your own Google Cloud account for this lab may incur extra charges.

7. 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 Google Cloud console opens in this tab.

Note: To access Google Cloud products and services, click the Navigation menu or type the service or product name in the Search field.

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.

2. Click through the following windows:

   • Continue through the Cloud Shell information window.
   • Authorize Cloud Shell to use your credentials to make Google Cloud API calls.

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.

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

4. Click Authorize.

Output:

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

Output:

Task 1. Create a cluster

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

2. Dataproc creates staging and temp buckets that are shared among clusters in the same region. Since we're not specifying an account for Dataproc to use, it will use the Compute Engine default service account, which doesn't have storage bucket permissions by default. Let's add those.

• First, run the following commands to grab the PROJECT_ID and PROJECT_NUMBER:

• Now run the following command to give the Storage Admin role to the Compute Engine default service account:

3. Enable Private Google Access on your subnetwork by running the following command:

4. Run the following command to create a cluster called example-cluster with e2-standard-4 VMs and default Cloud Dataproc settings:

5. 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 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

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

1. 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:

2. 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.

Congratulations!

You learned how to use the command line to create and modify a Dataproc cluster and submit jobs.

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 29, 2024

Lab Last Tested August 29, 2024

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