Introduction to Cloud Dataproc: Hadoop and Spark on Google Cloud

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Introduction to Cloud Dataproc: Hadoop and Spark on Google Cloud

30 minutes 1 Credit


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Cloud Dataproc is a managed Spark and Hadoop service that lets you take advantage of open source data tools for batch processing, querying, streaming, and machine learning. Cloud Dataproc automation helps you create clusters quickly, manage them easily, and save money by turning clusters off when you don't need them. With less time and money spent on administration, you can focus on your jobs and your data.

This lab is adapted from

What you'll learn

  • How to create a managed Cloud Dataproc cluster (with Apache Spark pre-installed).

  • How to submit a Spark job

  • How to shut down your cluster

What you'll need

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 a panel populated with the temporary credentials that you must use for this lab.

    Open Google Console

  2. Copy the username, and then click Open Google Console. The lab spins up resources, and then opens another tab that shows the Sign in page.

    Sign in

    Tip: Open the tabs in separate windows, side-by-side.

  3. In the Sign in page, paste the username that you copied from the left panel. Then copy and paste the password.

    Important: You must use the credentials from the left panel. Do not use your Google Cloud Training credentials. If you have your own Google Cloud account, do not use it for this lab (avoids incurring charges).

  4. 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.

Check project permissions

Before you begin your work on Google Cloud, you need to ensure that your project has the correct permissions within Identity and Access Management (IAM).

  1. In the Google Cloud console, on the Navigation menu (nav-menu.png), click IAM & Admin > IAM.

  2. Confirm that the default compute Service Account {project-number} is present and has the editor role assigned. The account prefix is the project number, which you can find on Navigation menu > Home.


If the account is not present in IAM or does not have the editor role, follow the steps below to assign the required role.

  • In the Google Cloud console, on the Navigation menu, click Home.

  • Copy the project number (e.g. 729328892908).

  • On the Navigation menu, click IAM & Admin > IAM.

  • At the top of the IAM page, click Add.

  • For New principals, type:


Replace {project-number} with your project number.

  • For Role, select Project (or Basic) > Editor. Click Save.


Create a Cloud Dataproc cluster

In the console, click Navigation menu > Dataproc > Clusters on the top left of the screen:


To create a new cluster, click Create cluster.


There are many parameters you can configure when creating a new cluster. Set values for the parameters listed below, leave the default settings for the other parameters.

Parameter Value
Name qlab
Region us-central1
Zone us-central1-c
Click Configure nodes, for Master node - Machine type 4 vCPUs (n1-standard-4)
Worker node - Machine type 2 vCPUs (n1-standard-2)

Click on Create to create the new cluster. You willll see the Status go from Provisioning to Running—move on to the next step once you're output resembles the following:


Test Completed Task

Click Check my progress to verify your performed task. If you have completed the task successfully you will granted with an assessment score.

Create a Cloud Dataproc cluster (region: us-central1).

Submit a Spark job to your cluster

Select Jobs to switch to Dataproc's jobs view.


Click Submit job.


Set values for the parameters listed below, leave the default settings for the other parameters.

Parameter Value
Region us-central1
Cluster qlab
Job type Spark
Main class or jar org.apache.spark.examples.SparkPi
Jar files file:///usr/lib/spark/examples/jars/spark-examples.jar
Arguments 1000 (This sets the number of tasks)


Click Submit.

Your job should appear in the Jobs list, which shows all your project's jobs with their cluster, type, and current status. The new job displays as "Running"—move on once you see "Succeeded" as the Status.

Test Completed Task

Click Check my progress to verify your performed task. If you have completed the task successfully you will granted with an assessment score.

Submit a Spark job to your cluster (region: us-central1).

To see your completed job's output, click the job ID in the Jobs list.


To avoid scrolling, select Line Wrap to ON.


You should see that your job has successfully calculated a rough value for pi!

Shut down your cluster

You can shut down a cluster on the Clusters page.


Select the checkbox next to the qlab cluster and click Delete.


Click CONFIRM to confirm deletion.

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 learned how to create a Dataproc cluster, submit a Spark job, and shut down your cluster!

Next Steps / Learn More

Continue your Google Cloud learning with these suggestions:

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Manual Last Updated February 25, 2021
Lab Last Tested February 25, 2021

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