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Dataproc: Qwik Start - Console

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Dataproc: Qwik Start - Console

30 minutes 1 Credit

GSP103

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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 the Google Cloud Console 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. Navigation menu icon

Confirm Cloud Dataproc API is enabled

To create a Dataproc cluster in Google Cloud, the Cloud Dataproc API must be enabled. To confirm the API is enabled:

  1. Click Navigation menu > APIs & Services > Library:

  2. Type Cloud Dataproc in the Search for APIs & Services dialog. The console will display the Cloud Dataproc API in the search results.

  3. Click on Cloud Dataproc API to display the status of the API. If the API is not already enabled, click the Enable button.

If the API's enabled, you're good to go:

Task 1. Create a cluster

  1. In the Cloud Platform Console, select Navigation menu > Dataproc > Clusters, then click Create cluster.

  2. Click Create for Cluster on Compute Engine.

  3. Set the following fields for your cluster and accept the default values for all other fields:

Note: In the Configure nodes section ensure both the Master node and Worker nodes are set to the correct Machine Series and Machine Type
Field Value
Name example-cluster
Region
Zone
Machine Series E2
Machine Type e2-standard-2
Max Worker Nodes 2
Note: A Zone is a special multi-region namespace that is capable of deploying instances into all Google Compute zones globally. You can also specify distinct regions, such as us-central1 or europe-west1, to isolate resources (including VM instances and Cloud Storage) and metadata storage locations utilized by Cloud Dataproc within the user-specified region.
  1. Click Create to create the cluster.

Your new cluster will appear in the Clusters list. It may take a few minutes to create, the cluster Status shows as Provisioning until the cluster is ready to use, then changes to Running.

Test completed task

Click Check my progress to verify your performed task.

Create a Dataproc cluster

Task 2. Submit a job

To run a sample Spark job:

  1. Click Jobs in the left pane to switch to Dataproc's jobs view, then click Submit job.

  2. Set the following fields to update Job. Accept the default values for all other fields:

Field Value
Region
Cluster example-cluster
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.)
  1. Click Submit.
Note: How the job calculates Pi: The Spark job estimates a value of Pi using the Monte Carlo method. It generates x,y points on a coordinate plane that models a circle enclosed by a unit square. The input argument (1000) determines the number of x,y pairs to generate; the more pairs generated, the greater the accuracy of the estimation. This estimation leverages Cloud Dataproc worker nodes to parallelize the computation. For more information, see Estimating Pi using the Monte Carlo Method and see JavaSparkPi.java on GitHub.

Your job should appear in the Jobs list, which shows your project's jobs with its cluster, type, and current status. Job status displays as Running, and then Succeeded after it completes.

Test completed task

Click Check my progress to verify your performed task.

Submit a job

Task 3. View the job output

To see your completed job's output:

  1. Click the job ID in the Jobs list.

  2. Check Line wrapping or scroll all the way to the right to see the calculated value of Pi. Your output, with Line wrapping checked, should look something like this:

Output

Your job has successfully calculated a rough value for pi!

Task 4. Update a cluster

To change the number of worker instances in your cluster:

  1. Select Clusters in the left navigation pane to return to the Dataproc Clusters view.

  2. Click example-cluster in the Clusters list. By default, the page displays an overview of your cluster's CPU usage.

  3. Click Configuration to display your cluster's current settings.

  4. Click Edit. The number of worker nodes is now editable.

  5. Enter 4 in the Worker nodes field.

  6. Click Save.

Your cluster is now updated. Check out the number of VM instances in the cluster.

Test completed task

Click Check my progress to verify your performed task.

Update a cluster

  1. To rerun the job with the updated cluster, you would click Jobs in the left pane, then click SUBMIT JOB.

  2. Set the same fields you set in the Submit a job section:

Field Value
Region
Cluster example-cluster
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.)

  1. Click Submit.

Task 5. 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!

Now you know how to use the Cloud Console to create and update a Dataproc cluster and then submit a job in that cluster.

Finish your quest

This self-paced lab is part of the Baseline: Data, ML, AI and Data Engineering quests. A quest is a series of related labs that form a learning path. Completing a 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 any quest that contains this lab and get immediate completion credit. See the Google Cloud Skills Boost catalog to see 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 16, 2022

Lab Last Tested August 16, 2022

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