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Before you begin
- Labs create a Google Cloud project and resources for a fixed time
- Labs have a time limit and no pause feature. If you end the lab, you'll have to restart from the beginning.
- On the top left of your screen, click Start lab to begin
Enable the Data Catalog API
/ 10
Create the PostgreSQL Database
/ 15
Create a Service Account for postgresql
/ 15
Execute PostgreSQL to Data Catalog connector
/ 15
Create the MySQL Database
/ 15
Create a Service Account for MySQL
/ 15
Execute MySQL to Data Catalog connector
/ 15
Data Catalog is deprecated and will be discontinued on January 30, 2026. You can still complete this lab if you want to.
For steps to transition your Data Catalog users, workloads, and content to Dataplex Catalog, see Transition from Data Catalog to Dataplex Catalog (https://cloud.google.com/dataplex/docs/transition-to-dataplex-catalog).
Dataplex is an intelligent data fabric that enables organizations to centrally discover, manage, monitor, and govern their data across data lakes, data warehouses, and data marts to power analytics at scale.
Data Catalog is a fully managed, scalable metadata management service within Dataplex. It offers a simple and easy-to-use search interface for data discovery, a flexible and powerful cataloging system for capturing both technical and business metadata, and a strong security and compliance foundation with Cloud Data Loss Prevention (part of Sensitive Data Protection) and Identity and Access Management (IAM) integrations.
Using Data Catalog within Dataplex, you can search for assets to which you have access, and you can tag data assets to support discovery and access control. Tags allow you to attach custom metadata fields to specific data assets for easy identification and retrieval (such as tagging certain assets as containing protected or sensitive data); you can also create reusable tag templates to rapidly assign the same tags to different data assets.
In this lab, you learn how to:
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:
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:
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.
If necessary, copy the Username below and paste it into the Sign in dialog.
You can also find the Username in the Lab Details pane.
Click Next.
Copy the Password below and paste it into the Welcome dialog.
You can also find the Password in the Lab Details pane.
Click Next.
Click through the subsequent pages:
After a few moments, the Google Cloud console opens in this tab.
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.
Click through the following windows:
When you are connected, you are already authenticated, and the project 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.
Output:
Output:
gcloud
, in Google Cloud, refer to the gcloud CLI overview guide.
In the Google Cloud console, click on the Navigation menu () > APIs & Services > Library.
In the search bar, enter Data Catalog
, and select the Google Cloud Data Catalog API
.
Click Enable.
Click Check my progress to verify the objective.
us-central1
and us-central1-a
to your default assigned region and zone:init-db.sh
script:This will create your PostgreSQL instance and populate it with a random schema. This can take around 10 to 15 minutes
to complete.
Error: Failed to load "tfplan" as a plan file
, re-run the init-db
script.
Soon after you should receive the following output:
Click Check my progress to verify the objective.
Click Check my progress to verify the objective.
You can build the PostgreSQL connector yourself by going to this GitHub repository.
To facilitate its usage, this lab uses a docker image.
The variables needed were output by the Terraform config.
Soon after you should receive the following output:
Click Check my progress to verify the objective.
Navigate to Dataplex in the Google Cloud console by clicking on the Navigation menu () > View all products > Analytics > Dataplex.
Click on Tag Templates.
You should see the following postgresql Tag Templates:
You should see the following postgresql Entry Group:
postgresql
Entry Group. Your console should resemble the following:This is the real value of an Entry Group — you can see all entries that belong to postgresql using the UI.
warehouse
entries. Look at the Custom entry details and tags:This is the real value the connector adds—it allows you to have the metadata searchable in Dataplex.
From the Dataplex menu, under Discover, click on the Search page.
In the search bar, enter PostgreSQL and click Search.
You no longer see the PostgreSQL Tag Templates in the results:
Ensure you see the following output in Cloud Shell before you move on:
Next, you learn how to do the same thing with a MySQL instance.
us-central1
and us-central1-a
to your default assigned region and zone:init-db.sh
script:This creates your MySQL instance and populate it with a random schema. After a few minutes, you should receive the following output:
Error: Failed to load "tfplan" as a plan file
, re-run the init-db
script.
Click Check my progress to verify the objective.
Click Check my progress to verify the objective.
You can build the MySQL connector yourself by going to this GitHub repository.
To facilitate its usage, this lab uses a docker image.
The variables needed were output by the Terraform config.
Soon after you should receive the following output:
Click Check my progress to verify the objective.
Navigate to Dataplex in the Google Cloud console by clicking on the Navigation menu () > View all products > Analytics > Dataplex.
Click on Tag Templates.
You should see the following mysql Tag Templates:
You should see the following mysql Entry Group:
mysql
Entry Group. Your console should resemble the following:This is the real value of an Entry Group — you can see all entries that belong to MySQL using the UI.
warehouse
entries. Look at the Custom entry details and tags.This is the real value the connector adds — it allows you to have the metadata searchable in Dataplex.
Ensure you see the following output in Cloud Shell before you move on:
From the Dataplex menu, under Discover, click on the Search page.
In the search bar, enter MySQL and click Search.
You no longer see the MySQL Tag Templates in the results.
In this lab, you learned how to build and execute PostgreSQL and MySQL to Dataplex connectors. You also learned how to search for PostgreSQL and MySQL entries in Data Catalog within Dataplex. You can now use this knowledge to build your own connectors.
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Manual Last Updated October 24, 2024
Lab Last Tested October 24, 2024
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