Checkpoints
Enable the Data Catalog API
/ 10
Create the SQLServer Database
/ 10
Set Up the Service Account for SQLServer
/ 10
Execute SQLServer to Data Catalog connector
/ 10
Create the PostgreSQL Database
/ 10
Create a Service Account for postgresql
/ 10
Execute PostgreSQL to Data Catalog connector
/ 10
Create the MySQL Database
/ 10
Create a Service Account for MySQL
/ 10
Execute MySQL to Data Catalog connector
/ 10
Build and Execute MySQL, PostgreSQL, and SQLServer to Data Catalog Connectors
GSP814
Overview
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 (DLP) and Cloud Identity and Access Management (IAM) integrations.
Using Dataplex
There are two main ways you interact with Dataplex:
-
Searching for data assets that you have access to.
-
Tagging assets with metadata.
Prerequisites
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).
- 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
-
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
-
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. -
If necessary, copy the Username from the Lab Details panel and paste it into the Sign in dialog. Click Next.
-
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. -
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.
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.
- 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:
gcloud
is the command-line tool for Google Cloud. It comes pre-installed on Cloud Shell and supports tab-completion.
-
(Optional) You can list the active account name with this command:
-
Click Authorize.
-
Your output should now look like this:
Output:
-
(Optional) You can list the project ID with this command:
Output:
Example output:
gcloud
, in Google Cloud, refer to the gcloud CLI overview guide.
Task 1. Enable the Data Catalog API
-
Open the Navigation menu and select APIs and Services > Library.
-
In the search bar, enter in "Data Catalog" and select the
Google Cloud Data Catalog API
. -
Then click Enable.
If you run into the following error after trying to enable the Data Catalog API:
- Click Close.
- Refresh your browser tab.
- Click Enable again.
The Data Catalog API should be successfully enabled:
Click Check my progress to verify the objective.
Task 2. SQLServer to Dataplex
Start by setting up your environment.
-
Run the following command to set your Project ID, replacing
<YOUR_PROJECT_ID>
with the Project ID found in the connection details panel:
-
Next set it as an environment variable:
Create the SQLServer database
-
In your Cloud Shell session, run the following command to download the scripts to create and populate your SQLServer instance:
-
Now change your current working directory to the downloaded directory:
-
Now run the
init-db.sh
script.
This will create your SQLServer instance and populate it with a random schema.
Error: Failed to load "tfplan" as a plan file
, re-run the init-db
script.
This will take around 5 to 10 minutes
to complete. You can move on when you receive the following output:
Click Check my progress to verify the objective.
Set up the Service Account
-
Run the following command to create a Service Account:
-
Now create and download the Service Account Key.
-
Add the Data Catalog admin role to the Service Account:
Click Check my progress to verify the objective.
Execute SQLServer to Dataplex connector
You can build the SQLServer connector yourself by going to this GitHub repository.
To facilitate its usage, we are going to use a docker image.
The variables needed were output by the Terraform config.
-
Change directories into the location of the Terraform scripts:
-
Grab the environment variables:
-
Change back to the root directory for the example code:
-
Run the following command to execute the connector:
Soon after you should receive the following output:
Click Check my progress to verify the objective.
Search for the SQLServer Entries in Dataplex
-
After the script finishes, open the navigation menu and select Dataplex from the list of services.
-
In the the Dataplex page, click on Tag Templates.
You should see your sqlserver Tag Templates listed.
- Next, select Entry Groups.
You should see the sqlserver Entry Group in the Entry Groups list:
- Now click on the
sqlserver
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 sqlserver using the UI.
- Click on one of the
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.
Clean up
-
To delete the created resources, run the following command to delete the SQLServer metadata:
-
Now execute the cleaner container:
-
Now run the following command to delete the SQLServer database:
-
From the Navigation menu click Dataplex.
-
Search for sqlserver.
You will no longer see the SQLServer Tag Templates in the results:
Ensure you see the following output in Cloud Shell before you move on:
You will now learn how to do the same thing with a PostgreSQL instance.
Task 3. PostgreSQL to Dataplex
Create the PostgreSQL Database
-
Run the following command in Cloud Shell to return to your home directory:
-
Run the following command to clone the Github repository:
-
Now change your current working directory to the cloned repo directory:
-
Now execute the
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.
Set up the Service Account
-
Create a Service Account:
-
Next create and download the Service Account Key:
-
Next add Data Catalog admin role to the Service Account:
Click Check my progress to verify the objective.
Execute PostgreSQL to Dataplex connector
You can build the PostgreSQL connector yourself by going to this GitHub repository.
To facilitate its usage, we are going to use a docker image.
The variables needed were output by the Terraform config.
-
Change directories into the location of the Terraform scripts:
-
Grab the environment variables:
-
Change back to the root directory for the example code:
-
Execute the connector:
Soon after you should receive the following output:
Click Check my progress to verify the objective.
Check the results of the script
-
Ensure that you are in the Dataplex home page.
-
Click on Tag Templates.
You should see the following postgresql Tag Templates:
- Click on Entry groups.
You should see the following postgresql Entry Group:
- Now click on the
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.
- Click on one of the
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.
Clean up
-
To delete the created resources, run the following command to delete the PostgreSQL metadata:
-
Now execute the cleaner container:
-
Finally, delete the PostgreSQL database:
-
Now, from the Navigation menu click on Dataplex.
-
Search for PostgreSQL. You will no longer see the PostgreSQL Tag Templates in the results:
Ensure you see the following output in Cloud Shell before you move on:
You will now learn how to do the same thing with a MySQL instance.
Task 4. MySQL to Dataplex
Create the MySQL database
-
Run the following command in Cloud Shell to return to your home directory:
-
Run the following command to download the scripts to create and populate your MySQL instance:
-
Now change your current working directory to the cloned repo directory:
-
Next execute the
init-db.sh
script:
This will create 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.
Set up the Service Account
-
Run the following to create a Service Account:
-
Next, create and download the Service Account Key:
-
Next add Data Catalog admin role to the Service Account:
Click Check my progress to verify the objective.
Execute MySQL to Dataplex connector
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.
-
Change directories into the location of the Terraform scripts:
-
Grab the environment variables:
-
Change back to the root directory for the example code:
-
Execute the connector:
Soon after you should receive the following output:
Click Check my progress to verify the objective.
Check the results of the script
-
Ensure that you are in the Dataplex home page.
-
Click on Tag Templates.
You should see the following mysql Tag Templates:
- Click on Entry groups.
You should see the following mysql Entry Group:
- Now click on the
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.
- Click on one of the
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.
Clean up
-
To delete the created resources, run the following command to delete the MySQL metadata:
-
Now execute the cleaner container:
-
Finally, delete the PostgreSQL database:
-
From the Navigation menu click Dataplex.
-
Search for MySQL. You will no longer see the MySQL Tag Templates in the results.
Ensure you see the following output in Cloud Shell before you move on:
Congratulations!
Great job! You received hands-on practice with Dataplex connectors.
In this lab, you learned how to:
-
Enable the Data Catalog API.
-
Create a dataset.
-
Copy a public New York Taxi table to your dataset.
-
Create a tag template and attach the tag to your table.
Finish your quest
This self-paced lab is part of the BigQuery for Data Warehousing, BigQuery for Marketing Analysts, and Data Catalog Fundamentals 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
- Read the Data Catalog Overview
- Learn How to search with Data Catalog
- Browse the Overview of APIs and Client Libraries
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Manual Last Updated January 23, 2023
Lab Last Tested January 23, 2023
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