GSP814

Overview

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

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.

What you'll learn

In this lab, you learn how to:

• Enable the Data Catalog API.
• Configure Dataplex connectors for PostgreSQL and MySQL.
• Search for PostgreSQL and MySQL entries in Data Catalog within Dataplex.

Prerequisites

Note: Before starting this lab, log out of your personal or corporate gmail account, or run this lab in Incognito. This prevents sign-in confusion while the lab is running.

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 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 panel.

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 panel.

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 view a menu with a list of Google Cloud products and services, click the Navigation menu at the top-left.

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.

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:

Your Cloud Platform project in this session is set to {{{project_0.project_id | "PROJECT_ID"}}}

gcloud is the command-line tool for Google Cloud. It comes pre-installed on Cloud Shell and supports tab-completion.

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

gcloud auth list

3. Click Authorize.

Output:

ACTIVE: * ACCOUNT: {{{user_0.username | "ACCOUNT"}}} To set the active account, run: $ gcloud config set account `ACCOUNT`

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

gcloud config list project

Output:

[core] project = {{{project_0.project_id | "PROJECT_ID"}}} Note: For full documentation of gcloud, in Google Cloud, refer to the gcloud CLI overview guide.

Task 1. Enable the Data Catalog API

1. In the Google Cloud console, click on the Navigation menu () > APIs & Services > Library.

2. In the search bar, enter Data Catalog, and select the Google Cloud Data Catalog API.

3. Click Enable.

Note: If you run into an "Action Failed" error after trying to enable the Data Catalog API, try the following steps: click close, refresh your browser tab, then click Enable again.

Click Check my progress to verify the objective. Enable the Data Catalog API

Task 2. PostgreSQL to Dataplex

Create a variable for Project ID

• In Cloud Shell, run the following command to set your Project ID as an environment variable:

export PROJECT_ID=$(gcloud config get-value project)

Create the PostgreSQL Database

1. Run the following command to clone the Github repository:

gsutil cp gs://spls/gsp814/cloudsql-postgresql-tooling.zip . unzip cloudsql-postgresql-tooling.zip

2. Next, change your current working directory to the cloned repo directory:

cd cloudsql-postgresql-tooling/infrastructure/terraform

3. Run the following commands to change the region and zone from us-central1 and us-central1-a to your default assigned region and zone:

export REGION={{{project_0.default_region|REGION}}} sed -i "s/us-central1/$REGION/g" variables.tf export ZONE={{{project_0.default_zone|ZONE}}} sed -i "s/$REGION-a/$ZONE/g" variables.tf

4. Next, execute the init-db.sh script:

cd ~/cloudsql-postgresql-tooling bash init-db.sh

This will create your PostgreSQL instance and populate it with a random schema. This can take around 10 to 15 minutes to complete.

Note: If you get an Error: Failed to load "tfplan" as a plan file, re-run the init-db script.

Soon after you should receive the following output:

CREATE TABLE factory_warehouse69945.home17e97c57 ( house57588 DATE, paragraph64180 SMALLINT, ip_address61569 JSONB, date_time44962 REAL, food19478 JSONB, state8925 VARCHAR(25), cpf75444 REAL, date_time96090 SMALLINT, reason7955 CHAR(5), phone_number96292 INT, size97593 DATE, date_time609 CHAR(5), location70431 DATE ) COMPLETED

Click Check my progress to verify the objective. Create the PostgreSQL Database

Set up the Service Account

1. Create a Service Account:

gcloud iam service-accounts create postgresql2dc-credentials \ --display-name "Service Account for PostgreSQL to Data Catalog connector" \ --project $PROJECT_ID

2. Next, create and download the Service Account Key:

gcloud iam service-accounts keys create "postgresql2dc-credentials.json" \ --iam-account "postgresql2dc-credentials@$PROJECT_ID.iam.gserviceaccount.com"

3. Next, add Data Catalog admin role to the Service Account:

gcloud projects add-iam-policy-binding $PROJECT_ID \ --member "serviceAccount:postgresql2dc-credentials@$PROJECT_ID.iam.gserviceaccount.com" \ --quiet \ --project $PROJECT_ID \ --role "roles/datacatalog.admin"

Click Check my progress to verify the objective. Create a Service Account for PostgreSQL

Execute PostgreSQL to Dataplex connector

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.

1. Change directories into the location of the Terraform scripts:

cd infrastructure/terraform/

2. Grab the environment variables:

public_ip_address=$(terraform output -raw public_ip_address) username=$(terraform output -raw username) password=$(terraform output -raw password) database=$(terraform output -raw db_name)

3. Change back to the root directory for the example code:

cd ~/cloudsql-postgresql-tooling

4. Execute the connector:

docker run --rm --tty -v \ "$PWD":/data mesmacosta/postgresql2datacatalog:stable \ --datacatalog-project-id=$PROJECT_ID \ --datacatalog-location-id=$REGION \ --postgresql-host=$public_ip_address \ --postgresql-user=$username \ --postgresql-pass=$password \ --postgresql-database=$database

Soon after you should receive the following output:

============End postgresql-to-datacatalog============

Click Check my progress to verify the objective. Execute PostgreSQL to Data Catalog connector

Check the results of the script

1. Navigate to Dataplex in the Google Cloud console by clicking on the Navigation menu () > View all products > Analytics > Dataplex.

2. Click on Tag Templates.

You should see the following postgresql Tag Templates:

3. Click on Entry groups.

You should see the following postgresql Entry Group:

4. 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.

5. 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

1. To delete the created resources, run the following command to delete the PostgreSQL metadata:

./cleanup-db.sh

2. Now execute the cleaner container:

docker run --rm --tty -v \ "$PWD":/data mesmacosta/postgresql-datacatalog-cleaner:stable \ --datacatalog-project-ids=$PROJECT_ID \ --rdbms-type=postgresql \ --table-container-type=schema

3. Finally, delete the PostgreSQL database:

./delete-db.sh

4. From the Dataplex menu, under Discover, click on the Search page.

5. 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:

Cloud SQL Instance deleted COMPLETED

Next, you learn how to do the same thing with a MySQL instance.

Task 3. MySQL to Dataplex

Create the MySQL database

1. Run the following command in Cloud Shell to return to your home directory:

cd

2. Run the following command to download the scripts to create and populate your MySQL instance:

gsutil cp gs://spls/gsp814/cloudsql-mysql-tooling.zip . unzip cloudsql-mysql-tooling.zip

3. Now change your current working directory to the cloned repo directory:

cd cloudsql-mysql-tooling/infrastructure/terraform

4. Run the following commands to change the region and zone from us-central1 and us-central1-a to your default assigned region and zone:

export REGION={{{project_0.default_region|REGION}}} sed -i "s/us-central1/$REGION/g" variables.tf export ZONE={{{project_0.default_zone|ZONE}}} sed -i "s/$REGION-a/$ZONE/g" variables.tf

5. Next execute the init-db.sh script:

cd ~/cloudsql-mysql-tooling bash init-db.sh

This creates your MySQL instance and populate it with a random schema. After a few minutes, you should receive the following output:

CREATE TABLE factory_warehouse14342.persons88a5ebc4 ( address9634 TEXT, cpf12934 FLOAT, food88799 BOOL, food4761 LONGTEXT, credit_card44049 FLOAT, city8417 TINYINT, name76076 DATETIME, address19458 TIME, reason49953 DATETIME ) COMPLETED Note: If you get an Error: Failed to load "tfplan" as a plan file, re-run the init-db script.

Click Check my progress to verify the objective. Create the MySQL Database

Set up the Service Account

1. Run the following to create a Service Account:

gcloud iam service-accounts create mysql2dc-credentials \ --display-name "Service Account for MySQL to Data Catalog connector" \ --project $PROJECT_ID

2. Next, create and download the Service Account Key:

gcloud iam service-accounts keys create "mysql2dc-credentials.json" \ --iam-account "mysql2dc-credentials@$PROJECT_ID.iam.gserviceaccount.com"

3. Next add Data Catalog admin role to the Service Account:

gcloud projects add-iam-policy-binding $PROJECT_ID \ --member "serviceAccount:mysql2dc-credentials@$PROJECT_ID.iam.gserviceaccount.com" \ --quiet \ --project $PROJECT_ID \ --role "roles/datacatalog.admin"

Click Check my progress to verify the objective. Create a Service Account for MySQL

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.

1. Change directories into the location of the Terraform scripts:

cd infrastructure/terraform/

2. Grab the environment variables:

public_ip_address=$(terraform output -raw public_ip_address) username=$(terraform output -raw username) password=$(terraform output -raw password) database=$(terraform output -raw db_name)

3. Change back to the root directory for the example code:

cd ~/cloudsql-mysql-tooling

4. Execute the connector:

docker run --rm --tty -v \ "$PWD":/data mesmacosta/mysql2datacatalog:stable \ --datacatalog-project-id=$PROJECT_ID \ --datacatalog-location-id=$REGION \ --mysql-host=$public_ip_address \ --mysql-user=$username \ --mysql-pass=$password \ --mysql-database=$database

Soon after you should receive the following output:

============End mysql-to-datacatalog============

Click Check my progress to verify the objective. Execute MySQL to Data Catalog connector

Check the results of the script

1. Navigate to Dataplex in the Google Cloud console by clicking on the Navigation menu () > View all products > Analytics > Dataplex.

2. Click on Tag Templates.

You should see the following mysql Tag Templates:

3. Click on Entry groups.

You should see the following mysql Entry Group:

4. 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.

5. 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

1. To delete the created resources, run the following command to delete the MySQL metadata:

./cleanup-db.sh

2. Now execute the cleaner container:

docker run --rm --tty -v \ "$PWD":/data mesmacosta/mysql-datacatalog-cleaner:stable \ --datacatalog-project-ids=$PROJECT_ID \ --rdbms-type=mysql \ --table-container-type=database

3. Finally, delete the PostgreSQL database:

./delete-db.sh

Ensure you see the following output in Cloud Shell before you move on:

Cloud SQL Instance deleted COMPLETED

4. From the Dataplex menu, under Discover, click on the Search page.

5. In the search bar, enter MySQL and click Search.

You no longer see the MySQL Tag Templates in the results.

Congratulations!

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.

Next steps / Learn more

• Check out related labs in the Data Catalog Fundamentals course.
• Read the Data Catalog Overview
• Learn How to search with Data Catalog
• Browse the Overview of APIs and Client Libraries

Google Cloud training and certification

...helps you make the most of Google Cloud technologies. Our classes include technical skills and best practices to help you get up to speed quickly and continue your learning journey. We offer fundamental to advanced level training, with on-demand, live, and virtual options to suit your busy schedule. Certifications help you validate and prove your skill and expertise in Google Cloud technologies.

Manual Last Updated October 24, 2024

Lab Last Tested October 24, 2024

Copyright 2024 Google LLC All rights reserved. Google and the Google logo are trademarks of Google LLC. All other company and product names may be trademarks of the respective companies with which they are associated.