SCBL006

Overview

In this lab, you learn how to run parameterized queries, create and use indexes, and execute transactions against a Spanner database.

Objectives

In this lab, you learn how to:

• Run prarameterized queries using indexes against a Spanner database using the Python Client library.
• Execute transactions against a Spanner database.

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.

Open the lab notebook in Vertex AI Workbench

Open Vertex AI Workbench from the console, and access the pre-created instance from the workbench.

STEPS:

1. In the Google Cloud console, enter Vertex AI in the top search bar.
2. Under Categories > Choose Artificial Intellgence , Select Vertex AI, or else you can go to Vertex AI Dashboard
3. If the Vertex AI APIs are not enabled, click Enable All Recommended APIs.
4. In the left panel, click the Workbench section and open the INSTANCES tab.
5. Select the Create New button. Name the Notebook my-notebook, choose the region. You may choose any zone for this region.
6. Click Machine type from the list on the left, select E2 standard and e2-standard-2 from Advanced options for the Machine type.
7. When the instance is ready, click the Open JupyterLab link.

Task 1. Programming queries and transactions with Python

1. Open a new Terminal window from the Launcher or from File>New>Terminal, and run

   git clone https://github.com/GoogleCloudPlatform/training-data-analyst

2. In the file explorer on the left, navigate to the home directory and open training-data-analyst/courses/understanding-spanner/colab-notebooks/Spanner_Queries_Transactions.ipynb

3. Run the first cell to install the Python Spanner client library.

4. In the second cell, update the following variables as listed:

Variable	New Value (In the notebook, please leave the outside single quotes)
project_id
region_id

4. Now run the second cell. In this cell, some variables are created and the Spanner API is enabled.

5. Read the text prior to each code cell and run each one. Take the time to understand what the code is doing.

Conclusion:

Congratulations! You have learned how to run parameterized queries and execute transactions against a Spanner database.

End your lab

When you have completed your lab, click End Lab. Your account and the resources you've used are removed from the lab platform.

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