# Datastream: PostgreSQL Replication to BigQuery - GSP1052

## **Overview**

In today's competitive environment, organizations need to quickly and easily make decisions based on real-time data. [Datastream for BigQuery](https://cloud.google.com/datastream-for-bigquery) features seamless replication from operational database sources such as AlloyDB, MySQL, PostgreSQL, and Oracle, directly into BigQuery, Google Cloud's serverless data warehouse. With a serverless, auto-scaling architecture, Datastream allows you to easily set up an ELT (Extract, Load, Transform) pipeline for low-latency data replication enabling real-time insights.

In this hands-on lab you'll deploy Cloud SQL for PostgreSQL database and import a sample data set using the `gcloud` command line. In the UI you will create and start a Datastream stream and replicate data into BigQuery.

Although you can easily copy and paste commands from the lab to the appropriate place, students should type the commands themselves to reinforce their understanding of the core concepts

#### **What you'll do**

* Prepare a Cloud SQL for PostgreSQL instance using the Google Cloud Console
    
* Import data into the Cloud SQL instance
    
* Create a Datastream connection profile for the PostgreSQL database
    
* Create a Datastream connection profile for the BigQuery destination
    
* Create a Datastream stream and start replication
    
* Validate that the existing data and changes are replicated correctly into BigQuery
    

### Prerequisites

* Familiarity with standard Linux environments
    
* Familiarity with change data capture (CDC) concepts
    

## **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.
    
    ```apache
    student-02-c9395d1a0b78@qwiklabs.net
    ```
    
    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.
    
    ```apache
    42BMhGEk41xW
    ```
    
    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.

![Navigation menu icon](https://cdn.qwiklabs.com/nUxFb6oRFr435O3t6V7WYJAjeDFcrFb16G9wHWp5BzU%3D align="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**
    
    ![Activate Cloud Shell icon](https://cdn.qwiklabs.com/ep8HmqYGdD%2FkUncAAYpV47OYoHwC8%2Bg0WK%2F8sidHquE%3D align="left")
    
    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**, `qwiklabs-gcp-00-43066a0fc67c`. The output contains a line that declares the **Project\_ID** for this session:

```apache
Your Cloud Platform project in this session is set to qwiklabs-gcp-00-43066a0fc67c
```

`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:
    

```apache
gcloud auth list
```

3. Click **Authorize**.
    

**Output:**

```apache
ACTIVE: *
ACCOUNT: student-02-c9395d1a0b78@qwiklabs.net

To set the active account, run:
    $ gcloud config set account `ACCOUNT`
```

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

```apache
gcloud config list project
```

**Output:**

```apache
[core]
project = qwiklabs-gcp-00-43066a0fc67c
```

**Note:** For full documentation of `gcloud`, in Google Cloud, refer to [the gcloud CLI overview guide](https://cloud.google.com/sdk/gcloud).

## **Task 1. Create a database for replication**

In this section you will prepare a Cloud SQL for PostgreSQL database for Datastream replication.

### Create the Cloud SQL database

1. Run the following command to enable the Cloud SQL API:
    

```apache
gcloud services enable sqladmin.googleapis.com
```

2. Run the following command to create a Cloud SQL for PostgreSQL database instance:
    

```apache
POSTGRES_INSTANCE=postgres-db
DATASTREAM_IPS=35.245.110.238,34.85.182.28,34.150.213.121,34.150.171.115,34.145.160.237
gcloud sql instances create ${POSTGRES_INSTANCE} \
    --database-version=POSTGRES_14 \
    --cpu=2 --memory=10GB \
    --authorized-networks=${DATASTREAM_IPS} \
    --region=us-east4 \
    --root-password pwd \
    --database-flags=cloudsql.logical_decoding=on
```

**Note:**This command creates the database in`us-east4`. For other regions, be sure to replace the`DATASTREAM_IPS`with the right[Datastream Public IPs](https://cloud.google.com/datastream/docs/ip-allowlists-and-regions)for your region.

Once the database instance is created, make a note of the instance's public IP - you'll need this later when creating Datastream's connection profile.

Click **Check my progress** to verify the objective.

Create a database for replication

Check my progress

### Populate the database with sample data

Connect to the PostgreSQL database by running the following command in Cloud Shell.

```apache
gcloud sql connect postgres-db --user=postgres
```

When prompted for the password, enter `pwd`.

Once connected to the database, run the following SQL command to create a sample schema and table:

```apache
CREATE SCHEMA IF NOT EXISTS test;

CREATE TABLE IF NOT EXISTS test.example_table (
id  SERIAL PRIMARY KEY,
text_col VARCHAR(50),
int_col INT,
date_col TIMESTAMP
);

ALTER TABLE test.example_table REPLICA IDENTITY DEFAULT; 

INSERT INTO test.example_table (text_col, int_col, date_col) VALUES
('hello', 0, '2020-01-01 00:00:00'),
('goodbye', 1, NULL),
('name', -987, NOW()),
('other', 2786, '2021-01-01 00:00:00');
```

### Configure the database for replication

* Run the following SQL command to create a publication and a replication slot:
    

```apache
CREATE PUBLICATION test_publication FOR ALL TABLES;
ALTER USER POSTGRES WITH REPLICATION;
SELECT PG_CREATE_LOGICAL_REPLICATION_SLOT('test_replication', 'pgoutput');
```

## **Task 2. Create the Datastream resources and start replication**

Now that the database is ready, create the Datastream connection profiles and stream to begin replication.

1. From the **Navigation menu**, click on **View All Products** under **Analytics** select **Datastream**
    
2. Click **Enable** to enable the Datastream API.
    

![64c95a330abbceb6.png](https://cdn.qwiklabs.com/WQ%2FMz0dupWOEc1cPQqW4fvBeWy56au6SeEw7oxmoB6g%3D align="left")

### **Create connection profiles**

Create two connection profiles, one for the PostgreSQL source, and another for the BigQuery destination.

#### **PostgreSQL connection profile**

1. In the Cloud console, navigate to the **Connection Profiles** tab and click **Create Profile**.
    

![connections profile page with Create Profile link in upper right corner](https://cdn.qwiklabs.com/%2BWHJQ79%2F7o5oOPvGKWt%2Bzv6Sx94pJrO3sNI%2FfeYqLL0%3D align="left")

2. Select the **PostgreSQL** connection profile type.
    

![PostgreSQL tile one of the choices shown](https://cdn.qwiklabs.com/%2F1cLHpUGslpbHEz2e0T5h3H3zNcsweIwbY%2FxrCpbrjQ%3D align="left")

3. Use `postgres-cp` as the name and ID of the connection profile.
    
4. Enter the database connection details:
    

* Region: `us-east4`
    
* The IP and port of the Cloud SQL instance created earlier
    
* Username: `postgres`
    
* Password: `pwd`
    
* Database: `postgres`
    

5. Click **Continue**.
    
6. Leave the encryption as NONE, and click **CONTINUE**.
    
7. Select the **IP allowlisting** connectivity method, and click **Continue**.
    
8. Click **RUN TEST** to make sure that Datastream can reach the database.
    
9. Click **Create**.
    

#### **BigQuery connection profile**

1. In the Cloud console, navigate to the **Connection Profiles** tab and click **Create Profile**.
    

![Connection profiles page wiht the Create Profile link in the upper right corner](https://cdn.qwiklabs.com/%2BWHJQ79%2F7o5oOPvGKWt%2Bzv6Sx94pJrO3sNI%2FfeYqLL0%3D align="left")

2. Select the **BigQuery** connection profile type.
    

![BigQuery tile one of the choices shown](https://cdn.qwiklabs.com/%2F1cLHpUGslpbHEz2e0T5h3H3zNcsweIwbY%2FxrCpbrjQ%3D align="left")

3. Use `bigquery-cp` as the name and ID of the connection profile.
    
4. Region `us-east4`
    
5. Click **Create**.
    

### **Create stream**

Create the stream which connects the connection profiles created above and defines the configuration for the data to stream from source to destination.

* In the Cloud console, navigate to the **Streams** tab and click **Create Stream**.
    

![Streams tab with create stream link in upper right corner](https://cdn.qwiklabs.com/s4DlMI%2BuigseWMiEdDRgTYnBmghyxgEhWra2NRxkNng%3D align="left")

#### **Define the stream details**

1. Use `test-stream` as the name and ID of the stream.
    
2. Region `us-east4`
    
3. Select PostgreSQL as the source type
    
4. Select BigQuery as destination type
    
5. Click **CONTINUE**.
    

![step 1 of create stream details page filled in](https://cdn.qwiklabs.com/VN6fNjyYYWL2mbstgg2zrDzJfUB%2BygXMB7vIpLYg3JU%3D align="left")

#### **Define the source**

1. Select the **postgres-cp** connection profile created in the previous step.
    
2. \[Optional\] Test connectivity by clicking **RUN TEST**
    
3. Click **CONTINUE**.
    

![step two of create streams page filled in](https://cdn.qwiklabs.com/wQpx8zzLoXduV%2FQgzecZUjVOsodk7sE4wi0CqR78JO4%3D align="left")

#### **Configure the source**

1. Specify the replication slot name as `test_replication`.
    
2. Specify the publication name as `test_publication`.
    

![step 3 of create streams page filled in](https://cdn.qwiklabs.com/8U%2BTQcrgekXHD3qWUiI8ikLo5KmfSrl%2BbH56yfQKc5M%3D align="left")

3. Select the **test** schema for replication.
    

![the test schema selected from several choices](https://cdn.qwiklabs.com/Lmrjnghu%2FsrkmvASF35aUKrtjjRCUY%2BMpNsPiobgn%2BQ%3D align="left")

4. Click **Continue**.
    

#### **Define the destination**

* Select the **bigquery-cp** connection profile created in the previous step, then click **Continue**.
    

![step 4 of the create stream page with bigquery-cp selected](https://cdn.qwiklabs.com/1SuvlVgaBoYruXirg1VIuvb0InSorFEnuZNBxu0D6yA%3D align="left")

#### **Configure the destination**

1. Choose Region and select `us-east4` as the BigQuery dataset location.
    
2. Set the staleness limit to **0 seconds**.
    

![step 5 of the create stream page with location selected ](https://cdn.qwiklabs.com/t%2FE1dGztk%2FYCGKlUSM6ryNGNs6PkiRzrvE6AbIqLHnk%3D align="left")

3. Click **Continue**.
    

#### **Review and create the stream**

* Finally, validate the stream details by clicking **RUN VALIDATION**. Once validation completes successfully, click **CREATE AND START**.
    

![validation results with green check marks](https://cdn.qwiklabs.com/1DMCDHlhunfH8fHMksbHA5F%2FKZZ9B3Nw%2FjWo59Kql8c%3D align="left")

Wait approximately 1-2 minutes until the stream status is shown as running.

Click **Check my progress** to verify the objective.

Create the Datastream resources

Check my progress

## **Task 3. View the data in BigQuery**

Now that the stream is running, see the data replicating into the BigQuery dataset.

1. In the Google Cloud console, from the **Navigation menu** go to **BigQuery**.
    
2. In the BigQuery Studio explorer, expand the project node to see the list of datasets.
    
3. Expand the **test** dataset node.
    
4. Click on the **example\_table** table.
    
5. Click on the **PREVIEW** tab to see the data in BigQuery.
    

**Note**: The data might take few minutes to appear in **Preview** section.

![BigQuery Explorer page with the example_table visible](https://cdn.qwiklabs.com/%2BqmRJAi4IaaSwz1Iaut6uh46BVBjvzqQP9BVhuZDScs%3D align="left")

## **Task 4. Check that changes in the source are replicated to BigQuery**

1. Run the following command in Cloud Shell to connect to the Cloud SQL database (the password is `pwd`):
    

```apache
gcloud sql connect postgres-db --user=postgres
```

2. Run the following SQL commands to make some changes to the data:
    

```apache
INSERT INTO test.example_table (text_col, int_col, date_col) VALUES
('abc', 0, '2022-10-01 00:00:00'),
('def', 1, NULL),
('ghi', -987, NOW());

UPDATE test.example_table SET int_col=int_col*2; 

DELETE FROM test.example_table WHERE text_col = 'abc';
```

3. Open the BigQuery SQL workspace and run the following query to see the changes in BigQuery:
    

```apache
SELECT * FROM test.example_table ORDER BY id;
```

![query results](https://cdn.qwiklabs.com/Q8Yg5AaUzkwUTlyEkj0m34yv5hmnUbo08m1oOETDZiA%3D align="left")

---

## **Solution of Lab**

%[https://youtu.be/GVl2jfB7DKA] 

```apache
export DATASTREAM_IPS=
```

![](https://cdn.hashnode.com/res/hashnode/image/upload/v1730976390640/60156279-2689-4fcc-95c7-54262ebc3cb2.png align="center")

```apache
curl -LO raw.githubusercontent.com/QUICK-GCP-LAB/2-Minutes-Labs-Solutions/refs/heads/main/Datastream%20PostgreSQL%20Replication%20to%20BigQuery/gsp1052-1.sh
sudo chmod +x gsp1052-1.sh
./gsp1052-1.sh
```

* When prompted for the password, paste the following.
    

```apache
pwd
```

```sql
CREATE SCHEMA IF NOT EXISTS test;

CREATE TABLE IF NOT EXISTS test.example_table (
id  SERIAL PRIMARY KEY,
text_col VARCHAR(50),
int_col INT,
date_col TIMESTAMP
);

ALTER TABLE test.example_table REPLICA IDENTITY DEFAULT; 

INSERT INTO test.example_table (text_col, int_col, date_col) VALUES
('hello', 0, '2020-01-01 00:00:00'),
('goodbye', 1, NULL),
('name', -987, NOW()),
('other', 2786, '2021-01-01 00:00:00');

CREATE PUBLICATION test_publication FOR ALL TABLES;
ALTER USER POSTGRES WITH REPLICATION;
SELECT PG_CREATE_LOGICAL_REPLICATION_SLOT('test_replication', 'pgoutput');
```

```apache
exit
```

```apache
curl -LO raw.githubusercontent.com/QUICK-GCP-LAB/2-Minutes-Labs-Solutions/refs/heads/main/Datastream%20PostgreSQL%20Replication%20to%20BigQuery/gsp1052-2.sh
sudo chmod +x gsp1052-2.sh
./gsp1052-2.sh
```

* ![](https://cdn.hashnode.com/res/hashnode/image/upload/v1730976940081/af951bea-a61c-4796-b103-bbf61e4f778c.png align="center")
    
    Use **postgres-cp** as the name and ID of the connection profile.
    

| Field | Value |
| --- | --- |
| Username | **postgres** |
| Password | **pwd** |
| Database | **postgres** |

* Use **bigquery-cp** as the name and ID of the connection profile.
    
* Use **test-stream** as the name and ID of the stream
    
* Specify the replication slot name as **test\_replication**
    
* Specify the publication name as **test\_publication**