<a id="flink-sql-example-data"></a>

# Example Data Streams in Confluent Cloud for Apache Flink

Confluent Cloud for Apache Flink® provides an Examples catalog that has mock data streams you can
use for experimenting with Flink SQL queries.

- The `examples` catalog is available in all environments.
- All example tables have `$rowtime` available as a system column. The
  `SOURCE_WATERMARK()` strategy for example tables is different than the
  `SOURCE_WATERMARK()` strategy for Kafka-based tables. For the example tables, the
  `SOURCE_WATERMARK()` corresponds to the maximum timestamp seen to this point.
- You can use example data in Flink workspaces, Flink shell, Terraform, and
  all other clients.
- Example data is read-only, so you can’t use INSERT INTO/ALTER/DROP/CREATE
  statements on these tables, the database, or the catalog.
- SHOW statements work for the database, catalog, and tables.
- SHOW CREATE TABLE works for the example tables.

## Publish to a Kafka topic

You can publish any of the example streams to a Kafka topic by creating a Flink
table and populating it with the
[INSERT INTO FROM SELECT](queries/insert-into-from-select.md#flink-sql-insert-into-from-select-statement)
statement. Confluent Cloud for Apache Flink creates a Kafka topic automatically for the table.

1. Run the following statements to create and populate a
   `customers_source` table with the `examples.marketplace.customers`
   stream.
   ```sql
   CREATE TABLE customers_source (
     customer_id INT,
     name STRING,
     address STRING,
     postcode STRING,
     city STRING,
     email STRING,
     PRIMARY KEY (customer_id) NOT ENFORCED
   );

   INSERT INTO customers_source(
     customer_id,
     name,
     address,
     postcode,
     city,
     email
   )
   SELECT * FROM examples.marketplace.customers;
   ```
2. Run the following statement to inspect the `customers_source` table:
   ```sql
   SELECT * FROM customers_source;
   ```

   Your output should resemble:
   ```none
   customer_id name                  address                postcode city               email
   3172        Roseanna Bode         6744 Kacy Bypass       22635    Margarettborough   rico.zboncak@yahoo.com
   3055        Josiah Morissette PhD 61799 Friesen Islands  14194    North Abbybury     thomas.dach@gmail.com
   3177        Buddy Hill            6836 Graham Street     72767    South Earnest      enoch.turcotte@hotmail.com
   ...
   ```
3. Navigate to the [Environments](https://confluent.cloud/environments) page,
   and in the navigation menu, click **Data portal**.
4. In the **Data portal** page, click the dropdown menu and select the
   environment for your workspace.
5. In the **Recently created** section, find your **customers_source** topic
   and click it to open the details pane.
6. Click **View all messages** to open the **Message viewer** on the
   `customers_source` topic.
7. Observe the example data from the `examples.marketplace.customers` flowing
   into the Kafka topic.

#### IMPORTANT
The INSERT INTO statement runs continuously until you stop it manually.
Free resources in your compute pool by deleting the long-running statement
when you’re done.

<a id="flink-sql-example-data-marketplace-database"></a>

## Marketplace database

The `marketplace` database provides streams that simulate commerce-related
data. The `marketplace` database has these tables:

- [clicks](#flink-sql-example-data-marketplace-database-clicks):
  simulates a stream of user clicks on a web page.
- [customers](#flink-sql-example-data-marketplace-database-customers):
  simulates a stream of customers who order products.
- [orders](#flink-sql-example-data-marketplace-database-orders):
  simulates a stream of orders.
- [products](#flink-sql-example-data-marketplace-database-products):
  simulates a stream of products that a customer has ordered.

<a id="flink-sql-example-data-marketplace-database-clicks"></a>

### clicks table

To access the `clicks` example stream, use the fully qualified string,
`examples.marketplace.clicks` in your queries.

The `clicks` table has the following schema:

```sql
CREATE TABLE clicks (
  click_id STRING, -- UUID
  user_id INT, -- range between 3000 and 5000
  url STRING, -- regex https://www[.]acme[.]com/product/[a-z]{5}
  user_agent STRING, -- set by the datafaker Internet class
  view_time INT -- range between 10 and 120
 );
```

The `user_agent` field is assigned by the
[datafaker Internet class](https://javadoc.io/doc/net.datafaker/datafaker/latest/net.datafaker/net/datafaker/providers/base/Internet.html).

Run the following statement to inspect the `clicks` data stream:

```sql
SELECT * FROM examples.marketplace.clicks;
```

Your output should resemble:

```none
click_id                             user_id url                                user_agent                                                           view_time
23add2ce-da47-47c1-925a-f7c1def06f0c 3278    https://www.acme.com/product/mqwpg Mozilla/5.0 (Windows NT 6.1; WOW64; Trident/7.0; AS; rv:11.0) like … 11
b81dc020-5ad2-493f-8175-d3e50e40f411 4919    https://www.acme.com/product/vycnj Mozilla/5.0 (Windows NT 6.1) AppleWebKit/537.36 (KHTML, like Gecko)… 58
b62ae975-0f5d-4e87-9cbe-45b7661ad327 3461    https://www.acme.com/product/pghkm Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML… 105
...
```

<a id="flink-sql-example-data-marketplace-database-customers"></a>

### customers table

To access the `customers` example stream, use the fully qualified string,
`examples.marketplace.customers` in your queries.

The `customers` table has the following schema:

```sql
CREATE TABLE customers (
  customer_id INT, -- range between 3000 and 3250
  name STRING, -- set by the datafaker Name class
  address STRING, -- set by the datafaker Address class
  postcode STRING, -- set by the datafaker Address class
  city STRING, -- set by the datafaker Address class
  email STRING, -- set by the datafaker Internet class
  PRIMARY KEY (customer_id) NOT ENFORCED
 );
```

- The `name` field is assigned by the
  [datafaker Name class](https://javadoc.io/static/net.datafaker/datafaker/2.1.0/net.datafaker/net/datafaker/providers/base/Name.html)
- The address fields are assigned by the
  [datafaker Address class](https://javadoc.io/static/net.datafaker/datafaker/2.1.0/net.datafaker/net/datafaker/providers/base/Address.html).
- The `email` field is assigned by the
  [datafaker Internet class](https://javadoc.io/doc/net.datafaker/datafaker/latest/net.datafaker/net/datafaker/providers/base/Internet.html).

Run the following statement to inspect the `customers` data stream:

```sql
SELECT * FROM examples.marketplace.customers;
```

Your output should resemble:

```none
customer_id name                 address                postcode city               email
3023        Ellsworth Price      0644 Mara Drive        29407    Emilyhaven         sheldon.sipes@gmail.com
3003        Jayme Buckridge      320 Schumm Green       38752    Schowalterchester  johnsie.hane@yahoo.com
3010        Les Beier            7032 Gerda Road        66841    Deckowside         minnie.becker@hotmail.com
...
```

<a id="flink-sql-example-data-marketplace-database-orders"></a>

### orders table

To access the `orders` example stream, use the fully qualified string,
`examples.marketplace.orders` in your queries.

The `customer_id` and `product_id` are suitable for joins with the
`customers` and `products` streams.

```sql
CREATE TABLE orders (
  order_id STRING, -- UUID
  customer_id INT, -- range between 3000 and 3250
  product_id INT, -- range between 1000 and 1500
  price DOUBLE -- range between 0.00 and 100.00
);
```

Run the following statement to inspect the `orders` data stream:

```sql
SELECT * FROM examples.marketplace.orders;
```

Your output should resemble:

```none
order_id                             customer_id product_id price
36d77b21-e68f-4123-b87a-cc19ac1f36ac 3137        1305       65.71
7fd3cd2a-392b-4f8f-b953-0bfa1d331354 3063        1327       17.75
1a223c61-38a5-4b8c-8465-2a6b359bf05e 3064        1166       14.95
...
```

Run the following statement to join the `orders` data stream with the
`customers` and `products` streams. The query shows the name of the
customer, and the product name, and the price of the order.

```sql
SELECT
  examples.marketplace.customers.name AS customer_name,
  examples.marketplace.products.name AS product_name,
  examples.marketplace.orders.price
FROM examples.marketplace.products
JOIN examples.marketplace.orders ON examples.marketplace.products.product_id = examples.marketplace.orders.product_id
JOIN examples.marketplace.customers ON examples.marketplace.customers.customer_id = examples.marketplace.orders.customer_id;
```

Your output should resemble:

```none
customer_name       product_name              price
Mr. Lexie Collins   Fantastic Rubber Car      32.76
Lyle Spencer        Synergistic Leather Clock 21.28
Mrs. Candida Howe   Lightweight Silk Hat      35.38
Colette Ebert       Sleek Steel Keyboard      92.22
```

<a id="flink-sql-example-data-marketplace-database-products"></a>

### products table

To access the `products` example stream, use the fully qualified string,
`examples.marketplace.products` in your queries.

```sql
CREATE TABLE products (
  product_id INT, -- range between 1000 and 1500
  name STRING, -- set by the datafaker Commerce class
  brand STRING, -- set by the datafaker Commerce class
  vendor STRING, -- set by the datafaker Commerce class
  department STRING, -- set by the datafaker Commerce class
  PRIMARY KEY (product_id) NOT ENFORCED
 );
```

The product fields are assigned by the
[datafaker Commerce class](https://javadoc.io/static/net.datafaker/datafaker/2.1.0/net.datafaker/net/datafaker/providers/base/Commerce.html).

Run the following statement to inspect the `products` data stream:

```sql
SELECT * FROM examples.marketplace.products;
```

Your output should resemble:

```none
product_id name                        brand   vendor         department
1440       Enormous Aluminum Keyboard  LG      Dollar General Garden & Movies
1404       Practical Plastic Computer  Adidas  Target         Outdoors
1132       Gorgeous Paper Watch        Samsung Amazon         Home, Kids & Movies
...
```

## Related content

- [DDL Statements](../concepts/statements.md#flink-sql-statements)
- [Flink SQL Queries](queries/overview.md#flink-sql-queries)

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This website includes content developed at the [Apache Software Foundation](https://www.apache.org/)
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