Quickstart: Input & Output Bindings

Get started with Dapr’s Binding building block

Let’s take a look at Dapr’s Bindings building block. Using bindings, you can:

  • Trigger your app with events coming in from external systems.
  • Interface with external systems.

In this Quickstart, you will schedule a batch script to run every 10 seconds using an input Cron binding. The script processes a JSON file and outputs data to a SQL database using the PostgreSQL Dapr binding.

Bindings - 图1

Select your preferred language-specific Dapr SDK before proceeding with the Quickstart.

Pre-requisites

For this example, you will need:

Step 1: Set up the environment

Clone the sample provided in the Quickstarts repo.

  1. git clone https://github.com/dapr/quickstarts.git

Step 2: Run PostgreSQL Docker container locally

Run the PostgreSQL instance locally in a Docker container on your machine. The Quickstart sample includes a Docker Compose file to locally customize, build, run, and initialize the postgres container with a default orders table.

In a terminal window, from the root of the Quickstarts clone directory, navigate to the bindings/db directory.

  1. cd quickstarts/bindings/db

Run the following command to set up the container:

  1. docker compose up

Verify that the container is running locally.

  1. docker ps

The output should include:

  1. CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
  2. 55305d1d378b postgres "docker-entrypoint.s…" 3 seconds ago Up 2 seconds 0.0.0.0:5432->5432/tcp sql_db

Step 3: Schedule a Cron job and write to the database

In a new terminal window, navigate to the SDK directory.

  1. cd quickstarts/bindings/python/sdk/batch

Install the dependencies:

  1. pip3 install -r requirements.txt

Run the batch-sdk service alongside a Dapr sidecar.

  1. dapr run --app-id batch-sdk --app-port 50051 --components-path ../../../components -- python3 app.py

Note: Since Python3.exe is not defined in Windows, you may need to use python app.py instead of python3 app.py.

The code inside the process_batch function is executed every 10 seconds (defined in binding-cron.yaml in the components directory). The binding trigger looks for a route called via HTTP POST in your Flask application by the Dapr sidecar.

  1. # Triggered by Dapr input binding
  2. @app.route('/' + cron_binding_name, methods=['POST'])
  3. def process_batch():

The batch-sdk service uses the PostgreSQL output binding defined in the binding-postgres.yaml component to insert the OrderId, Customer, and Price records into the orders table.

  1. with DaprClient() as d:
  2. sqlCmd = ('insert into orders (orderid, customer, price) values ' +
  3. '(%s, \'%s\', %s)' % (order_line['orderid'],
  4. order_line['customer'],
  5. order_line['price']))
  6. payload = {'sql': sqlCmd}
  7. print(sqlCmd, flush=True)
  8. try:
  9. # Insert order using Dapr output binding via HTTP Post
  10. resp = d.invoke_binding(binding_name=sql_binding, operation='exec',
  11. binding_metadata=payload, data='')
  12. return resp
  13. except Exception as e:
  14. print(e, flush=True)
  15. raise SystemExit(e)

Step 4: View the output of the job

Notice, as specified above, the code invokes the output binding with the OrderId, Customer, and Price as a payload.

Your output binding’s print statement output:

  1. == APP == Processing batch..
  2. == APP == insert into orders (orderid, customer, price) values (1, 'John Smith', 100.32)
  3. == APP == insert into orders (orderid, customer, price) values (2, 'Jane Bond', 15.4)
  4. == APP == insert into orders (orderid, customer, price) values (3, 'Tony James', 35.56)
  5. == APP == Finished processing batch

In a new terminal, verify the same data has been inserted into the database. Navigate to the bindings/db directory.

  1. cd quickstarts/bindings/db

Run the following to start the interactive Postgres CLI:

  1. docker exec -i -t postgres psql --username postgres -p 5432 -h localhost --no-password

At the admin=# prompt, change to the orders table:

  1. \c orders;

At the orders=# prompt, select all rows:

  1. select * from orders;

The output should look like this:

  1. orderid | customer | price
  2. ---------+------------+--------
  3. 1 | John Smith | 100.32
  4. 2 | Jane Bond | 15.4
  5. 3 | Tony James | 35.56

components\binding-cron.yaml component file

When you execute the dapr run command and specify the component path, the Dapr sidecar:

The Cron binding-cron.yaml file included for this Quickstart contains the following:

  1. apiVersion: dapr.io/v1alpha1
  2. kind: Component
  3. metadata:
  4. name: cron
  5. namespace: quickstarts
  6. spec:
  7. type: bindings.cron
  8. version: v1
  9. metadata:
  10. - name: schedule
  11. value: "@every 10s" # valid cron schedule

Note: The metadata section of binding-cron.yaml contains a Cron expression that specifies how often the binding is invoked.

component\binding-postgres.yaml component file

When you execute the dapr run command and specify the component path, the Dapr sidecar:

  • Initiates the PostgreSQL binding building block
  • Connects to PostgreSQL using the settings specified in the binding-postgres.yaml file

With the binding-postgres.yaml component, you can easily swap out the backend database binding without making code changes.

The PostgreSQL binding-postgres.yaml file included for this Quickstart contains the following:

  1. apiVersion: dapr.io/v1alpha1
  2. kind: Component
  3. metadata:
  4. name: sqldb
  5. namespace: quickstarts
  6. spec:
  7. type: bindings.postgres
  8. version: v1
  9. metadata:
  10. - name: url # Required
  11. value: "user=postgres password=docker host=localhost port=5432 dbname=orders pool_min_conns=1 pool_max_conns=10"

In the YAML file:

  • spec/type specifies that PostgreSQL is used for this binding.
  • spec/metadata defines the connection to the PostgreSQL instance used by the component.

Pre-requisites

For this example, you will need:

Step 1: Set up the environment

Clone the sample provided in the Quickstarts repo.

  1. git clone https://github.com/dapr/quickstarts.git

Step 2: Run PostgreSQL Docker container locally

Run the PostgreSQL instance locally in a Docker container on your machine. The Quickstart sample includes a Docker Compose file to locally customize, build, run, and initialize the postgres container with a default orders table.

In a terminal window, from the root of the Quickstarts clone directory, navigate to the bindings/db directory.

  1. cd quickstarts/bindings/db

Run the following command to set up the container:

  1. docker compose up

Verify that the container is running locally.

  1. docker ps

The output should include:

  1. CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
  2. 55305d1d378b postgres "docker-entrypoint.s…" 3 seconds ago Up 2 seconds 0.0.0.0:5432->5432/tcp sql_db

Step 3: Schedule a Cron job and write to the database

In a new terminal window, navigate to the SDK directory.

  1. cd quickstarts/bindings/javascript/sdk/batch

Install the dependencies:

  1. npm install

Run the batch-sdk service alongside a Dapr sidecar.

  1. dapr run --app-id batch-sdk --app-port 5002 --dapr-http-port 3500 --components-path ../../../components -- node index.js

The code inside the process_batch function is executed every 10 seconds (defined in binding-cron.yaml in the components directory). The binding trigger looks for a route called via HTTP POST in your Flask application by the Dapr sidecar.

  1. async function start() {
  2. await server.binding.receive(cronBindingName,processBatch);
  3. await server.start();
  4. }

The batch-sdk service uses the PostgreSQL output binding defined in the binding-postgres.yaml component to insert the OrderId, Customer, and Price records into the orders table.

  1. async function processBatch(){
  2. const loc = '../../orders.json';
  3. fs.readFile(loc, 'utf8', (err, data) => {
  4. const orders = JSON.parse(data).orders;
  5. orders.forEach(order => {
  6. let sqlCmd = `insert into orders (orderid, customer, price) values (${order.orderid}, '${order.customer}', ${order.price});`;
  7. let payload = `{ "sql": "${sqlCmd}" } `;
  8. console.log(payload);
  9. client.binding.send(postgresBindingName, "exec", "", JSON.parse(payload));
  10. });
  11. console.log('Finished processing batch');
  12. });
  13. return 0;
  14. }

Step 4: View the output of the job

Notice, as specified above, the code invokes the output binding with the OrderId, Customer, and Price as a payload.

Your output binding’s print statement output:

  1. == APP == Processing batch..
  2. == APP == insert into orders (orderid, customer, price) values(1, 'John Smith', 100.32)
  3. == APP == insert into orders (orderid, customer, price) values(2, 'Jane Bond', 15.4)
  4. == APP == insert into orders (orderid, customer, price) values(3, 'Tony James', 35.56)

In a new terminal, verify the same data has been inserted into the database. Navigate to the bindings/db directory.

  1. cd quickstarts/bindings/db

Run the following to start the interactive Postgres CLI:

  1. docker exec -i -t postgres psql --username postgres -p 5432 -h localhost --no-password

At the admin=# prompt, change to the orders table:

  1. \c orders;

At the orders=# prompt, select all rows:

  1. select * from orders;

The output should look like this:

  1. orderid | customer | price
  2. ---------+------------+--------
  3. 1 | John Smith | 100.32
  4. 2 | Jane Bond | 15.4
  5. 3 | Tony James | 35.56

components\binding-cron.yaml component file

When you execute the dapr run command and specify the component path, the Dapr sidecar:

The Cron binding-cron.yaml file included for this Quickstart contains the following:

  1. apiVersion: dapr.io/v1alpha1
  2. kind: Component
  3. metadata:
  4. name: cron
  5. namespace: quickstarts
  6. spec:
  7. type: bindings.cron
  8. version: v1
  9. metadata:
  10. - name: schedule
  11. value: "@every 10s" # valid cron schedule

Note: The metadata section of binding-cron.yaml contains a Cron expression that specifies how often the binding is invoked.

component\binding-postgres.yaml component file

When you execute the dapr run command and specify the component path, the Dapr sidecar:

  • Initiates the PostgreSQL binding building block
  • Connects to PostgreSQL using the settings specified in the binding-postgres.yaml file

With the binding-postgres.yaml component, you can easily swap out the backend database binding without making code changes.

The PostgreSQL binding-postgres.yaml file included for this Quickstart contains the following:

  1. apiVersion: dapr.io/v1alpha1
  2. kind: Component
  3. metadata:
  4. name: sqldb
  5. namespace: quickstarts
  6. spec:
  7. type: bindings.postgres
  8. version: v1
  9. metadata:
  10. - name: url # Required
  11. value: "user=postgres password=docker host=localhost port=5432 dbname=orders pool_min_conns=1 pool_max_conns=10"

In the YAML file:

  • spec/type specifies that PostgreSQL is used for this binding.
  • spec/metadata defines the connection to the PostgreSQL instance used by the component.

Pre-requisites

For this example, you will need:

Step 1: Set up the environment

Clone the sample provided in the Quickstarts repo.

  1. git clone https://github.com/dapr/quickstarts.git

Step 2: Run PostgreSQL Docker container locally

Run the PostgreSQL instance locally in a Docker container on your machine. The Quickstart sample includes a Docker Compose file to locally customize, build, run, and initialize the postgres container with a default orders table.

In a terminal window, from the root of the Quickstarts clone directory, navigate to the bindings/db directory.

  1. cd quickstarts/bindings/db

Run the following command to set up the container:

  1. docker compose up

Verify that the container is running locally.

  1. docker ps

The output should include:

  1. CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
  2. 55305d1d378b postgres "docker-entrypoint.s…" 3 seconds ago Up 2 seconds 0.0.0.0:5432->5432/tcp sql_db

Step 3: Schedule a Cron job and write to the database

In a new terminal window, navigate to the SDK directory.

  1. cd quickstarts/bindings/csharp/sdk/batch

Install the dependencies:

  1. dotnet restore
  2. dotnet build batch.csproj

Run the batch-sdk service alongside a Dapr sidecar.

  1. dapr run --app-id batch-sdk --app-port 7002 --components-path ../../../components -- dotnet run

The code inside the process_batch function is executed every 10 seconds (defined in binding-cron.yaml in the components directory). The binding trigger looks for a route called via HTTP POST in your Flask application by the Dapr sidecar.

  1. app.MapPost("/" + cronBindingName, async () => {
  2. // ...
  3. });

The batch-sdk service uses the PostgreSQL output binding defined in the binding-postgres.yaml component to insert the OrderId, Customer, and Price records into the orders table.

  1. // ...
  2. string jsonFile = File.ReadAllText("../../../orders.json");
  3. var ordersArray = JsonSerializer.Deserialize<Orders>(jsonFile);
  4. using var client = new DaprClientBuilder().Build();
  5. foreach(Order ord in ordersArray?.orders ?? new Order[] {}){
  6. var sqlText = $"insert into orders (orderid, customer, price) values ({ord.OrderId}, '{ord.Customer}', {ord.Price});";
  7. var command = new Dictionary<string,string>(){
  8. {"sql",
  9. sqlText}
  10. };
  11. // ...
  12. }
  13. // Insert order using Dapr output binding via Dapr Client SDK
  14. await client.InvokeBindingAsync(bindingName: sqlBindingName, operation: "exec", data: "", metadata: command);

Step 4: View the output of the job

Notice, as specified above, the code invokes the output binding with the OrderId, Customer, and Price as a payload.

Your output binding’s print statement output:

  1. == APP == Processing batch..
  2. == APP == insert into orders (orderid, customer, price) values (1, 'John Smith', 100.32);
  3. == APP == insert into orders (orderid, customer, price) values (2, 'Jane Bond', 15.4);
  4. == APP == insert into orders (orderid, customer, price) values (3, 'Tony James', 35.56);
  5. == APP == Finished processing batch

In a new terminal, verify the same data has been inserted into the database. Navigate to the bindings/db directory.

  1. cd quickstarts/bindings/db

Run the following to start the interactive Postgres CLI:

  1. docker exec -i -t postgres psql --username postgres -p 5432 -h localhost --no-password

At the admin=# prompt, change to the orders table:

  1. \c orders;

At the orders=# prompt, select all rows:

  1. select * from orders;

The output should look like this:

  1. orderid | customer | price
  2. ---------+------------+--------
  3. 1 | John Smith | 100.32
  4. 2 | Jane Bond | 15.4
  5. 3 | Tony James | 35.56

components\binding-cron.yaml component file

When you execute the dapr run command and specify the component path, the Dapr sidecar:

The Cron binding-cron.yaml file included for this Quickstart contains the following:

  1. apiVersion: dapr.io/v1alpha1
  2. kind: Component
  3. metadata:
  4. name: cron
  5. namespace: quickstarts
  6. spec:
  7. type: bindings.cron
  8. version: v1
  9. metadata:
  10. - name: schedule
  11. value: "@every 10s" # valid cron schedule

Note: The metadata section of binding-cron.yaml contains a Cron expression that specifies how often the binding is invoked.

component\binding-postgres.yaml component file

When you execute the dapr run command and specify the component path, the Dapr sidecar:

  • Initiates the PostgreSQL binding building block
  • Connects to PostgreSQL using the settings specified in the binding-postgres.yaml file

With the binding-postgres.yaml component, you can easily swap out the backend database binding without making code changes.

The PostgreSQL binding-postgres.yaml file included for this Quickstart contains the following:

  1. apiVersion: dapr.io/v1alpha1
  2. kind: Component
  3. metadata:
  4. name: sqldb
  5. namespace: quickstarts
  6. spec:
  7. type: bindings.postgres
  8. version: v1
  9. metadata:
  10. - name: url # Required
  11. value: "user=postgres password=docker host=localhost port=5432 dbname=orders pool_min_conns=1 pool_max_conns=10"

In the YAML file:

  • spec/type specifies that PostgreSQL is used for this binding.
  • spec/metadata defines the connection to the PostgreSQL instance used by the component.

Pre-requisites

For this example, you will need:

Step 1: Set up the environment

Clone the sample provided in the Quickstarts repo.

  1. git clone https://github.com/dapr/quickstarts.git

Step 2: Run PostgreSQL Docker container locally

Run the PostgreSQL instance locally in a Docker container on your machine. The Quickstart sample includes a Docker Compose file to locally customize, build, run, and initialize the postgres container with a default orders table.

In a terminal window, from the root of the Quickstarts clone directory, navigate to the bindings/db directory.

  1. cd quickstarts/bindings/db

Run the following command to set up the container:

  1. docker compose up

Verify that the container is running locally.

  1. docker ps

The output should include:

  1. CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
  2. 55305d1d378b postgres "docker-entrypoint.s…" 3 seconds ago Up 2 seconds 0.0.0.0:5432->5432/tcp sql_db

Step 3: Schedule a Cron job and write to the database

In a new terminal window, navigate to the SDK directory.

  1. cd quickstarts/bindings/java/sdk/batch

Install the dependencies:

  1. mvn clean install

Run the batch-sdk service alongside a Dapr sidecar.

  1. dapr run --app-id batch-sdk --app-port 8080 --components-path ../../../components -- java -jar target/BatchProcessingService-0.0.1-SNAPSHOT.jar

The code inside the process_batch function is executed every 10 seconds (defined in binding-cron.yaml in the components directory). The binding trigger looks for a route called via HTTP POST in your Flask application by the Dapr sidecar.

  1. @PostMapping(path = cronBindingPath, consumes = MediaType.ALL_VALUE)
  2. public ResponseEntity<String> processBatch() throws IOException, Exception

The batch-sdk service uses the PostgreSQL output binding defined in the binding-postgres.yaml component to insert the OrderId, Customer, and Price records into the orders table.

  1. try (DaprClient client = new DaprClientBuilder().build()) {
  2. for (Order order : ordList.orders) {
  3. String sqlText = String.format(
  4. "insert into orders (orderid, customer, price) " +
  5. "values (%s, '%s', %s);",
  6. order.orderid, order.customer, order.price);
  7. logger.info(sqlText);
  8. Map<String, String> metadata = new HashMap<String, String>();
  9. metadata.put("sql", sqlText);
  10. // Invoke sql output binding using Dapr SDK
  11. client.invokeBinding(sqlBindingName, "exec", null, metadata).block();
  12. }
  13. logger.info("Finished processing batch");
  14. return ResponseEntity.ok("Finished processing batch");
  15. }

Step 4: View the output of the job

Notice, as specified above, the code invokes the output binding with the OrderId, Customer, and Price as a payload.

Your output binding’s print statement output:

  1. == APP == 2022-06-22 16:39:17.012 INFO 35772 --- [nio-8080-exec-4] c.s.c.BatchProcessingServiceController : Processing batch..
  2. == APP == 2022-06-22 16:39:17.268 INFO 35772 --- [nio-8080-exec-4] c.s.c.BatchProcessingServiceController : insert into orders (orderid, customer, price) values (1, 'John Smith', 100.32);
  3. == APP == 2022-06-22 16:39:17.838 INFO 35772 --- [nio-8080-exec-4] c.s.c.BatchProcessingServiceController : insert into orders (orderid, customer, price) values (2, 'Jane Bond', 15.4);
  4. == APP == 2022-06-22 16:39:17.844 INFO 35772 --- [nio-8080-exec-4] c.s.c.BatchProcessingServiceController : insert into orders (orderid, customer, price) values (3, 'Tony James', 35.56);
  5. == APP == 2022-06-22 16:39:17.848 INFO 35772 --- [nio-8080-exec-4] c.s.c.BatchProcessingServiceController : Finished processing batch

In a new terminal, verify the same data has been inserted into the database. Navigate to the bindings/db directory.

  1. cd quickstarts/bindings/db

Run the following to start the interactive Postgres CLI:

  1. docker exec -i -t postgres psql --username postgres -p 5432 -h localhost --no-password

At the admin=# prompt, change to the orders table:

  1. \c orders;

At the orders=# prompt, select all rows:

  1. select * from orders;

The output should look like this:

  1. orderid | customer | price
  2. ---------+------------+--------
  3. 1 | John Smith | 100.32
  4. 2 | Jane Bond | 15.4
  5. 3 | Tony James | 35.56

components\binding-cron.yaml component file

When you execute the dapr run command and specify the component path, the Dapr sidecar:

The Cron binding-cron.yaml file included for this Quickstart contains the following:

  1. apiVersion: dapr.io/v1alpha1
  2. kind: Component
  3. metadata:
  4. name: cron
  5. namespace: quickstarts
  6. spec:
  7. type: bindings.cron
  8. version: v1
  9. metadata:
  10. - name: schedule
  11. value: "@every 10s" # valid cron schedule

Note: The metadata section of binding-cron.yaml contains a Cron expression that specifies how often the binding is invoked.

component\binding-postgres.yaml component file

When you execute the dapr run command and specify the component path, the Dapr sidecar:

  • Initiates the PostgreSQL binding building block
  • Connects to PostgreSQL using the settings specified in the binding-postgres.yaml file

With the binding-postgres.yaml component, you can easily swap out the backend database binding without making code changes.

The PostgreSQL binding-postgres.yaml file included for this Quickstart contains the following:

  1. apiVersion: dapr.io/v1alpha1
  2. kind: Component
  3. metadata:
  4. name: sqldb
  5. namespace: quickstarts
  6. spec:
  7. type: bindings.postgres
  8. version: v1
  9. metadata:
  10. - name: url # Required
  11. value: "user=postgres password=docker host=localhost port=5432 dbname=orders pool_min_conns=1 pool_max_conns=10"

In the YAML file:

  • spec/type specifies that PostgreSQL is used for this binding.
  • spec/metadata defines the connection to the PostgreSQL instance used by the component.

Pre-requisites

For this example, you will need:

Step 1: Set up the environment

Clone the sample provided in the Quickstarts repo.

  1. git clone https://github.com/dapr/quickstarts.git

Step 2: Run PostgreSQL Docker container locally

Run the PostgreSQL instance locally in a Docker container on your machine. The Quickstart sample includes a Docker Compose file to locally customize, build, run, and initialize the postgres container with a default orders table.

In a terminal window, from the root of the Quickstarts clone directory, navigate to the bindings/db directory.

  1. cd quickstarts/bindings/db

Run the following command to set up the container:

  1. docker compose up

Verify that the container is running locally.

  1. docker ps

The output should include:

  1. CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
  2. 55305d1d378b postgres "docker-entrypoint.s…" 3 seconds ago Up 2 seconds 0.0.0.0:5432->5432/tcp sql_db

Step 3: Schedule a Cron job and write to the database

In a new terminal window, navigate to the SDK directory.

  1. cd quickstarts/bindings/go/sdk/batch

Install the dependencies:

  1. go build .

Run the batch-sdk service alongside a Dapr sidecar.

  1. dapr run --app-id batch-sdk --app-port 6002 --dapr-http-port 3502 --dapr-grpc-port 60002 --components-path ../../../components -- go run .

The code inside the process_batch function is executed every 10 seconds (defined in binding-cron.yaml in the components directory). The binding trigger looks for a route called via HTTP POST in your Flask application by the Dapr sidecar.

  1. // Triggered by Dapr input binding
  2. r.HandleFunc("/"+cronBindingName, processBatch).Methods("POST")

The batch-sdk service uses the PostgreSQL output binding defined in the binding-postgres.yaml component to insert the OrderId, Customer, and Price records into the orders table.

  1. func sqlOutput(order Order) (err error) {
  2. client, err := dapr.NewClient()
  3. if err != nil {
  4. return err
  5. }
  6. ctx := context.Background()
  7. sqlCmd := fmt.Sprintf("insert into orders (orderid, customer, price) values (%d, '%s', %s);", order.OrderId, order.Customer, strconv.FormatFloat(order.Price, 'f', 2, 64))
  8. fmt.Println(sqlCmd)
  9. // Insert order using Dapr output binding via Dapr SDK
  10. in := &dapr.InvokeBindingRequest{
  11. Name: sqlBindingName,
  12. Operation: "exec",
  13. Data: []byte(""),
  14. Metadata: map[string]string{"sql": sqlCmd},
  15. }
  16. err = client.InvokeOutputBinding(ctx, in)
  17. if err != nil {
  18. return err
  19. }
  20. return nil
  21. }

Step 4: View the output of the job

Notice, as specified above, the code invokes the output binding with the OrderId, Customer, and Price as a payload.

Your output binding’s print statement output:

  1. == APP == Processing batch..
  2. == APP == insert into orders (orderid, customer, price) values(1, 'John Smith', 100.32)
  3. == APP == insert into orders (orderid, customer, price) values(2, 'Jane Bond', 15.4)
  4. == APP == insert into orders (orderid, customer, price) values(3, 'Tony James', 35.56)

In a new terminal, verify the same data has been inserted into the database. Navigate to the bindings/db directory.

  1. cd quickstarts/bindings/db

Run the following to start the interactive Postgres CLI:

  1. docker exec -i -t postgres psql --username postgres -p 5432 -h localhost --no-password

At the admin=# prompt, change to the orders table:

  1. \c orders;

At the orders=# prompt, select all rows:

  1. select * from orders;

The output should look like this:

  1. orderid | customer | price
  2. ---------+------------+--------
  3. 1 | John Smith | 100.32
  4. 2 | Jane Bond | 15.4
  5. 3 | Tony James | 35.56

components\binding-cron.yaml component file

When you execute the dapr run command and specify the component path, the Dapr sidecar:

The Cron binding-cron.yaml file included for this Quickstart contains the following:

  1. apiVersion: dapr.io/v1alpha1
  2. kind: Component
  3. metadata:
  4. name: cron
  5. namespace: quickstarts
  6. spec:
  7. type: bindings.cron
  8. version: v1
  9. metadata:
  10. - name: schedule
  11. value: "@every 10s" # valid cron schedule

Note: The metadata section of binding-cron.yaml contains a Cron expression that specifies how often the binding is invoked.

component\binding-postgres.yaml component file

When you execute the dapr run command and specify the component path, the Dapr sidecar:

  • Initiates the PostgreSQL binding building block
  • Connects to PostgreSQL using the settings specified in the binding-postgres.yaml file

With the binding-postgres.yaml component, you can easily swap out the backend database binding without making code changes.

The PostgreSQL binding-postgres.yaml file included for this Quickstart contains the following:

  1. apiVersion: dapr.io/v1alpha1
  2. kind: Component
  3. metadata:
  4. name: sqldb
  5. namespace: quickstarts
  6. spec:
  7. type: bindings.postgres
  8. version: v1
  9. metadata:
  10. - name: url # Required
  11. value: "user=postgres password=docker host=localhost port=5432 dbname=orders pool_min_conns=1 pool_max_conns=10"

In the YAML file:

  • spec/type specifies that PostgreSQL is used for this binding.
  • spec/metadata defines the connection to the PostgreSQL instance used by the component.

Tell us what you think!

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Next steps

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Last modified October 12, 2022: quickstarts code fix (#2877) (58811fae)