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Publishing Avro Events via Kafka


This application demonstrates how to configure WSO2 Streaming Integrator Tooling to send sweet production events via the Kafka transport in Avro format using Confluent Schema Registry.


  1. To install Kafka, follow the steps below:

    1. In Streaming Integrator Tooling, click Tools, and then click Extension Installer.

    2. In the Extension Installer dialog box that opens, search for Kafka. Then click Install in the row that appears. A message appears to confirm whether you want to proceed to install the extension. Click Install.

    3. Restart Streaming Integrator Tooling.

  2. Download confluent-5.2.1 from the Confluent website. Then unzip the file you downloaded.


    Download the product Confluent PLatform. For this sample, the deployment type selected was Manual.

  3. Save the sample PublishKafkaInAvroFormatUsingSchemaRegistry Siddhi application.

    If there is no syntax error, the following message is logged in the terminal.

    * -Siddhi App PublishKafkaInAvroFormatUsingSchemaRegistry successfully deployed.

Executing the Sample:

To execute the sample, follow the steps below:

  1. First, start a zoo keeper node. To do this, navigate to the <KAFKA_HOME> directory and issue the following command.

    sh bin/ config/

  2. Next, start a Kafka server node. To do this, issue the following command from the same directory.

    sh bin/ config/

  3. Start the schema registry node by navigating to the <CONFLUENT_HOME> directory and issuing the following command:

    sh bin/schema-registry-start ./etc/schema-registry/

    This starts the Confluent client in localhost:8081 port.

  4. Post the avro schema to the schema registry by issuing the following CURL command.

    curl -X POST -H "Content-Type: application/json" --data '{ "schema": "{ \"type\": \"record\", \"name\": \"sweetProduction\",\"namespace\": \"sweetProduction\", \"fields\":[{ \"name\": \"name\", \"type\": \"string\" },{ \"name\": \"amount\", \"type\": \"double\" }]}"}' http://localhost:8081/subjects/sweet-production/versions

The sample Siddhi application specifies http://localhost:8081/subjects/sweet-production/versions as the URI of the schema registry. The above CURL command defines the Avro schema and posts it to this schema registry so that the schema is applied to the output events generated in the LowProductionAlertStream when they are published to the kafka_result_topic kafka topic.

For more information about how to configure an Avro mapper, see Siddhi Documentation - Avro Sink Mapper

  1. Navigate to the <SI_TOOLING_HOME>/samples/sample-clients/kafka-avro-consumer directory and run the ant command without arguments.

  2. Start the PublishKafkaInAvroFormatUsingSchemaRegistry Siddhi application you saved by opening it in Streaming Integrator Tooling and clicking the Start button in the toolbar.

    If the Siddhi application starts successfully, the following messages are logged in the terminal:

    • PublishKafkaInAvroFormatUsingSchemaRegistry.siddhi - Started Successfully!

    • Kafka version : 2.2.0

    • Kafka commitId : 05fcfde8f69b0349

    • Kafka producer created.

Testing the Sample:

To test this sample, send events following one or more of the methods given below:

Option 1 - Send events to the kafka sink via the Event Simulator:

  1. In Streaming Integrator Studio, open the Event Simulator by clicking on the Event Simulator icon in the left panel or pressing Ctrl+Shift+I.

  2. In the Single Simulation tab of the panel, specify the values as follows:

    Field Value
    Siddhi App Name PublishKafkaInAvroFormatUsingSchemaRegistry
    Stream Name SweetProductionStream
  3. Once you select the stream, the name and amount fields appear. Enter chocolate cake as the name and 50.50 as the value. Then click Send to send the event.

  4. Simulate a few more events for the SweetProductionStream stream by repeating the above steps.

Option 2 - Publish events with Curl to the simulator HTTP endpoint:

  1. Open a new terminal and issue the following command:

    curl -X POST -d '{"streamName": "SweetProductionStream", "siddhiAppName": "PublishKafkaInAvroFormatUsingSchemaRegistry","data": ["chocolate cake", 50.50]}' http://localhost:9390/simulation/single -H 'content-type: text/plain'

    When the message is successfully sent, the following message is logged in the terminal:

    "status":"OK","message":"Single Event simulation started successfully"

Option 3 - Publish events with Postman to the simulator HTTP endpoint:

  1. Install the Postman application from the Chrome web store.

  2. Launch the Postman application.

  3. Make a 'Post' request to the 'http://localhost:9390/simulation/single' endpoint. Set the Content-Type to text/plain and set the request body in text as follows:

    {"streamName": "SweetProductionStream", "siddhiAppName": "PublishKafkaInAvroFormatUsingSchemaRegistry","data": ['chocolate cake', 50.50]}

  4. Click send. When the message is successfully sent, the following messages are logged in the terminal.

    • "status": "OK",
    • "message": "Single Event simulation started successfully"

Viewing the Results:

You can view the following output in the terminal in which you ran the ant build for <SI_HOME>/samples/sample-clients/kafka-avro-consumer.

[java] [] : Event received in Kafka Event Adaptor with offSet: 2, key: null, topic: kafka_result_topic, partition: 0
[java] [] : KafkaSample : logStream : Event{timestamp=1546973831995, data=[chocolate cake, 50.5], isExpired=false}


If the message 'Kafka' sink at 'LowProductionAlertStream' has successfully connected to http://localhost:9092 does not appear, the reason can be that port 9092 defined in the Siddhi application is already being used by a different program. To resolve this issue, do as follows:

1. Stop the Siddhi application (i.e., by clicking the stop button for the Siddhi application in the top panel).

2. In the source configuration of the Siddhi application, change port 9092 to an unused port.

3. Start the Siddhi application and check whether the specified messages appear in the terminal.

The complete Siddhi application used in this sample is as follows:


@App:description('Send events via Kafka transport using Avro format')

define stream SweetProductionStream (name string, amount double);

define stream LowProductionAlertStream (name string, amount double);

from SweetProductionStream
select *
insert into LowProductionAlertStream;