Skip to content
Branch: master
Find file History

Latest commit

Fetching latest commit…
Cannot retrieve the latest commit at this time.

Files

Permalink
Type Name Latest commit message Commit time
..
Failed to load latest commit information.
src
README.md
build.gradle
gradle.properties

README.md

Kafka Connect Connector

From the Confluent documentation:

Kafka Connect, an open source component of Kafka, is a framework for connecting Kafka with external systems such as databases, key-value stores, search indexes, and file systems. Using Kafka Connect you can use existing connector implementations for common data sources and sinks to move data into and out of Kafka.

Take an existing Kafka Connect source and use it as a source for Hazelcast Jet without the need to have a Kafka deployment. Hazelcast Jet will drive the Kafka Connect connector and bring the data from external systems to the pipeline directly.

Connector Attributes

Source Attributes

Atrribute Value
Has Source Yes
Batch Yes
Stream Yes
Distributed No

Sink Attributes

Atrribute Value
Has Sink No
Distributed No

Getting Started

Installing

The Kafka Connect Connector artifacts are published on the Maven repositories.

Add the following lines to your pom.xml to include it as a dependency to your project:

<dependency>
    <groupId>com.hazelcast.jet.contrib</groupId>
    <artifactId>kafka-connect</artifactId>
    <version>${version}</version>
</dependency>

or if you are using Gradle:

compile group: 'com.hazelcast.jet.contrib', name: 'kafka-connect', version: ${version}

Usage

To use any Kafka Connect Connector as a source in your pipeline you need to create a source by calling KafkaConnectSources.connect() method with the Properties object. After that you can use your pipeline like any other source in the Jet pipeline. The source will emit items in SourceRecord type from Kafka Connect API, where you can access the key and value along with their corresponding schemas. Hazelcast Jet will instantiate a single task for the specified source in the cluster.

Following is an example pipeline which stream events from RabbitMQ, maps the values to their string representation and logs them.

Beware the fact that you'll need to attach the Kafka Connect Connector of your choice with the job that you are submitting.

Properties properties = new Properties();
properties.setProperty("name", "rabbitmq-source-connector");
properties.setProperty("connector.class", "com.github.jcustenborder.kafka.connect.rabbitmq.RabbitMQSourceConnector");
properties.setProperty("kafka.topic", "messages");
properties.setProperty("rabbitmq.queue", "test-queue");
properties.setProperty("rabbitmq.host", "???");
properties.setProperty("rabbitmq.port", "???");
properties.setProperty("rabbitmq.username", "???");
properties.setProperty("rabbitmq.password", "???");

Pipeline pipeline = Pipeline.create();
pipeline.readFrom(KafkaConnectSources.connect(properties))
        .withoutTimestamps()
        .map(record -> Values.convertToString(record.valueSchema(), record.value()))
        .writeTo(Sinks.logger());

JobConfig jobConfig = new JobConfig();
jobConfig.addJarsInZip("/path/to/kafka-connect-rabbitmq-0.0.2-SNAPSHOT.zip");

Job job = createJetMember().newJob(pipeline, jobConfig);
job.join();

The pipeline will output records like the following:

INFO: [127.0.0.1]:5701 [jet] [4.0-SNAPSHOT] Output to ordinal 0: 
{
   "consumerTag":"amq.ctag-06l2oPQOnzjaGlAocCTzwg",
   "envelope":{
      "deliveryTag":100,
      "isRedeliver":false,
      "exchange":"ex",
      "routingKey":"test"
   },
   "basicProperties":{
      "contentType":"text/plain",
      "contentEncoding":"UTF-8",
      "headers":{

      },
      "deliveryMode":null,
      "priority":null,
      "correlationId":null,
      "replyTo":null,
      "expiration":null,
      "messageId":null,
      "timestamp":null,
      "type":null,
      "userId":"guest",
      "appId":null
   },
   "body":"Hello World!"
}

P.S. The record has been pretty printed for clarity.

Fault-Tolerance

The Kafka Connect connectors driven by Jet are participating to store their state snapshots (e.g partition offsets + any metadata which they might have to recover/restart) in Jet. This way when the job is restarted they can recover their state and continue to consume from where they left off. Since implementations may vary between Kafka Connect modules, each will have different behaviors when there is a failure. Please refer to the documentation of Kafka Connect connector of your choice for detailed information.

Running the tests

To run the tests run the command below:

./gradlew test

Authors

You can’t perform that action at this time.