Replicator Tutorial

In this section, we provide a tutorial for running Replicator which replicates data from two source Kafka clusters to a destination Kafka cluster. By the end of this tutorial, you will have successfully run Replicator and replicated data for two topics from different source clusters to a destination cluster. Furthermore, you will have also set up a Kafka Connect cluster because Replicator is built on Connect.

It is worth noting that we will be configuring Kafka and Zookeeper to store data locally in the Docker containers. For deployments that require persistent data (e.g. production deployments), you should use mounted volumes for persisting data in the event that a container stops running or is restarted. This is important when running a system like Kafka on Docker, as it relies heavily on the filesystem for storing and caching messages. Refer to our documentation on Docker external volumes for an example of how to add mounted volumes to the host machine.

Installing & Running Docker

For this tutorial, we’ll run Docker using Docker Compose.

To get started, you will first need to install Docker and Docker Compose. The CP Docker Images require Docker version 1.11 or greater.

Once you’ve done that, you can follow the steps below to start up the Confluent Platform services.

  1. Create and configure the Docker Machine (OS X only).
docker-machine create --driver virtualbox --virtualbox-memory 6000 confluent

Next, configure your terminal window to attach it to your new Docker Machine:

eval $(docker-machine env confluent)
  1. Clone the CP Docker Images Github Repository.
git clone https://github.com/confluentinc/cp-docker-images

We have provided an example Docker Compose file that will start up 2 source Kafka clusters, one destination Kafka cluster and a Kafka Connect cluster. Navigate to cp-docker-images/examples/enterprise-replicator, where it is located:

  1. Start the Kafka and Kafka Connect clusters using Docker Compose create and start commands.
docker-compose create

You should see the following

Creating enterprisereplicator_kafka-1-src-b_1
Creating enterprisereplicator_kafka-1-src-a_1
Creating enterprisereplicator_kafka-2-dest_1
Creating enterprisereplicator_zookeeper-src-b_1
Creating enterprisereplicator_zookeeper-src-a_1
Creating enterprisereplicator_connect-host-1_1
Creating enterprisereplicator_kafka-2-src-a_1
Creating enterprisereplicator_kafka-2-src-b_1
Creating enterprisereplicator_kafka-1-dest_1
Creating enterprisereplicator_zookeeper-dest_1
Creating enterprisereplicator_connect-host-2_1

Start all the services

docker-compose start

You should see the following

Starting kafka-1-src-b ... done
Starting kafka-1-src-a ... done
Starting kafka-2-dest ... done
Starting zookeeper-src-b ... done
Starting zookeeper-src-a ... done
Starting connect-host-1 ... done
Starting kafka-2-src-a ... done
Starting kafka-2-src-b ... done
Starting kafka-1-dest ... done
Starting zookeeper-dest ... done
Starting connect-host-2 ... done

Before we move on, let’s make sure the services are up and running:

docker-compose ps

You should see the following:

  Name                             Command            State   Ports
----------------------------------------------------------------------------------
enterprisereplicator_connect-host-1_1    /etc/confluent/docker/run   Up
enterprisereplicator_connect-host-2_1    /etc/confluent/docker/run   Up
enterprisereplicator_kafka-1-dest_1      /etc/confluent/docker/run   Up
enterprisereplicator_kafka-1-src-a_1     /etc/confluent/docker/run   Up
enterprisereplicator_kafka-1-src-b_1     /etc/confluent/docker/run   Up
enterprisereplicator_kafka-2-dest_1      /etc/confluent/docker/run   Up
enterprisereplicator_kafka-2-src-a_1     /etc/confluent/docker/run   Up
enterprisereplicator_kafka-2-src-b_1     /etc/confluent/docker/run   Up
enterprisereplicator_zookeeper-dest_1    /etc/confluent/docker/run   Up
enterprisereplicator_zookeeper-src-a_1   /etc/confluent/docker/run   Up
enterprisereplicator_zookeeper-src-b_1   /etc/confluent/docker/run   Up

Now check the Zookeeper logs for destination cluster to verify that Zookeeper is healthy.

docker-compose logs zookeeper-dest | grep -i binding

You should see the following in your terminal window:

zookeeper-dest_1   | [2016-10-20 17:31:40,784] INFO binding to port 0.0.0.0/0.0.0.0:42181 (org.apache.zookeeper.server.NIOServerCnxnFactory)

Next, check the Kafka logs for the destination cluster to verify that it is healthy:

docker-compose logs kafka-1-dest | grep -i started

You should see message a message that looks like the following:

kafka-1-dest_1     | [2016-10-20 17:31:45,364] INFO [Socket Server on Broker 1002], Started 1 acceptor threads (kafka.network.SocketServer)
kafka-1-dest_1     | [2016-10-20 17:31:45,792] INFO [Kafka Server 1002], started (kafka.server.KafkaServer)
....

Similarly verify that the source-a and source-b Kafka clusters are ready by running the following commands and verifying the output as described in the steps above.

docker-compose logs zookeeper-src-a | grep -i binding
docker-compose logs zookeeper-src-b | grep -i binding
docker-compose logs kafka-1-src-a | grep -i started
docker-compose logs kafka-1-src-b | grep -i started

Now, let’s check to make sure that the Connect worker is up by running the following command to search the logs:

docker-compose logs connect-host-1 | grep started

You should see the following

connect-host-1_1   | [2016-10-20 17:31:48,942] INFO Kafka Connect started (org.apache.kafka.connect.runtime.Connect)
connect-host-1_1   | [2016-10-20 17:31:50,403] INFO Worker started (org.apache.kafka.connect.runtime.Worker)
connect-host-1_1   | [2016-10-20 17:31:50,988] INFO Herder started (org.apache.kafka.connect.runtime.distributed.DistributedHerder)
  1. We will now create our first Kafka Connect Replicator connector for replicating topic “foo” from source cluster source-a.

First, we’ll create a topic. We’ll name it foo.

docker run \
  --net=host \
  --rm confluentinc/cp-kafka:3.1.2 \
  kafka-topics --create --topic foo --partitions 3 --replication-factor 2 --if-not-exists --zookeeper localhost:22181

You should see the following output in your terminal window:

Created topic "foo".

Before moving on, verify that the topic was created successfully:

docker run \
  --net=host \
  --rm confluentinc/cp-kafka:3.1.2 \
  kafka-topics --describe --topic foo --zookeeper localhost:22181

You should see the following output in your terminal window:

Topic:foo           PartitionCount:3        ReplicationFactor:2     Configs:
Topic: foo          Partition: 0    Leader: 1002    Replicas: 1002,1001     Isr: 1002,1001
Topic: foo          Partition: 1    Leader: 1001    Replicas: 1001,1002     Isr: 1001,1002
Topic: foo          Partition: 2    Leader: 1002    Replicas: 1002,1001     Isr: 1002,1001
  1. Next, we’ll try generating some data to our new topic:
docker run \
  --net=host \
  --rm \
  confluentinc/cp-kafka:3.1.2 \
  bash -c "seq 1000 | kafka-console-producer --request-required-acks 1 --broker-list localhost:9092 --topic foo && echo 'Produced 1000 messages.'"

This command will use the built-in Kafka Console Producer to produce 100 simple messages to the topic. Upon running it, you should see the following:

Produced 1000 messages.
  1. Now create the connector using the Kafka Connect REST API. First, let’s exec into the Connect container.
docker-compose exec connect-host-1 bash

You should see a bash prompt now. We will call this the docker exec command prompt:

root@confluent:/#

The next step is to create the Replicator connector. Run the following command on the docker exec command prompt.

curl -X POST \
     -H "Content-Type: application/json" \
     --data '{
        "name": "replicator-src-a-foo",
        "config": {
          "connector.class":"io.confluent.connect.replicator.ReplicatorSourceConnector",
          "key.converter": "io.confluent.connect.replicator.util.ByteArrayConverter",
          "value.converter": "io.confluent.connect.replicator.util.ByteArrayConverter",
          "src.zookeeper.connect": "localhost:22181",
          "src.kafka.bootstrap.servers": "localhost:9092",
          "dest.zookeeper.connect": "localhost:42181",
          "topic.whitelist": "foo",
          "topic.rename.format": "${topic}.replica"}}'  \
     http://localhost:28082/connectors

Upon running the command, you should see the following output in your docker exec command prompt:

{"name":"replicator-src-a-foo","config":{"connector.class":"io.confluent.connect.replicator.ReplicatorSourceConnector","key.converter":"io.confluent.connect.replicator.util.ByteArrayConverter","value.converter":"io.confluent.connect.replicator.util.ByteArrayConverter","src.zookeeper.connect":"localhost:22181","src.kafka.bootstrap.servers":"localhost:9092","dest.zookeeper.connect":"localhost:42181","topic.whitelist":"foo","topic.rename.format":"${topic}.replica","name":"replicator-src-a-foo"},"tasks":[]}

Before moving on, let’s check the status of the connector using curl on the docker exec command prompt.

curl -X GET http://localhost:28082/connectors/replicator-src-a-foo/status

You should see the following output including the state of the connector as RUNNING:

{"name":"replicator-src-a-foo","connector":{"state":"RUNNING","worker_id":"localhost:38082"},"tasks":[{"state":"RUNNING","id":0,"worker_id":"localhost:28082"}]}

Exit the docker exec command prompt by typing exit on the prompt.

exit
  1. Now that the connector is up and running, it should replicate data from foo topic on source-a cluster to foo.replica topic on the dest cluster.

Let’s try reading a sample of 1000 records from the foo.replica topic to check if the connector is replicating data to the destination Kafka cluster, as expected. Run the following command on your terminal (Make sure you have exited the docker exec command prompt):

docker run \
  --net=host \
  --rm \
  confluentinc/cp-kafka:3.1.2 \
  kafka-console-consumer --bootstrap-server localhost:9072 --topic foo.replica --new-consumer --from-beginning --max-messages 1000

If everything is working as expected, each of the original messages we produced should be written back out:

1
....
1000
Processed a total of 1000 messages

We will now verify that the destination topic is created with correct replication factor and partition count.

docker run \
  --net=host \
  --rm confluentinc/cp-kafka:3.1.2 \
  kafka-topics --describe --topic foo.replica --zookeeper localhost:42181

You should see that the topic foo.replica is created with 3 partitions and 2 replicas, same as the original topic foo.

Topic:foo.replica           PartitionCount:3        ReplicationFactor:2     Configs:message.timestamp.type=CreateTime
Topic: foo.replica          Partition: 0    Leader: 1002    Replicas: 1002,1001     Isr: 1002,1001
Topic: foo.replica          Partition: 1    Leader: 1001    Replicas: 1001,1002     Isr: 1001,1002
Topic: foo.replica          Partition: 2    Leader: 1002    Replicas: 1002,1001     Isr: 1002,1001
  1. Now, we will replicate another topic from a different source cluster.

First, lets create a new topic on the cluster source-b and add some data to it. Run the following commands to create and verify the topic. You should see output similar to steps 4 and 5 above:

docker run \
  --net=host \
  --rm confluentinc/cp-kafka:3.1.2 \
  kafka-topics --create --topic bar --partitions 3 --replication-factor 2 --if-not-exists --zookeeper localhost:32181

docker run \
  --net=host \
  --rm confluentinc/cp-kafka:3.1.2 \
  kafka-topics --describe --topic bar --zookeeper localhost:32181

docker run \
  --net=host \
  --rm \
  confluentinc/cp-kafka:3.1.2 \
  bash -c "seq 1000 | kafka-console-producer --request-required-acks 1 --broker-list localhost:9082 --topic bar && echo 'Produced 1000 messages.'"

Now lets exec into the Kafka Connect container and run the replicator connector. Enter the following commands on your terminal. You should see output similar to step 6 above.

Run the following to into the container to get docker exec command prompt.

docker-compose exec connect-host-1 bash

Run the following command on the docker exec command prompt.

curl -X POST \
     -H "Content-Type: application/json" \
     --data '{
        "name": "replicator-src-b-bar",
        "config": {
          "connector.class":"io.confluent.connect.replicator.ReplicatorSourceConnector",
          "key.converter": "io.confluent.connect.replicator.util.ByteArrayConverter",
          "value.converter": "io.confluent.connect.replicator.util.ByteArrayConverter",
          "src.zookeeper.connect": "localhost:32181",
          "src.kafka.bootstrap.servers": "localhost:9082",
          "dest.zookeeper.connect": "localhost:42181",
          "topic.whitelist": "bar",
          "topic.rename.format": "${topic}.replica"}}'  \
     http://localhost:28082/connectors

curl -X GET http://localhost:28082/connectors/replicator-src-b-bar/status

Exit the docker exec command prompt by typing exit on the prompt.

exit
  1. Now that the second replicator connector is up and running, it should replicate data from bar topic on source-b cluster to bar.replica topic on the dest cluster.

Let’s try reading a data from bar.replica topic to check if the connector is replicating data properly followed by describing the topic to verify that the destination topic was created properly. You should see output similar to step 7 above. as expected.

Run the following commands on your terminal (Make sure you have exited the docker exec command prompt):

docker run \
  --net=host \
  --rm \
  confluentinc/cp-kafka:3.1.2 \
  kafka-console-consumer --bootstrap-server localhost:9072 --topic bar.replica --new-consumer --from-beginning --max-messages 1000

docker run \
  --net=host \
  --rm confluentinc/cp-kafka:3.1.2 \
  kafka-topics --describe --topic bar.replica --zookeeper localhost:42181
  1. Feel free to experiment with the replicator connector on your own now. When you are done, use the following commands to shutdown all the components.
docker-compose stop

If you want to remove all the containers, run:

docker-compose rm