Enterprise Java

Getting Started with Kafka REST Proxy for MapR Streams

MapR Ecosystem Package 2.0 (MEP) is coming with some new features related to MapR Streams:

  • Kafka REST Proxy for MapR Streams provides a RESTful interface to MapR Streams and Kafka clusters, making it easy to consume and produce messages as well as perform administrative operations.
  • Kafka Connect for MapR Streams is a utility for streaming data between MapR Streams and Apache Kafka and other storage systems.

MapR Ecosystem Packs (MEPs) are a way to deliver ecosystem upgrades, decoupled from core upgrades – allowing you to upgrade your tooling independently of the MapR Converged Data Platform. You can learn more about MEP 2.0 in this article.

In this blog, we describe how to use the Kafka REST Proxy to publish and consume messages to/from MapR Streams. The REST Proxy is a great addition to the MapR Converged Data Platform, allowing any programming language to use MapR Streams.

The Kafka REST Proxy, provided with the MapR Streams tools, can be used with MapR Streams (default) as well as Apache Kafka (in a hybrid mode). In this article, we will focus on MapR Streams.


  • MapR Converged Data Platform 5.2 with MEP 2.0
    • with MapR Streams Tools
  • curl, wget or any HTTP/REST Client tool

Create the MapR Streams and Topic

A stream is a collection of topics that you can manage as a group by:

  1. Setting security policies that apply to all topics in that stream
  2. Setting a default number of partitions for each new topic that is created in the stream
  3. Setting a time-to-live for messages in every topic in the stream

You can find more information about MapR Streams concepts in the documentation.

On your MapR Cluster or Sandbox, run the following commands:

$ maprcli stream create -path /apps/iot-stream -produceperm p -consumeperm p -topicperm p
$ maprcli stream topic create -path /apps/iot-stream -topic sensor-json -partitions 3
$ maprcli stream topic create -path /apps/iot-stream -topic sensor-binary -partitions 3

Start Kafka Console Producers and Consumers

Open two terminal windows and run the consumer Kafka utilities using the following commands:


  • Topic sensor-json
$ /opt/mapr/kafka/kafka-0.9.0/bin/kafka-console-consumer.sh --new-consumer --bootstrap-server this.will.be.ignored:9092 --topic /apps/iot-stream:sensor-json
  • Topic sensor-binary
$ /opt/mapr/kafka/kafka-0.9.0/bin/kafka-console-consumer.sh --new-consumer --bootstrap-server this.will.be.ignored:9092 --topic /apps/iot-stream:sensor-binary

These two terminal windows will allow you to see the messages posted on the different topics.

Using Kafka REST Proxy

Inspect Topic Metadata

The endpoint /topics/[topic_name] allows you to get some information about the topic. In MapR Streams, topics are part of a stream identified by a path; to access the topic via the REST API, you have to input the full path and encode it in the URL; for example:

  • /apps/iot-stream:sensor-json will be encoded with %2Fapps%2Fiot-stream%3Asensor-json

Run the following command, to get information about the sensor-json topic:

$ curl -X GET  http://localhost:8082/topics/%2Fapps%2Fiot-stream%3Asensor-json

Note: For the sake of simplicity, I am running the command from the node where the Kafka REST proxy is running, so it is possible to use localhost.

You can print JSON in a pretty way, by adding a Python command, such as:

$ curl -X GET  http://localhost:8082/topics/%2Fapps%2Fiot-stream%3Asensor-json | python -m json.tool

Default Stream

As mentioned above, the Stream path is part of the topic name you have to use in the command; however, it is possible to configure the MapR Kafka REST Proxy to use a default stream. For this configuration, you should add the following property in the /opt/mapr/kafka-rest/kafka-rest-2.0.1/config/kafka-rest.properties file:

  • streams.default.stream=/apps/iot-stream

When you change the Kafka REST proxy configuration, you must restart the service using maprcli or MCS.

The main reason to use the streams.default.stream properties is to simplify the URLs used by the application. For example:

In this article, all the URLs contain the encoded stream name, so that you can start using the Kafka REST proxy without changing the configuration and also use it with different streams.

Publishing Messages

The Kafka REST Proxy for MapR Streams allows applications to publish messages to MapR Streams. Messages could be sent as JSON or binary content (base64 encoding).

To send a JSON message:

  • the query should be a HTTP POST
  • the Content-Type should be : application/vnd.kafka.json.v1+json
  • the Body:
        "temp" : 10 ,
        "speed" : 40 ,
        "direction" : "NW"

The complete request is:

curl -X POST -H "Content-Type: application/vnd.kafka.json.v1+json" \
  --data '{"records":[{"value": {"temp" : 10 , "speed" : 40 , "direction" : "NW"}  }]}' \

You should see the message printed in the terminal window, where the /apps/iot-stream:sensor-json consumer is running.

To send a binary message:

  • the query should be a HTTP POST
  • the Content-Type should be : application/vnd.kafka.binary.v1+json
  • the Body:

Note that SGVsbG8gV29ybGQ= is the string “Hello World” encoded in Base64.

The complete request is:

curl -X POST -H "Content-Type: application/vnd.kafka.binary.v1+json" \
  --data '{"records":[{"value":"SGVsbG8gV29ybGQ="}]}' \

You should see the message printed in the terminal window, where the /apps/iot-stream:sensor-binary consumer is running.

To send multiple messages:

The record field of the HTTP Body allows you to send multiple messages; for example, you can send:

curl -X POST -H "Content-Type: application/vnd.kafka.json.v1+json" \
  --data '{"records":[{"value": {"temp" : 12 , "speed" : 42 , "direction" : "NW"}  }, {"value": {"temp" : 10 , "speed" : 37 , "direction" : "N"}  } ]}' \

This command will send 2 messages and increment the offset by 2. You can do the same with binary content by adding new elements in the JSON array; for example:

curl -X POST -H "Content-Type: application/vnd.kafka.binary.v1+json" \
  --data '{"records":[{"value":"SGVsbG8gV29ybGQ="}, {"value":"Qm9uam91cg=="}]}' \

As you probably know, it is possible to bind a key to a message to be sure that all the messages with the same key will arrive in the same partition. To do so, add the key attribute to the message as follows:

      "key": "K001",
        "temp" : 10 ,
        "speed" : 40 ,
        "direction" : "NW"

Now that you know how to post messages to a MapR Streams topic using the REST Proxy, let’s see how to consume the messages.

Consuming Messages

The REST proxy can also be used to consume messages from topics; for this task, you need to:

  1. Create a consumer instance.
  2. Use the URL returned by the first call to read the message.
  3. Delete the consumer instance, if needed.

Creating the consumer instance

The following request creates the consumer instance:

curl -X POST -H "Content-Type: application/vnd.kafka.v1+json" \
      --data '{"name": "iot_json_consumer", "format": "json", "auto.offset.reset": "earliest"}' \

The response from the server looks like:


Note that we have used the /consumers/[topic_name] to create the consumer. The base_uri will be used by the subsequent requests to get the messages from the topic. Like any MapR Streams/Kafka consumer, the auto.offset.reset defines its behavior. In this example, the value is set to earliest, which means that the consumer will read the messages from the beginning. You can find more information about the consumer configuration in the MapR Streams documentation.

Consuming the messages

To consume the messages, just add the MapR Streams topic to the URL of the consumer instance.

The following request consumes the messages from the topic:

curl -X GET -H "Accept: application/vnd.kafka.json.v1+json" \

This call returns the messages in a JSON document:


Each call to the API returns the new messages published, based on the offset of the last call.

Note that the Consumer will be destroyed:

  • after some idle time set by the consumer.instance.timeout.ms (default value set to 300000ms / 5 minutes), it is destroyed using a REST API call (see below).

Consuming binary format messages

The approach is the same if you need to consume binary messages: you need to change the format and Accept header.

Call this URL to create a consumer instance for the binary topic:

curl -X POST -H "Content-Type: application/vnd.kafka.v1+json" \
      --data '{"name": "iot_binary_consumer", "format": "binary", "auto.offset.reset": "earliest"}' \

Then consume messages, the accept header is set to application/vnd.kafka.binary.v1+json:

curl -X GET -H "Accept: application/vnd.kafka.binary.v1+json" \

This call returns the messages in a JSON document, and the value is encoded in Base64:


Delete consumer instances

As mentioned before, the consumer will be destroyed automatically based on the consumer.instance.timeout.msconfiguration of the REST Proxy; it is also possible to destroy the instance using the consumer instance URI and an HTTP DELETE call, as follows:

curl -X DELETE http://localhost:8082/consumers/%2Fapps%2Fiot-stream%3Asensor-binary/instances/iot_binary_consumer


In this article, you have learned how to use the Kafka REST Proxy for MapR Streams that allows any application to use messages published in the MapR Converged Data Platform.

You can find more information about the Kafka REST Proxy in the MapR documentation and in the following resources:

Reference: Getting Started with Kafka REST Proxy for MapR Streams from our JCG partner Tugdual Grall at the Mapr blog.

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Tugdual Grall

Tugdual Grall, an open source advocate and a passionate developer, is a Chief Technical Evangelist EMEA at MapR. He currently works with the European developer communities to ease MapR, Hadoop, and NoSQL adoption. Before joining MapR, Tug was Technical Evangelist at MongoDB and Couchbase. Tug has also worked as CTO at eXo Platform and JavaEE product manager, and software engineer at Oracle. Tugdual is Co-Founder of the Nantes JUG (Java User Group) that holds since 2008 monthly meeting about Java ecosystem. Tugdual also writes a blog available at http://tgrall.github.io/
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