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<script><!--#include virtual="js/templateData.js" --></script>

<script id="quickstart-docker-template" type="text/x-handlebars-template">
<div class="quickstart-step">
<h4 class="anchor-heading">
    <a class="anchor-link" id="step-1-get-kafka" href="#step-1-get-kafka"></a>
    <a href="#step-1-get-kafka">Step 1: Get Kafka</a>
</h4>

<p>
    This docker-compose file will run everything for you via <a href="https://www.docker.com/" rel="nofollow">Docker</a>.
    Copy and paste it into a file named <code>docker-compose.yml</code> on your local filesystem.
</p>
<pre class="line-numbers"><code class="language-bash">---
    version: '2'
    
    services:
      broker:
        image: apache-kafka/broker:2.5.0
        hostname: kafka-broker
        container_name: kafka-broker
    
    # ...rest omitted...</code></pre>
</div>

<div class="quickstart-step">
<h4 class="anchor-heading">
    <a class="anchor-link" id="step-2-start-kafka" href="#step-2-start-kafka"></a>
    <a href="#step-2-start-kafka">Step 2: Start the Kafka environment</a>
</h4>

<p>
    From the directory containing the <code>docker-compose.yml</code> file created in the previous step, run this
    command in order to start all services in the correct order:
</p>
<pre class="line-numbers"><code class="language-bash">$ docker-compose up</code></pre>
<p>
    Once all services have successfully launched, you will have a basic Kafka environment running and ready to use.
</p>
</div>

<div class="quickstart-step">
<h4 class="anchor-heading">
    <a class="anchor-link" id="step-3-create-a-topic" href="#step-3-create-a-topic"></a>
    <a href="#step-3-create-a-topic">Step 3: Create a topic to store your events</a>
</h4>
<p>Kafka is a distributed <em>event streaming platform</em> that lets you read, write, store, and process
<a href="/documentation/#messages" rel="nofollow"><em>events</em></a> (also called <em>records</em> or <em>messages</em> in the documentation)
across many machines.
Example events are payment transactions, geolocation updates from mobile phones, shipping orders, sensor measurements
from IoT devices or medical equipment, and much more.
These events are organized and stored in <a href="/documentation/#intro_topics" rel="nofollow"><em>topics</em></a>.
Very simplified, a topic is similar to a folder in a filesystem, and the events are the files in that folder.</p>
<p>So before you can write your first events, you must create a topic:</p>
<pre class="line-numbers"><code class="language-bash">$ docker exec -it kafka-broker kafka-topics.sh --create --topic quickstart-events</code></pre>
<p>All of Kafka's command line tools have additional options: run the <code>kafka-topics.sh</code> command without any
arguments to display usage information.
For example, it can also show you
<a href="/documentation/#intro_topics" rel="nofollow">details such as the partition count</a> of the new topic:</p>
<pre class="line-numbers"><code class="language-bash">$ docker exec -it kafka-broker kafka-topics.sh --describe --topic quickstart-events
    Topic:quickstart-events  PartitionCount:1    ReplicationFactor:1 Configs:
    Topic: quickstart-events Partition: 0    Leader: 0   Replicas: 0 Isr: 0</code></pre>
</div>

<div class="quickstart-step">
<h4 class="anchor-heading">
    <a class="anchor-link" id="step-4-write-events" href="#step-4-write-events"></a>
    <a href="#step-4-write-events">Step 4: Write some events into the topic</a>
</h4>
<p>A Kafka client communicates with the Kafka brokers via the network for writing (or reading) events.
Once received, the brokers will store the events in a durable and fault-tolerant manner for as long as you
need—even forever.</p>
<p>Run the console producer client to write a few events into your topic.
By default, each line you enter will result in a separate event being written to the topic.</p>
<pre class="line-numbers"><code class="language-bash">$ docker exec -it kafka-broker kafka-console-producer.sh --topic quickstart-events
This is my first event
This is my second event</code></pre>
<p>You can stop the producer client with <code>Ctrl-C</code> at any time.</p>
</div>

<div class="quickstart-step">
<h4 class="anchor-heading">
    <a class="anchor-link" id="step-5-read-the-events" href="#step-5-read-the-events"></a>
    <a href="#step-5-read-the-events">Step 5: Read the events</a>
</h4>
<p>Open another terminal session and run the console consumer client to read the events you just created:</p>
<pre class="line-numbers"><code class="language-bash">$ docker exec -it kafka-broker kafka-console-consumer.sh --topic quickstart-events --from-beginning
This is my first event
This is my second event</code></pre>
<p>You can stop the consumer client with <code>Ctrl-C</code> at any time.</p>
<p>Feel free to experiment: for example, switch back to your producer terminal (previous step) to write
additional events, and see how the events immediately show up in your consumer terminal.</p>
<p>Because events are durably stored in Kafka, they can be read as many times and by as many consumers as you want.
You can easily verify this by opening yet another terminal session and re-running the previous command again.</p>

</div>

<div class="quickstart-step">
<h4 class="anchor-heading">
    <a class="anchor-link" id="step-5-read-the-events" href="#step-5-read-the-events"></a>
    <a href="#step-5-read-the-events">Step 6: Import/export your data as streams of events with Kafka Connect</a>
</h4>
<p>You probably have lots of data in existing systems like relational databases or traditional messaging systems, along
with many applications that already use these systems.
<a href="/documentation/#connect" rel="nofollow">Kafka Connect</a> allows you to continuously ingest data from external
systems into Kafka, and vice versa.  It is thus
very easy to integrate existing systems with Kafka. To make this process even easier, there are hundreds of such
connectors readily available.</p>
<p>Take a look at the <a href="/documentation/#connect" rel="nofollow">Kafka Connect section</a> in the documentation to
learn more about how to continuously import/export your data into and out of Kafka.</p>

</div>

<div class="quickstart-step">
<h4 class="anchor-heading">
    <a class="anchor-link" id="step-7-process-events" href="#step-7-process-events"></a>
    <a href="#step-7-process-events">Step 7: Process your events with Kafka Streams</a>
</h4>

<p>Once your data is stored in Kafka as events, you can process the data with the
<a href="/documentation/streams" rel="nofollow">Kafka Streams</a> client library for Java/Scala.
It allows you to implement mission-critical real-time applications and microservices, where the input and/or output data
is stored in Kafka topics.  Kafka Streams combines the simplicity of writing and deploying standard Java and Scala
applications on the client side with the benefits of Kafka's server-side cluster technology to make these applications
highly scalable, elastic, fault-tolerant, and distributed. The library supports exactly-once processing, stateful
operations and aggregations, windowing, joins, processing based on event-time, and much more.</p>
<p>To give you a first taste, here's how one would implement the popular <code>WordCount</code> algorithm:</p>
<pre class="line-numbers"><code class="language-java">KStream<String, String> textLines = builder.stream("quickstart-events");

KTable<String, Long> wordCounts = textLines
            .flatMapValues(line -> Arrays.asList(line.toLowerCase().split(" ")))
            .groupBy((keyIgnored, word) -> word)
            .count();

wordCounts.toStream().to("output-topic"), Produced.with(Serdes.String(), Serdes.Long()));</code></pre>
<p>The <a href="/25/documentation/streams/quickstart" rel="nofollow">Kafka Streams demo</a> and the
<a href="/25/documentation/streams/tutorial" rel="nofollow">app development tutorial</a> demonstrate how to code and run
such a streaming application from start to finish.</p>

</div>

<div class="quickstart-step">
<h4 class="anchor-heading">
    <a class="anchor-link" id="step-8-terminate" href="#step-8-terminate"></a>
    <a href="#step-8-terminate">Step 8: Terminate the Kafka environment</a>
</h4>
<p>Now that you reached the end of the quickstart, feel free to tear down the Kafka environment—or continue playing around.</p>
<p>Run the following command to tear down the environment, which also deletes any events you have created along the way:</p>
<pre class="line-numbers"><code class="language-bash">$ docker-compose down</code></pre>

</div>

<div class="quickstart-step">
<h4 class="anchor-heading">
    <a class="anchor-link" id="quickstart_kafkacongrats" href="#quickstart_kafkacongrats"></a>
    <a href="#quickstart_kafkacongrats">Congratulations!</a>
  </h4>
  
  <p>You have successfully finished the Apache Kafka quickstart.<div>
  
  <p>To learn more, we suggest the following next steps:</p>
  
  <ul>
      <li>
          Read through the brief <a href="/intro">Introduction</a> to learn how Kafka works at a high level, its
          main concepts, and how it compares to other technologies. To understand Kafka in more detail, head over to the
          <a href="/documentation/">Documentation</a>.
      </li>
      <li>
          Browse through the <a href="/powered-by">Use Cases</a> to learn how other users in our world-wide
          community are getting value out of Kafka.
      </li>
      <!--
      <li>
          Learn how _Kafka compares to other technologies_ [note to design team: this new page is not yet written] you might be familiar with.
      </li>
      -->
      <li>
          Join a <a href="/events">local Kafka meetup group</a> and
          <a href="https://kafka-summit.org/past-events/">watch talks from Kafka Summit</a>,
          the main conference of the Kafka community.
      </li>
  </ul>
</div>
</script>

<div class="p-quickstart-docker"></div>