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| <script><!--#include virtual="../js/templateData.js" --></script> |
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| <h1>Kafka Streams API</h1> |
| |
| <h3 style="max-width: 75rem;">The easiest way to write mission-critical real-time applications and microservices with all the benefits of Kafka's server-side cluster technology.</h3> |
| |
| <div class="hero"> |
| <div class="hero__diagram"> |
| <img src="/{{version}}/images/streams-welcome.png" /> |
| </div> |
| <div class="hero__cta"> |
| <a href="/{{version}}/documentation/streams/tutorial" class="btn">Write your first app</a> |
| <a href="/{{version}}/documentation/streams/quickstart" class="btn">Play with demo app</a> |
| </div> |
| </div> |
| |
| <ul class="feature-list"> |
| <li>Write standard Java applications</li> |
| <li>Exactly-once processing semantics</li> |
| <li>No seperate processing cluster required</li> |
| <li>Develop on Mac, Linux, Windows</li> |
| <li>Elastic, highly scalable, fault-tolerant</li> |
| <li>Deploy to containers, VMs, bare metal, cloud</li> |
| <li>Equally viable for small, medium, & large use cases</li> |
| <li>Fully integrated with Kafka security</li> |
| </ul> |
| |
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| <a class="card" href="/{{version}}/documentation/streams/developer-guide"> |
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| <span class="card__label">Concepts</span> |
| </a> |
| </div> |
| |
| <h3>Hello Kafka Streams</h3> |
| <p>The code example below implements a WordCount application that is elastic, highly scalable, fault-tolerant, stateful, and ready to run in production at large scale</p> |
| |
| <div class="code-example"> |
| <div class="btn-group"> |
| <a class="selected b-java-8" data-section="java-8">Java 8+</a> |
| <a class="b-java-7" data-section="java-7">Java 7</a> |
| <a class="b-scala" data-section="scala">Scala</a> |
| </div> |
| |
| <div class="code-example__snippet b-java-8 selected"> |
| <pre class="line-numbers"><code class="language-java"> import org.apache.kafka.common.serialization.Serdes; |
| import org.apache.kafka.streams.KafkaStreams; |
| import org.apache.kafka.streams.StreamsConfig; |
| import org.apache.kafka.streams.kstream.KStream; |
| import org.apache.kafka.streams.kstream.KStreamBuilder; |
| import org.apache.kafka.streams.kstream.KTable; |
| |
| import java.util.Arrays; |
| import java.util.Properties; |
| |
| public class WordCountApplication { |
| |
| public static void main(final String[] args) throws Exception { |
| Properties config = new Properties(); |
| config.put(StreamsConfig.APPLICATION_ID_CONFIG, "wordcount-application"); |
| config.put(StreamsConfig.BOOTSTRAP_SERVERS_CONFIG, "kafka-broker1:9092"); |
| config.put(StreamsConfig.DEFAULT_KEY_SERDE_CLASS_CONFIG, Serdes.String().getClass()); |
| config.put(StreamsConfig.DEFAULT_VALUE_SERDE_CLASS_CONFIG, Serdes.String().getClass()); |
| |
| KStreamBuilder builder = new KStreamBuilder(); |
| KStream<String, String> textLines = builder.stream("TextLinesTopic"); |
| KTable<String, Long> wordCounts = textLines |
| .flatMapValues(textLine -> Arrays.asList(textLine.toLowerCase().split("\\W+"))) |
| .groupBy((key, word) -> word) |
| .count("Counts"); |
| wordCounts.to(Serdes.String(), Serdes.Long(), "WordsWithCountsTopic"); |
| |
| KafkaStreams streams = new KafkaStreams(builder, config); |
| streams.start(); |
| } |
| |
| } |
| </code></pre> |
| </div> |
| |
| <div class="code-example__snippet b-java-7"> |
| <pre class="line-numbers"><code class="language-java"> import org.apache.kafka.common.serialization.Serdes; |
| import org.apache.kafka.streams.KafkaStreams; |
| import org.apache.kafka.streams.StreamsConfig; |
| import org.apache.kafka.streams.kstream.KStream; |
| import org.apache.kafka.streams.kstream.KStreamBuilder; |
| import org.apache.kafka.streams.kstream.KTable; |
| import org.apache.kafka.streams.kstream.KeyValueMapper; |
| import org.apache.kafka.streams.kstream.ValueMapper; |
| |
| import java.util.Arrays; |
| import java.util.Properties; |
| |
| public class WordCountApplication { |
| |
| public static void main(final String[] args) throws Exception { |
| Properties config = new Properties(); |
| config.put(StreamsConfig.APPLICATION_ID_CONFIG, "wordcount-application"); |
| config.put(StreamsConfig.BOOTSTRAP_SERVERS_CONFIG, "kafka-broker1:9092"); |
| config.put(StreamsConfig.DEFAULT_KEY_SERDE_CLASS_CONFIG, Serdes.String().getClass()); |
| config.put(StreamsConfig.DEFAULT_VALUE_SERDE_CLASS_CONFIG, Serdes.String().getClass()); |
| |
| KStreamBuilder builder = new KStreamBuilder(); |
| KStream<String, String> textLines = builder.stream("TextLinesTopic"); |
| KTable<String, Long> wordCounts = textLines |
| .flatMapValues(new ValueMapper<String, Iterable<String>>() { |
| @Override |
| public Iterable<String> apply(String textLine) { |
| return Arrays.asList(textLine.toLowerCase().split("\\W+")); |
| } |
| }) |
| .groupBy(new KeyValueMapper<String, String, String>() { |
| @Override |
| public String apply(String key, String word) { |
| return word; |
| } |
| }) |
| .count("Counts"); |
| wordCounts.to(Serdes.String(), Serdes.Long(), "WordsWithCountsTopic"); |
| |
| KafkaStreams streams = new KafkaStreams(builder, config); |
| streams.start(); |
| } |
| |
| } |
| </code></pre> |
| </div> |
| |
| <div class="code-example__snippet b-scala"> |
| <pre class="line-numbers"><code class="language-scala"> import java.lang.Long |
| import java.util.Properties |
| import java.util.concurrent.TimeUnit |
| |
| import org.apache.kafka.common.serialization._ |
| import org.apache.kafka.streams._ |
| import org.apache.kafka.streams.kstream.{KStream, KStreamBuilder, KTable} |
| |
| import scala.collection.JavaConverters.asJavaIterableConverter |
| |
| object WordCountApplication { |
| |
| def main(args: Array[String]) { |
| val config: Properties = { |
| val p = new Properties() |
| p.put(StreamsConfig.APPLICATION_ID_CONFIG, "wordcount-application") |
| p.put(StreamsConfig.BOOTSTRAP_SERVERS_CONFIG, "kafka-broker1:9092") |
| p.put(StreamsConfig.DEFAULT_KEY_SERDE_CLASS_CONFIG, Serdes.String().getClass) |
| p.put(StreamsConfig.DEFAULT_VALUE_SERDE_CLASS_CONFIG, Serdes.String().getClass) |
| p |
| } |
| |
| val builder: KStreamBuilder = new KStreamBuilder() |
| val textLines: KStream[String, String] = builder.stream("TextLinesTopic") |
| val wordCounts: KTable[String, Long] = textLines |
| .flatMapValues(textLine => textLine.toLowerCase.split("\\W+").toIterable.asJava) |
| .groupBy((_, word) => word) |
| .count("Counts") |
| wordCounts.to(Serdes.String(), Serdes.Long(), "WordsWithCountsTopic") |
| |
| val streams: KafkaStreams = new KafkaStreams(builder, config) |
| streams.start() |
| |
| Runtime.getRuntime.addShutdownHook(new Thread(() => { |
| streams.close(10, TimeUnit.SECONDS) |
| })) |
| } |
| |
| } |
| </code></pre> |
| </div> |
| </div> |
| <h3 class="customer-title">See how Kafka Streams is being used</h3> |
| <div class="customer__cards"> |
| <div class="customer__card"> |
| <div class="customer__card__icon"> |
| <img src="/{{version}}/images/icons/rabobank.png"> |
| </div> |
| <span class="customer__card__label">Rabobank is one of the 3 largest banks in the Netherlands. Its digital nervous system, the Business Event Bus, is powered by Apache Kafka and Kafka Streams. |
| </span> |
| <a href="https://www.confluent.io/blog/real-time-financial-alerts-rabobank-apache-kafkas-streams-api/">Learn More</a> |
| </div> |
| <div class="customer__card customer-right" > |
| <div class="customer__card__icon" > |
| <img src="/{{version}}/images/icons/zalando.png"> |
| </div> |
| <span class="customer__card__label">As the leading online fashion retailer in Europe, Zalando uses Kafka as an ESB (Enterprise Service Bus), which helps us in transitioning from a monolithic to a micro services architecture. Using Kafka for processing event streams enables our technical team to do near-real time business intelligence.</span> |
| <a href="https://kafka-summit.org/sessions/using-kstreams-ktables-calculate-real-time-domain-rankings/">Learn More</a> |
| </div> |
| </div> |
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