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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>

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        <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, &amp; large use cases</li>
        <li>Fully integrated with Kafka security</li>
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    <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>

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            <pre class="brush: 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&lt;String, String&gt; textLines = builder.stream("TextLinesTopic");
                        KTable&lt;String, Long&gt; 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();
                    }

                }
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            <pre class="brush: 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&lt;String, String&gt; textLines = builder.stream("TextLinesTopic");
                        KTable&lt;String, Long&gt; wordCounts = textLines
                            .flatMapValues(new ValueMapper&lt;String, Iterable&lt;String&gt;&gt;() {
                                @Override
                                public Iterable&lt;String&gt; apply(String textLine) {
                                    return Arrays.asList(textLine.toLowerCase().split("\\W+"));
                                }
                            })
                            .groupBy(new KeyValueMapper&lt;String, String, String&gt;() {
                                @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();
                    }

                }
            </pre>
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        <div class="code-example__snippet b-scala">
            <pre class="brush: 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)
                        }))
                    }

                }
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