implement a simple WordCount program using the high-level Kafka Streams DSL

WordCount.java

package com.rich.stream.example;

import org.apache.kafka.common.serialization.Serdes;
import org.apache.kafka.common.utils.Bytes;
import org.apache.kafka.streams.KafkaStreams;
import org.apache.kafka.streams.StreamsBuilder;
import org.apache.kafka.streams.StreamsConfig;
import org.apache.kafka.streams.Topology;
import org.apache.kafka.streams.kstream.KeyValueMapper;
import org.apache.kafka.streams.kstream.Materialized;
import org.apache.kafka.streams.kstream.Produced;
import org.apache.kafka.streams.kstream.ValueMapper;
import org.apache.kafka.streams.state.KeyValueStore;

import java.util.Arrays;
import java.util.Locale;
import java.util.Properties;
import java.util.concurrent.CountDownLatch;

/**
 * In this example, we implement a simple WordCount program using the high-level Streams DSL
 * that reads from a source topic "streams-plaintext-input", where the values of messages represent lines of text,
 * split each text line into words and then compute the word occurence histogram, write the continuous updated histogram
 * into a topic "streams-wordcount-output" where each record is an updated count of a single word.
 */
public class WordCount {

    public static void main(String[] args) throws Exception {
        Properties props = new Properties();
        props.put(StreamsConfig.APPLICATION_ID_CONFIG, "streams-wordcount");
        props.put(StreamsConfig.BOOTSTRAP_SERVERS_CONFIG, "localhost:9092");
        props.put(StreamsConfig.DEFAULT_KEY_SERDE_CLASS_CONFIG, Serdes.String().getClass());
        props.put(StreamsConfig.DEFAULT_VALUE_SERDE_CLASS_CONFIG, Serdes.String().getClass());

        final StreamsBuilder builder = new StreamsBuilder();

        builder.<String, String>stream("streams-plaintext-input")
                // Split each text line, by whitespace, into words.
                .flatMapValues(value -> Arrays.asList(value.toLowerCase(Locale.getDefault()).split("\\W+")))
                // Group the text words as message keys
                .groupBy((key, value) -> value)
                // specifies that the running count should be stored in a state store named counts-store
               .count(Materialized.<String, Long, KeyValueStore<Bytes, byte[]>>as("counts-store"))
               .toStream()
                // Store the running counts as a changelog stream to the output topic.
               .to("streams-wordcount-output", Produced.with(Serdes.String(), Serdes.Long()));

        final Topology topology = builder.build();
        final KafkaStreams streams = new KafkaStreams(topology, props);
        final CountDownLatch latch = new CountDownLatch(1);

        // attach shutdown handler to catch control-c
        Runtime.getRuntime().addShutdownHook(new Thread("streams-shutdown-hook") {
            @Override
            public void run() {
                streams.close();
                latch.countDown();
            }
        });

        try {
            streams.start();
            latch.await();
        } catch (Throwable e) {
            System.exit(1);
        }
        System.exit(0);
    }
}