content: /*
   * Licensed to the Apache Software Foundation (ASF) under one or more
   * contributor license agreements. See the NOTICE file distributed with
   * this work for additional information regarding copyright ownership.
   * The ASF licenses this file to You under the Apache License, Version 2.0
   * (the "License"); you may not use this file except in compliance with
   * the License. You may obtain a copy of the License at
   *
   *    http://www.apache.org/licenses/LICENSE-2.0
   *
   * Unless required by applicable law or agreed to in writing, software
   * distributed under the License is distributed on an "AS IS" BASIS,
   * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
   * See the License for the specific language governing permissions and
   * limitations under the License.
   */
  package ${package};
  
  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 occurrence 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) {
          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")
                 .flatMapValues(value -> Arrays.asList(value.toLowerCase(Locale.getDefault()).split("\\W+")))
                 .groupBy((key, value) -> value)
                 .count(Materialized.<String, Long, KeyValueStore<Bytes, byte[]>>as("counts-store"))
                 .toStream()
                 .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);
      }
  }
  