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 streams;
  
  import java.util.Arrays;
  import java.util.Locale;
  import java.util.Properties;
  import java.util.concurrent.CountDownLatch;
  import org.apache.kafka.clients.consumer.ConsumerConfig;
  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.Grouped;
  import org.apache.kafka.streams.kstream.KStream;
  import org.apache.kafka.streams.kstream.KTable;
  import org.apache.kafka.streams.kstream.Materialized;
  import org.apache.kafka.streams.kstream.Produced;
  import org.apache.kafka.streams.state.KeyValueStore;
  
  /**
   * Demonstrates, using the high-level KStream DSL, how to implement the WordCount program
   * that computes a simple word occurrence histogram from an input text.
   * <p>
   * In this example, the input stream reads from a topic named "streams-plaintext-input", where the values of messages
   * represent lines of text; and the histogram output is written to topic "streams-wordcount-output" where each record
   * is an updated count of a single word.
   * <p>
   * Before running this example you must create the input topic and the output topic (e.g. via
   * {@code bin/kafka-topics.sh --create ...}), and write some data to the input topic (e.g. via
   * {@code bin/kafka-console-producer.sh}). Otherwise you won't see any data arriving in the output topic.
   */
  public final class WordCountDemo {
  
      public static void main(final String[] args) {
          String servers = args.length > 0 ? args[1] : "localhost:9092";
          System.out.println("servers:" + servers);
          final Properties props = new Properties();
          props.put(StreamsConfig.APPLICATION_ID_CONFIG, "streams");
          props.put(StreamsConfig.BOOTSTRAP_SERVERS_CONFIG, servers);
          props.put(StreamsConfig.CACHE_MAX_BYTES_BUFFERING_CONFIG, 0);
          props.put(StreamsConfig.DEFAULT_KEY_SERDE_CLASS_CONFIG, Serdes.String().getClass().getName());
          props.put(StreamsConfig.DEFAULT_VALUE_SERDE_CLASS_CONFIG, Serdes.String().getClass().getName());
  
          // setting offset reset to earliest so that we can re-run the demo code with the same pre-loaded data
          // Note: To re-run the demo, you need to use the offset reset tool:
          // https://cwiki.apache.org/confluence/display/KAFKA/Kafka+Streams+Application+Reset+Tool
          props.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "earliest");
  
          final StreamsBuilder builder = new StreamsBuilder();
  
          //normal source topics
          final KStream<String, String> source = builder.stream("streams-plaintext-input");
  
          final KTable<String, Long> counts = source
              .flatMapValues(value -> Arrays.asList(value.toLowerCase(Locale.getDefault()).split(" ")))
              //local topic, clean.policy=delete
              .groupBy((key, value) -> value, Grouped.as("counts-groupby"))
              //local topic, clean.policy=compact
              .count(Materialized.<String, Long, KeyValueStore<Bytes, byte[]>>as("counts-store").withKeySerde(Serdes.String()).withValueSerde(Serdes.Long()));
  
          //local topic, clean.policy=compact
          counts.toStream().to("streams-wordcount-output", Produced.with(Serdes.String(), Serdes.Long()));
  
          Topology topology = builder.build();
  
          //print the topology
          System.out.println(topology.describe());
  
          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-wordcount-shutdown-hook") {
              @Override
              public void run() {
                  streams.close();
                  latch.countDown();
              }
          });
  
          try {
              streams.start();
              latch.await();
          } catch (final Throwable e) {
              System.exit(1);
          }
          System.exit(0);
      }
  }
  