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 org.apache.beam.examples;
  
  // beam-playground:
  //   name: KafkaWordCountJson
  //   description: Read CountWords dataset (CountWords.json) from Kafka to count words
  //   multifile: false
  //   context_line: 65
  //   categories:
  //     - Emulated Data Source
  //     - IO
  //     - Quickstart
  //   complexity: MEDIUM
  //   tags:
  //     - strings
  //     - emulator
  //   emulators:
  //      - type: kafka
  //        topic:
  //          id: CountWords
  //          source_dataset: CountWordsJson
  //   datasets:
  //     CountWordsJson:
  //       location: local
  //       format: json
  
  import java.util.Collections;
  import java.util.HashMap;
  import java.util.Map;
  import org.apache.beam.sdk.Pipeline;
  import org.apache.beam.sdk.io.TextIO;
  import org.apache.beam.sdk.io.kafka.KafkaIO;
  import org.apache.beam.sdk.options.Default;
  import org.apache.beam.sdk.options.Description;
  import org.apache.beam.sdk.options.PipelineOptions;
  import org.apache.beam.sdk.options.PipelineOptionsFactory;
  import org.apache.beam.sdk.transforms.Count;
  import org.apache.beam.sdk.transforms.DoFn;
  import org.apache.beam.sdk.transforms.MapElements;
  import org.apache.beam.sdk.transforms.ParDo;
  import org.apache.beam.sdk.transforms.SimpleFunction;
  import org.apache.beam.sdk.transforms.Values;
  import org.apache.beam.sdk.values.KV;
  import org.apache.kafka.common.TopicPartition;
  import org.apache.kafka.common.serialization.LongDeserializer;
  import org.apache.kafka.common.serialization.StringDeserializer;
  
  public class KafkaWordCountJson {
    static final String TOKENIZER_PATTERN = "[^\\p{L}]+"; // Java pattern for letters
  
    public interface KafkaStreamingOptions extends PipelineOptions {
      /**
       * By default, this example uses Playground's Kafka server. Set this option to different value
       * to use your own Kafka server.
       */
      @Description("Kafka server host")
      @Default.String("kafka_server:9092")
      String getKafkaHost();
  
      void setKafkaHost(String value);
    }
  
    public static void main(String[] args) {
      KafkaStreamingOptions options =
          PipelineOptionsFactory.fromArgs(args).withValidation().as(KafkaStreamingOptions.class);
      final Pipeline p = Pipeline.create(options);
  
      final Map<String, Object> consumerConfig = new HashMap<>();
      consumerConfig.put("auto.offset.reset", "earliest");
  
      p.apply(
              KafkaIO.<Long, String>read()
                  .withBootstrapServers(
                      options.getKafkaHost()) // Set KafkaHost pipeline option to redefine
                  // default value (valid for Playground environment)
                  .withTopicPartitions(
                      Collections.singletonList(
                          new TopicPartition(
                              "CountWords", 0))) // Kafka topic is preloaded in Playground environment
                  .withKeyDeserializer(LongDeserializer.class)
                  .withValueDeserializer(StringDeserializer.class)
                  .withConsumerConfigUpdates(consumerConfig)
                  .withMaxNumRecords(5)
                  .withoutMetadata())
          .apply(Values.create())
          .apply(
              "ExtractWords",
              ParDo.of(
                  new DoFn<String, String>() {
                    @ProcessElement
                    public void processElement(ProcessContext c) {
                      for (String word : c.element().split(TOKENIZER_PATTERN, 0)) {
                        if (!word.isEmpty()) {
                          c.output(word);
                        }
                      }
                    }
                  }))
          .apply(Count.perElement())
          .apply(
              "FormatResults",
              MapElements.via(
                  new SimpleFunction<KV<String, Long>, String>() {
                    @Override
                    public String apply(KV<String, Long> input) {
                      System.out.printf("key: %s, value: %d%n", input.getKey(), input.getValue());
                      return input.getKey() + ": " + input.getValue();
                    }
                  }))
          .apply(TextIO.write().to("word-counts"));
  
      p.run().waitUntilFinish();
    }
  }
  