/*
 * 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.kafka.streams.examples.wordcount;

import org.apache.kafka.clients.consumer.ConsumerConfig;
import org.apache.kafka.common.serialization.Serdes;
import org.apache.kafka.streams.KafkaStreams;
import org.apache.kafka.streams.StreamsBuilder;
import org.apache.kafka.streams.StreamsConfig;
import org.apache.kafka.streams.kstream.KStream;
import org.apache.kafka.streams.kstream.KTable;
import org.apache.kafka.streams.kstream.Produced;

import java.io.FileInputStream;
import java.io.IOException;
import java.util.Arrays;
import java.util.Locale;
import java.util.Properties;
import java.util.concurrent.CountDownLatch;

/**
 * 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 final String INPUT_TOPIC = "streams-plaintext-input";
    public static final String OUTPUT_TOPIC = "streams-wordcount-output";

    static Properties getStreamsConfig(final String[] args) throws IOException {
        final Properties props = new Properties();
        if (args != null && args.length > 0) {
            try (final FileInputStream fis = new FileInputStream(args[0])) {
                props.load(fis);
            }
            if (args.length > 1) {
                System.out.println("Warning: Some command line arguments were ignored. This demo only accepts an optional configuration file.");
            }
        }
        props.putIfAbsent(StreamsConfig.APPLICATION_ID_CONFIG, "streams-wordcount");
        props.putIfAbsent(StreamsConfig.BOOTSTRAP_SERVERS_CONFIG, "localhost:9092");
        props.putIfAbsent(StreamsConfig.STATESTORE_CACHE_MAX_BYTES_CONFIG, 0);
        props.putIfAbsent(StreamsConfig.DEFAULT_KEY_SERDE_CLASS_CONFIG, Serdes.StringSerde.class);
        props.putIfAbsent(StreamsConfig.DEFAULT_VALUE_SERDE_CLASS_CONFIG, Serdes.StringSerde.class);

        // 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.putIfAbsent(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "earliest");
        return props;
    }

    static void createWordCountStream(final StreamsBuilder builder) {
        final KStream<String, String> source = builder.stream(INPUT_TOPIC);

        final KTable<String, Long> counts = source
            .flatMapValues(value -> Arrays.asList(value.toLowerCase(Locale.getDefault()).split("\\W+")))
            .groupBy((key, value) -> value)
            .count();

        // need to override value serde to Long type
        counts.toStream().to(OUTPUT_TOPIC, Produced.with(Serdes.String(), Serdes.Long()));
    }

    public static void main(final String[] args) throws IOException {
        final Properties props = getStreamsConfig(args);

        final StreamsBuilder builder = new StreamsBuilder();
        createWordCountStream(builder);
        final KafkaStreams streams = new KafkaStreams(builder.build(), 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);
    }
}
