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org.apache.kafka.streams.examples.temperature.TemperatureDemo Maven / Gradle / Ivy
/*
* 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.temperature;
import org.apache.kafka.clients.consumer.ConsumerConfig;
import org.apache.kafka.common.serialization.Serde;
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.Produced;
import org.apache.kafka.streams.kstream.TimeWindows;
import org.apache.kafka.streams.kstream.Windowed;
import org.apache.kafka.streams.kstream.WindowedSerdes;
import java.time.Duration;
import java.util.Properties;
import java.util.concurrent.CountDownLatch;
/**
* This demo demonstrates, using the high-level KStream DSL, how to implement an IoT demo application
* which ingests temperature value to compute the maximum value in the latest TEMPERATURE_WINDOW_SIZE seconds (which
* is 5 seconds) and send a new message if it exceeds the TEMPERATURE_THRESHOLD (which is 20)
*
* In this example, the input stream reads from a topic named "iot-temperature", where the values of messages
* represent temperature values; using a TEMPERATURE_WINDOW_SIZE seconds "tumbling" window, the maximum value is processed and
* sent to a topic named "iot-temperature-max" if it exceeds the TEMPERATURE_THRESHOLD.
*
*
Before running this example you must create the input topic for temperature values in the following way :
*
*
bin/kafka-topics.sh --create --bootstrap-server localhost:9092 --replication-factor 1 --partitions 1 --topic iot-temperature
*
*
and at same time create the output topic for filtered values :
*
*
bin/kafka-topics.sh --create --bootstrap-server localhost:9092 --replication-factor 1 --partitions 1 --topic iot-temperature-max
*
*
After that, a console consumer can be started in order to read filtered values from the "iot-temperature-max" topic :
*
* bin/kafka-console-consumer.sh --bootstrap-server localhost:9092 --topic iot-temperature-max --from-beginning
*
*
On the other side, a console producer can be used for sending temperature values (which needs to be integers)
* to "iot-temperature" by typing them on the console :
*
*
bin/kafka-console-producer.sh --bootstrap-server localhost:9092 --topic iot-temperature
* > 10
* > 15
* > 22
*/
public class TemperatureDemo {
// threshold used for filtering max temperature values
private static final int TEMPERATURE_THRESHOLD = 20;
// window size within which the filtering is applied
private static final int TEMPERATURE_WINDOW_SIZE = 5;
public static void main(final String[] args) {
final Properties props = new Properties();
props.put(StreamsConfig.APPLICATION_ID_CONFIG, "streams-temperature");
props.put(StreamsConfig.BOOTSTRAP_SERVERS_CONFIG, "localhost:9092");
props.put(StreamsConfig.DEFAULT_KEY_SERDE_CLASS_CONFIG, Serdes.StringSerde.class);
props.put(StreamsConfig.DEFAULT_VALUE_SERDE_CLASS_CONFIG, Serdes.StringSerde.class);
props.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "earliest");
props.put(StreamsConfig.STATESTORE_CACHE_MAX_BYTES_CONFIG, 0);
final Duration duration24Hours = Duration.ofHours(24);
final StreamsBuilder builder = new StreamsBuilder();
final KStream source = builder.stream("iot-temperature");
final KStream, String> max = source
// temperature values are sent without a key (null), so in order
// to group and reduce them, a key is needed ("temp" has been chosen)
.selectKey((key, value) -> "temp")
.groupByKey()
.windowedBy(TimeWindows.ofSizeAndGrace(Duration.ofSeconds(TEMPERATURE_WINDOW_SIZE), duration24Hours))
.reduce((value1, value2) -> {
if (Integer.parseInt(value1) > Integer.parseInt(value2)) {
return value1;
} else {
return value2;
}
})
.toStream()
.filter((key, value) -> Integer.parseInt(value) > TEMPERATURE_THRESHOLD);
final Serde> windowedSerde = WindowedSerdes.timeWindowedSerdeFrom(String.class, TEMPERATURE_WINDOW_SIZE);
// need to override key serde to Windowed type
max.to("iot-temperature-max", Produced.with(windowedSerde, Serdes.String()));
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-temperature-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);
}
}