A to Z Kafka Streams (Example 2)

September 27, 2022

Running a Kafka Streams application

Download Kafka:

curl https://dlcdn.apache.org/kafka/3.6.1/kafka_2.13-3.6.1.tgz -o kafka_2.13-3.6.1.tgz


tar -xzf kafka_2.13-3.6.1.tgz

Go to Kafka folder:

cd kafka_2.13-3.6.1.tgz

Start zookeeper:

bin/zookeeper-server-start.sh config/zookeeper.properties

Note: Zookeeper defaults to port 2181

Start kafka:

bin/kafka-server-start.sh config/server.properties

Note: Kafka defaults to port 9092

Create the input topic(input-topic):

bin/kafka-topics.sh --create \
    --bootstrap-server localhost:9092 \
    --replication-factor 1 \
    --partitions 1 \
    --topic streams-plaintext-input

Create the output topic(output-topic):

bin/kafka-topics.sh --create \
    --bootstrap-server localhost:9092 \
    --replication-factor 1 \
    --partitions 1 \
    --topic streams-wordcount-output \
    --config cleanup.policy=compact

Check that all is ok by listing out all the topics created:

bin/kafka-topics.sh --bootstrap-server localhost:9092 --list

Build your Java project

cd ..
mkdir producer
cd producer
mkdir -p src/main/java
curl https://joelpintomata.com/tutorials/a-to-z-kafka-streams-example-2-producer.java -o src/main/java/Producer.java
curl https://joelpintomata.com/tutorials/a-to-z-kafka-streams-example-2-producer-pom.xml -o pom.xml
mvn clean package
java -jar ./target/kafka-streams-example-2-1.0-SNAPSHOT-jar-with-dependencies.jar

Build your Java project

cd ..
mkdir consumer
cd consumer
mkdir -p src/main/java
curl https://raw.githubusercontent.com/apache/kafka/3.6/streams/examples/src/main/java/org/apache/kafka/streams/examples/wordcount/WordCountDemo.java -o src/main/java/WordCountDemo.java
curl https://joelpintomata.com/tutorials/a-to-z-kafka-streams-example-2-consumer-pom.xml -o pom.xml
mvn clean package
java -jar ./target/kafka-streams-example-2-1.0-SNAPSHOT-jar-with-dependencies.jar

In a third terminal, start a kafka consumer checking the stream process output:

bin/kafka-console-consumer.sh --bootstrap-server localhost:9092 \
    --topic streams-wordcount-output \
    --from-beginning \
    --formatter kafka.tools.DefaultMessageFormatter \
    --property print.key=true \
    --property print.value=true \
    --property key.deserializer=org.apache.kafka.common.serialization.StringDeserializer \
    --property value.deserializer=org.apache.kafka.common.serialization.LongDeserializer

Kafka Streams application Architecture example

Kafka Streams architecture example

Credits to Introduction to Kafka Streams - Akash

Key points:

  • A tasks represents the set your processors that is, the steps your application applies to the stream
  • When the application starts it creates a number of tasks are equal to the number of partitions
  • When the application starts it balances the number of tasks along the number of application threads
  • The moment another application starts Kafka balances the amoung of tasks along the number of applications.

Failover/fault_tolerance considerations

  • Kafka relies on change compacted topic to speed up recoveries. change compacted topics are compacted so that theres a unique value per key meaning, each key contains the last value.
  • Kafka relies on change logs that one can query via API