1. Overview

When a producer sends a message to Apache Kafka, it appends it in a log file and retains it for a configured duration.

In this tutorial, we’ll learn to configure time-based message retention properties for Kafka topics.

2. Time-Based Retention

With retention period properties in place, messages have a TTL (time to live). Upon expiry, messages are marked for deletion, thereby freeing up the disk space.

The same retention period property applies to all messages within a given Kafka topic. Furthermore, we can set these properties either before topic creation or alter them at runtime for a pre-existing topic.

In the following sections, we’ll learn how to tune this through broker configuration for setting the retention period for new topics and topic-level configuration to control it at runtime.

3. Server-Level Configuration

Apache Kafka supports a server-level retention policy that we can tune by configuring exactly one of the three time-based configuration properties:

  • log.retention.hours
  • log.retention.minutes
  • log.retention.ms

It’s important to understand that Kafka overrides a lower-precision value with a higher one. So, log.retention.ms would take the highest precedence.

3.1. Basics

First, let’s inspect the default value for retention by executing the grep command from the Apache Kafka directory:

$ grep -i 'log.retention.[hms].*\=' config/server.properties
log.retention.hours=168

We can notice here that the default retention time is seven days.

To retain messages only for ten minutes, we can set the value of the log.retention.minutes property in the config/server.properties:

log.retention.minutes=10

3.2. Retention Period for New Topic

The Apache Kafka package contains several shell scripts that we can use to perform administrative tasks. We’ll use them to create a helper script, functions.sh, that we’ll use during the course of this tutorial*.*

Let’s start by adding two functions in functions.sh to create a topic and describe its configuration, respectively:

function create_topic {
    topic_name="$1"
    bin/kafka-topics.sh --create --topic ${topic_name} --if-not-exists \
      --partitions 1 --replication-factor 1 \
      --zookeeper localhost:2181
}

function describe_topic_config {
    topic_name="$1"
    ./bin/kafka-configs.sh --describe --all \
      --bootstrap-server=0.0.0.0:9092 \
      --topic ${topic_name}
}

Next, let’s create two standalone scripts, create-topic.sh and get-topic-retention-time.sh:

bash-5.1# cat create-topic.sh
#!/bin/bash
. ./functions.sh
topic_name="$1"
create_topic "${topic_name}"
exit $?
bash-5.1# cat get-topic-retention-time.sh
#!/bin/bash
. ./functions.sh
topic_name="$1"
describe_topic_config "${topic_name}" | awk 'BEGIN{IFS="=";IRS=" "} /^[ ]*retention.ms/{print $1}'
exit $?

We must note that describe_topic_config will give all the properties configured for the topic. So, we used the awk one-liner to add a filter for the retention.ms property.

Finally, let’s start the Kafka environment and verify retention period configuration for a new sample topic:

bash-5.1# ./create-topic.sh test-topic
Created topic test-topic.
bash-5.1# ./get-topic-retention-time.sh test-topic
retention.ms=600000

Once the topic is created and described, we’ll notice that retention.ms* is set to *600000 (ten minutes). That’s actually derived from the log.retention.minutes property that we had earlier defined in the server.properties file.

4. Topic-Level Configuration

Once the Broker server is started, log.retention.{hours|minutes|ms} server-level properties become read-only. On the other hand, we get access to the retention.ms property, which we can tune at the topic-level.

Let’s add a method in our functions.sh script to configure a property of a topic:

function alter_topic_config {
    topic_name="$1"
    config_name="$2"
    config_value="$3"
    ./bin/kafka-configs.sh --alter \
      --add-config ${config_name}=${config_value} \
      --bootstrap-server=0.0.0.0:9092 \
      --topic ${topic_name}
}

Then, we can use this within an alter-topic-config.sh script:

#!/bin/sh
. ./functions.sh

alter_topic_retention_config $1 $2 $3
exit $?

Finally, let’s set retention time to five minutes for the test-topic and verify the same:

bash-5.1# ./alter-topic-config.sh test-topic retention.ms 300000
Completed updating config for topic test-topic.

bash-5.1# ./get-topic-retention-time.sh test-topic
retention.ms=300000

5. Validation

So far, we’ve seen how we can configure the retention period of a message within a Kafka topic. It’s time to validate that a message indeed expires after the retention timeout.

5.1. Producer-Consumer

Let’s add produce_message and consume_message functions in the functions.sh. Internally, these use the kafka-console-producer.sh and kafka-console-consumer.sh, respectively, for producing/consuming a message:

function produce_message {
    topic_name="$1"
    message="$2"
    echo "${message}" | ./bin/kafka-console-producer.sh \
    --bootstrap-server=0.0.0.0:9092 \
    --topic ${topic_name}
}

function consume_message {
    topic_name="$1"
    timeout="$2"
    ./bin/kafka-console-consumer.sh \
    --bootstrap-server=0.0.0.0:9092 \
    --from-beginning \
    --topic ${topic_name} \
    --max-messages 1 \
    --timeout-ms $timeout
}

We must note that the consumer is always reading messages from the beginning as we need a consumer that reads any available message in Kafka.

Next, let’s create a standalone message producer:

bash-5.1# cat producer.sh
#!/bin/sh
. ./functions.sh
topic_name="$1"
message="$2"

produce_message ${topic_name} ${message}
exit $?

Finally, let’s have a standalone message consumer:

bash-5.1# cat consumer.sh
#!/bin/sh
. ./functions.sh
topic_name="$1"
timeout="$2"

consume_message ${topic_name} $timeout
exit $?

5.2. Message Expiry

Now that we have our basic setup ready, let’s produce a single message and consume it twice instantly:

bash-5.1# ./producer.sh "test-topic-2" "message1"
bash-5.1# ./consumer.sh test-topic-2 10000
message1
Processed a total of 1 messages
bash-5.1# ./consumer.sh test-topic-2 10000
message1
Processed a total of 1 messages

So, we can see that the consumer is repeatedly consuming any available message.

Now, let’s introduce a sleep delay of five minutes and then attempt to consume the message:

bash-5.1# sleep 300 && ./consumer.sh test-topic 10000
[2021-02-06 21:55:00,896] ERROR Error processing message, terminating consumer process:  (kafka.tools.ConsoleConsumer$)
org.apache.kafka.common.errors.TimeoutException
Processed a total of 0 messages

As expected, the consumer didn’t find any message to consume because the message has crossed its retention period.

6. Limitations

Internally, the Kafka Broker maintains another property called log.retention.check.interval.ms. This property decides the frequency at which messages are checked for expiry.

So, to keep the retention policy effective, we must ensure that the value of the log.retention.check.interval.ms is lower than the property value of retention.ms for any given topic.

7. Conclusion

In this tutorial, we explored Apache Kafka to understand the time-based retention policy for messages. In the process, we created simple shell scripts to simplify the administrative activities. Later, we created a standalone consumer and producer to validate the message expiry after the retention period.