How to make a unqiue and deduplicated version of a kafka topic

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If i have a topic in kafka that has messages which use integer as their keys. How to create a topic that is based on this topic but has no duplication and the messages are ordered by its key?

For example, let's say the topic name is "my_topic", and there are 5 messages in this topic:

key: "10", value: "{ value: 15 }"
key: "13", value: "{ value: 40 }"
key: "11", value: "{ value: 30 }"
key: "10", value: "{ value: 15 }"
key: "12", value: "{ value: 20 }"

Then, how to create a "ordered_deduplicated_my_topic" such that it has only 4 messages (becase the messages in are ordered asc by key, and the duplicated "10" was removed):

key: "10", value: "{ value: 15 }"
key: "11", value: "{ value: 30 }"
key: "12", value: "{ value: 20 }"
key: "13", value: "{ value: 40 }"

Latest version of Kafka comes with exactly-once-delivery semantics which aims to write to Kafka exactly-once. If your kafka based solution is in beta phase then I would recommend you to update producers and consumers to use exactly-once-semantics. If you go with exactly-once-semantics then you won't have to worry about it at all.

If you do not have option to use exactly-once-semantics then Effective strategy to avoid duplicate messages in apache kafka consumer might help a little.

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To achieve this, you should set cleanup.policy for this topic to compact, as shown below:

bin/kafka-topics.sh --zookeeper localhost:2181 --create --topic my-topic --partitions 1 --replication-factor 1 --config cleanup.policy=compact

Documentation - Apache Kafka, You're viewing documentation for an older version of Kafka - check out our If all the consumer instances have the same consumer group, then this works just The broker.id property is the unique and permanent name of each node in the cluster. This ratio bounds the maximum space wasted in the log by duplicates ( at� A log for a topic named "my_topic" with two partitions consists of two directories (namely my_topic_0 and my_topic_1) populated with data files containing the messages for that topic. The format of the log files is a sequence of "log entries""; each log entry is a 4 byte integer N storing the message length which is followed by the N message bytes.

I'm new here, so can't reply directly to comments.

This comment is in reference to setting a topic as a compacted topic in order to ensure a unique entry per key in Kafka logs: this would be an incorrect solution. Messages in compacted topics will still exist for a time until Kafka actually marks them for deletion (tombstones), and then actually removes them over time. This time is, by default, a ratio of dirty messages it cleans from time to time.

You can see and configure the clean ratio here: https://docs.confluent.io/current/installation/configuration/topic-configs.html#min.cleanable.dirty.ratio

You can also in effect configure how long messages are retained in a compacted log, similar to how default topics work, but ensuring the latest occurrence of a key always remains: https://docs.confluent.io/current/installation/configuration/topic-configs.html#min.compaction.lag.ms

The main caveat here, though, is to understand that compacted topics do not automatically remove old keys. They will actually keep them for a while longer, and even if we configure it to be very aggressive in getting rid of older messages, this is actually not advisable, because it can have multiple side effects, such as slow consumers, that suddenly lost their pointer (deleted), or even performance issues. This is a log after all, and removing ad-hoc entries is costly and time consuming.

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Comments
  • Possible duplicate of Log compaction to keep exactly one message per key
  • Messages in Kafka are ordered per partition based on the offset. You can't order them in topic based on key or value. What is your use case for ordering? If you describe it more precisely, than maybe some functionalities of Kafka Streams might be useful.
  • only way would be to 1) use Kafka streams to filter duplicates and order and publish 2) do it manually in the consumer and produce again to the new topic. You may want to look at in memory compaction offered by Kafka streams on the consumer side which can achieve deduplication. But here we are talking about key deduplication only. Deduping based on value content is possible only with some application logic
  • he doesn't say that his duplicate records are due to duplicate publishing. What if they are indeed two separate events, but just happen to have same key and values?