Kafka — Partitioning

In this series of blog post on Kafka, we will take a deep dive into what is partitioning, how it works, and its pros and cons. In end I’ll also share some commands which are handy for troubleshooting.

Also, checkout following related posts

• Kafka — Consumer Group

Apache Kafka is a distributed streaming platform that uses a publish-subscribe model to handle high volume real-time data feeds. In Kafka, the data is divided into a series of topics, which are then divided into partitions. These partitions are the key to Kafka’s high throughput and scalability, as they allow data to be distributed across multiple nodes in a cluster.

What is Kafka Partitioning?

Kafka partitioning is the process of dividing a topic into multiple partitions. A partition is a log that contains a sequence of messages. Each message is identified by an offset, which is a unique identifier within the partition. The partitions are stored on different nodes within the Kafka cluster, which enables data to be processed and stored in parallel. A topic in Kafka is divided into one or more partitions, which are essentially individual log files. Each partition is an ordered, immutable sequence of messages that are assigned a sequential id called an offset.

How does Kafka Partitioning Work?

When a producer sends a message to a Kafka topic, it specifies the partition to which the message should be written. If the producer does not specify a partition, Kafka assigns the message to a partition using a partitioning algorithm. Kafka uses a hash-based partitioner by default, which distributes messages evenly across all available partitions.

Once a message is written to a partition, it is stored in a log file on the Kafka broker. The messages in the log file are ordered by their offset within the partition, which allows consumers to read the messages in order.

Pros of Kafka Partitioning

Scalability:

Partitioning allows Kafka to scale to handle large volumes of data by distributing the data across multiple nodes.

Partitions allow for easy horizontal scaling of Kafka clusters to handle increasing data volumes.

Parallel processing:

By storing data in multiple partitions, Kafka can process the data in parallel, which improves performance and reduces latency.

Reliability:

Kafka replication ensures that data is available even if a broker fails. If a broker fails, the replicas of the partitions stored on that broker are automatically moved to another broker.

Cons of Kafka Partitioning

Complexity:

Partitioning adds complexity to the Kafka system, as it requires a partitioning strategy and the ability to manage multiple partitions. Managing partition replication and leader election can be complex and requires careful configuration.

Data skew:

If a partitioning strategy is not carefully designed, it can lead to data skew, where some partitions may receive more data than others. This can lead to performance issues.

Reassigning Kafka partitions

Reassigning partitions is the process of moving partitions between brokers in a Kafka cluster. This is done to balance the load on the brokers and to ensure that data is stored in the most efficient way.

Reassigning partitions can be done using the Kafka command-line tool or through the Kafka API. When a partition is reassigned, Kafka will move the replicas of the partition to the new broker and update the partition metadata on the Kafka cluster.

Useful Commands

List Partition:

bin/kafka-topics.sh --describe --zookeeper <zookeeper_ip>:2181 --topic <topic_name>

Reassign partition:

Create a json file with following format

{
  "partitions": 
    [
      {"topic": "<topic_name>", "partition": 0, "replicas": [0,10]},
      {"topic": "<topic_name>", "partition": 1, "replicas": [10,20]},
      {"topic": "<topic_name>", "partition": 2, "replicas": [20,0]},
      {"topic": "<topic_name>", "partition": 3, "replicas": [0,10]},
      {"topic": "<topic_name>", "partition": 4, "replicas": [10,20]},
      {"topic": "<topic_name>", "partition": 5, "replicas": [20,0]}
    ],
  "version":1
}

Run following command to execute created json

/bin/kafka-reassign-partitions.sh - zookeeper <zookeeper_ip>:2181 -reassignment-json-file partitions.json -execute

In conclusion, Kafka partitioning is a key feature of the Kafka streaming platform, which enables scalability, parallel processing, and reliability. However, it also adds complexity to the system, and requires careful planning to avoid data skew. Reassigning partitions is a useful tool for balancing the load on the Kafka brokers and ensuring efficient data storage.