Apache Kafka - Introduction

Used by over 70% of the Fortune 500, Apache Kafka has become the foundational platform for data in motion, but self-supporting the open source project puts you in the business of managing low-level data infrastructure. That’s why modern businesses choose Confluent, so they can keep their focus where it matters. With Kafka at its core, Confluent offers a more complete, cloud-native platform to set your data in motion, available everywhere your data and applications reside.

What is Apache Kafka?

Apache Kafka is an open-source distributed streaming platform that allows users to publish and subscribe to streams of records, as well as store and process these records in real-time. Kafka was designed to handle high-volume, high-throughput, and low-latency data streams, making it a popular choice for building real-time data pipelines and applications.

Why use Apache Kafka?

Apache Kafka is widely used for building real-time data pipelines and streaming applications due to its scalability, reliability, and high performance. It allows for the efficient handling of high volume, time-sensitive data in a distributed environment, making it ideal for use cases such as real-time data processing, event-driven architectures, and data streaming. Kafka’s distributed architecture also provides fault tolerance and high availability, ensuring that data is always available and can be processed without interruption.

Key concepts and terminology:

BrokerA single Kafka server that manages and stores messages.
TopicA category or stream name to which messages are published by producers and from which messages are consumed by consumers.
PartitionA partition is a unit of parallelism and scalability in Kafka. Each topic is divided into one or more partitions.
ProducerAn entity that publishes messages to a Kafka topic.
ConsumerAn entity that subscribes to a topic and consumes messages from Kafka.
Consumer GroupA set of consumers that cooperate to consume messages from a topic.
OffsetA unique identifier assigned to each message by Kafka within a partition. It represents the position of a consumer in a partition.
ReplicationThe process of maintaining copies of a partition on multiple brokers.
LeaderThe broker that is currently responsible for handling read and write requests for a specific partition.
FollowerThe broker that replicates the leader’s partition.
ZooKeeperA distributed coordination service used by Kafka for storing metadata information and managing Kafka cluster nodes.
ConnectorA pre-built software that connects Kafka to external data sources or sinks, such as databases, message queues, or data lakes.
Stream ProcessingA real-time data processing approach that allows applications to consume, transform, and produce data continuously as it flows through a stream.
Producer APIA set of APIs that allow applications to produce messages to Kafka.
Consumer APIA set of APIs that allow applications to consume messages from Kafka.
Admin APIA set of APIs that allow administrators to manage Kafka topics, partitions, and consumer groups.
SerdeA serialization/deserialization framework that translates data between binary and structured formats.





Apache Kafka - Getting Started with Kafka

 steps to install and configure Apache Kafka on a Linux-based operating system:

  1. Download the latest version of Apache Kafka from the official website: https://kafka.apache.org/downloads
  2. Extract the downloaded package to a directory of your choice. For example, run the command tar -xzf kafka_2.13-2.8.0.tgz to extract the package.
  3. Navigate to the Kafka directory and open the config/server.properties file in a text editor.
  4. Modify the listeners property to match the IP address and port number of the server. For example, listeners=PLAINTEXT://localhost:9092.
  5. (Optional) Modify other properties such as log.dirs to change the directory where Kafka stores its logs.
  6. Save and close the server.properties file.
  7. Start the Kafka server by running the command bin/kafka-server-start.sh config/server.properties.
  8. Kafka should now be running. You can test it by creating a topic and producing and consuming messages using the Kafka command-line tools.

Creating Kafka topics:

To create a Kafka topic, follow these steps:

Step 1: Open a terminal window and navigate to the Kafka installation directory.

Step 2: Start the ZooKeeper server by running the following command
bin/zookeeper-server-start.sh config/zookeeper.properties
Step 3: Open a new terminal window and start the Kafka server by running the following command:
bin/kafka-server-start.sh config/server.properties
Step 4: Create a Kafka topic by running the following command:
bin/kafka-topics.sh –create –zookeeper localhost:2181 –replication-factor 1 –partitions 1 –topic my-topic
This command creates a topic named “my-topic” with a replication factor of 1 and one partition.
Step 5: Verify that the topic was created by running the following command:
bin/kafka-topics.sh –list –zookeeper localhost:2181
This command lists all the topics available in the Kafka cluster. You should see “my-topic” in the list.
Note: You can customize the replication factor and number of partitions based on your requirements.