For java developers top kafka interview questions for freshers and experienced we have covered most asked kafka interview questions
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What is Apache Kafka?
Its a publish-subscribe based durable messaging system, exchanging data between processes, applications, and servers.
Apache Kafka, created by former LinkedIn data engineers and written in Scala and Java, became an open-source technology in 2011. It started as a highly scalable messaging system and is now a crucial part of the Confluent Stream Platform, managing trillions of events daily. Many well-known companies trust and use Apache Kafka.
In real time, managing data and logs is a big task. This involves processing, reprocessing, analyzing, and handling information, often in real-time. This is where Apache Kafka shines. It plays a significant role in handling messages efficiently in a streaming environment. The principles behind Kafka's design focus on meeting the increasing demand for systems that can handle a large volume of data
Architecture of kafka
The architecture of Apache Kafka is designed for distributed, fault-tolerant, and scalable handling of streaming data.
Let's explore the key components and their interactions in detail:
Producer
Producers are applications that publish messages to Kafka topics. They create ProducerRecord like this public ProducerRecord
Topic:
Topics are logical channels or categories to which messages are published. Topics can be divided into partitions for scalability and parallelism.
Partition:
Each topic is divided into partitions, which are the basic units of parallelism. Partitions allow Kafka to distribute and parallelize the processing of messages.
Broker:
Responsibility: Kafka brokers are individual servers within the Kafka cluster. They store and manage data, handle producer and consumer requests, and participate in the replication and distribution of data.
ZooKeeper:
Responsibility: ZooKeeper is used for distributed coordination and management of the Kafka cluster. It maintains metadata, leader election, and helps manage the overall state of the cluster.
Topic Partitions Replication:
Responsibility: Each partition has multiple replicas for fault tolerance. Replicas are distributed across different brokers. One replica is designated as the leader, and the others are followers.
Consumer:
Responsibility: Consumers subscribe to one or more topics and consume messages from partitions. Each consumer group can have multiple consumers, and each consumer within a group processes a specific subset of partitions.
Why did you use Kafka?
Scalability
Fault Tolerance
Durability
Real-time Stream Processing
Partitioning
High Throughput
Data Retention Policies
Dynamic Reconfiguration
Community and Support
What is the role of the ZooKeeper in Kafka
ZooKeeper acts as a centralized and reliable coordination service for Kafka, ensuring that the distributed components of a Kafka cluster can work together seamlessly.
It helps in managing the dynamic nature of Kafka clusters, providing fault tolerance, and enabling coordination among different components.
It's worth noting that starting with Kafka version 2.8.0, there have been efforts to reduce Kafka's dependency on ZooKeeper, with ongoing work to replace it with a self-managed metadata store. Its said that with kafka 4.x it will be completely removed while with 3.x its removed but still its not prod ready.
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