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Interview Questions and Answers

Know the top Apache Kafka interview questions and answers for freshers and experienced candidates to prepare for job interviews.

Total 38 questions Interview Questions and Answers

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Know the top Apache Kafka interview questions and answers for freshers and experienced candidates to prepare for job interviews.

Interview Questions and Answers

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Intermediate / 1 to 5 years experienced level questions & answers

Ques 1

Explain the role of the offset.

There is a sequential ID number given to the messages in the partitions what we call, an offset. So, to identify each message in the partition uniquely, we use these offsets.
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Ques 3

What is the process for starting a Kafka server?

It is the very important step to initialize the ZooKeeper server because Kafka uses ZooKeeper. So, the process for starting a Kafka server is:
  • In order to start the ZooKeeper server: > bin/zookeeper-server-start.sh config/zookeeper.properties
  • Next, to start the Kafka server: > bin/kafka-server-start.sh config/server.properties
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Ques 5

What can you do with Kafka?

It can perform in several ways, such as:
  • In order to transmit data between two systems, we can build a real-time stream of data pipelines with it.
  • Also, we can build a real-time streaming platform with Kafka, that can actually react to the data.
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Ques 7

What is the role of Consumer API?

An API which permits an application to subscribe to one or more topics and also to process the stream of records produced to them is what we call Consumer API.
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Ques 8

Explain the role of Streams API in Kafka?

An API which permits an application to act as a stream processor, and also consuming an input stream from one or more topics and producing an output stream to one or more output topics, moreover, transforming the input streams to output streams effectively, is what we call Streams API.
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Ques 9

What is the role of Connector API?

An API which permits to run as well as build the reusable producers or consumers which connect Kafka topics to existing applications or data systems is what we call the Connector API.
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Ques 10

Why Should we use Apache Kafka Cluster?

In order to overcome the challenges of collecting the large volume of data, and analyzing the collected data we need a messaging system. Hence Apache Kafka came in the story. Its benefits are:
  • It is possible to track web activities just by storing/sending the events for real-time processes.
  • Through this, we can Alert as well as report the operational metrics.
  • Also, we can transform data into the standard format.
  • Moreover, it allows continuous processing of streaming data to the topics.
Due to its this wide use, it is ruling over some of the most popular applications like ActiveMQ, RabbitMQ, AWS etc.
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Ques 11

What is Data Log in Kafka?

As we know, messages are retained for a considerable amount of time in Kafka. Moreover, there is flexibility for consumers that they can read as per their convenience. Although, there is a possible case that if Kafka is configured to keep messages for 24 hours and possibly that time consumer is down for time greater than 24 hours, then the consumer may lose those messages. However, still, we can read those messages from last known offset, but only at a condition that the downtime on part of the consumer is just 60 minutes. Moreover, on what consumers are reading from a topic Kafka doesn’t keep state.
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Ques 12

Explain how to Tune Kafka for Optimal Performance.

So, ways to tune Apache Kafka it is to tune its several components:
  • Tuning Kafka Producers
  • Kafka Brokers Tuning 
  • Tuning Kafka Consumers
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Ques 14

Enlist all Apache Kafka Operations.

Apache Kafka Operations are:
  • Addition and Deletion of Kafka Topics
  • How to modify the Kafka Topics
  • Distinguished Turnoff
  • Mirroring Data between Kafka Clusters
  • Finding the position of the Consumer
  • Expanding Your Kafka Cluster
  • Migration of Data Automatically
  • Retiring Servers
  • Datacenters
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Ques 15

Explain Apache Kafka Use Cases?

Apache Kafka has so many use cases, such as:
  • Kafka Metrics: It is possible to use Kafka for operational monitoring data. Also, to produce centralized feeds of operational data, it involves aggregating statistics from distributed applications.
  • Kafka Log Aggregation: Moreover, to gather logs from multiple services across an organization.
  • Stream Processing: While stream processing, Kafka’s strong durability is very useful.
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Ques 16

What role does ZooKeeper play in a cluster of Kafka?

Apache ZooKeeper acts as a distributed, open-source configuration and synchronization service, along with being a naming registry for distributed applications. It keeps track of the status of the Kafka cluster nodes, as well as of Kafka topics, partitions, etc.

Since the data is divided across collections of nodes within ZooKeeper, it exhibits high availability and consistency. When a node fails, ZooKeeper performs an instant failover migration.

ZooKeeper is used in Kafka for managing service discovery for Kafka brokers, which form the cluster. ZooKeeper communicates with Kafka when a new broker joins, when a broker dies, when a topic gets removed, or when a topic is added so that each node in the cluster knows about these changes. Thus, it provides an in-sync view of the Kafka cluster configuration.

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Ques 17

Elaborate the architecture of Kafka.

In Kafka, a cluster contains multiple brokers since it is a distributed system. Topic in the system will get divided into multiple partitions, and each broker stores one or more of those partitions so that multiple producers and consumers can publish and retrieve messages at the same time.
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