Apache Zookeeper Interview Questions

Top Kafka Interview Questions and Answers- Ace your next big data/data engineer job interview | ProjectPro Last Updated: 12 Jan 2023

Your search for Apache Kafka interview questions ends right here! This blog brings you the most popular Kafka interview questions and answers divided into various categories such as Apache Kafka interview questions for beginners, Advanced Kafka interview questions/Apache Kafka interview questions for experienced, Apache Kafka Zookeeper interview questions, etc.

9 How can we create Znodes?

Znodes are created within the given path.


Flags can be used to specify whether the znode created will be persistent, ephemeral, or sequential.

All znodes are persistent by default.

What is the role of the ZooKeeper in Kafka?

Apache Kafka is a distributed system built to use Zookeeper. Although, Zookeeper’s central role here is to make coordinate between different nodes in a cluster. However, we also use Zookeeper to recover from previously committed offset if any node fails because it works as a periodically commit offset.

What are topics in Apache Kafka?

A stream of messages that belong to a particular category is called a topic in Kafka. Kafka stores data in topics that are split into partitions.

The Market Demand for Kafka Skills

According to HG insights, there are over 18,000 companies that use Apache Kafka, and 3729 developers on StackShare have mentioned that they use Apache Kafka.

  • Twitter uses Apache Storm and Apache Kafka as an integral part of it’s stream processing infrastructure.
  • Kafka was originally created by LinkedIn for the purpose of monitoring and tracking user activity stream data and calculating operational metrics. Kafka messaging system is an integral part of LinkedIns popular products like LinkedIn today and LinkedIn Newsfeed.LinkedIn maintains over 100 Kafka clusters with over 4K brokers that serve 100,000+ topics and 7M partitions. Kafka deployments at LinkedIn handle over 7 trillion messages every day.
  • Netflix uses Kafka for real-time monitoring and event processing.
  • Oracle provides native connectivity to Kafka from its Enterprise Service Bus product, which it calls OSB or Oracle Service Bus. This allows developers to use built-in features of OSB to implement staged data pipelines.
  • Companies like Uber, PayPal, Spotify, Goldman Sachs, Tinder, Pinterest, and Tumbler also use Kafka stream processing and message passing features and claim Kafka technology to be one of the most popular big data tools in the world.

    8 Explain customer serialization and deserialization in Kafka.

    In Kafka, message transfer among the producer, broker, and consumers is done by making use of a standardized binary message format. The process of converting the data into a stream of bytes for the purpose of the transmission is known as serialization. Deserialization is the process of converting the bytes of arrays into the desired data format. Custom serializers are used at the producer end to let the producer know how to convert the message into byte arrays. Deserializers are used at the consumer end to convert the byte arrays back into the message.

    1 What are some differences between Apache Kafka and Flume?

    Apache Kafka and Flume are distributed data systems, but there is a certain difference between Kafka and Flume in terms of features, scalability, etc. The below table lists all the major differences between Apache Kafka and Flume-

    Apache Kafka

    Apache Flume

    Kafka is optimized to ingest data and process streaming data in real-time.

    Flume is mainly used for collecting and aggregating large amounts of log data from multiple sources to a centralized data location.

    Easy to scale.

    Not as easy to scale as Kafka.

    It can be supported across various applications.

    Specifically designed for Hadoop.

    Apache Kafka runs as a cluster and supports automatic recovery if resilient to node failure.

    Tool to collect log data from distributed web servers.

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