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KAFKA INTERVIEW QUESTIONS
Here are a few Kafka Interview Questions for you
Which of the following is not a core API in
Kafka
Q 1
Storage
Producer
Streams
Connector
Which node accounts for reads/writes for
Kafka partition
Q 2
Central
Leader
Replicas
Follower
Which of the following is the Message
Broker in SMACK technologies
Q 3
Apache Kafka
Cassandra
Apache Mesos
Apache Spark
Which of the following is a real time
processing system present in Apache
Kafka
Q 4
Which one of the following is not a
component of Apache Kafka
Q 5
Which of the following is a feature of Kafka
architecture
Q 6
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Combined Event Processing
Customer Event Processing
Complex Event Processing
Cluster Event Processing
Broker
Mesos
Zookeeper
Producer
Low Overhead and High Throughput
High Overhear and Low Throughput
Low Overhead and Low Throughput
High Overhead and High Throughput
SUBMIT
Some useful information that will help you brush up on Kafka Interview Questions
If you are not familiar with Kafka or have any query about its installation operation and usability this Apache Kafka
tutorial can truly help you. Here we are explaining all useful information about Apache Kafka that will provide a
clear understanding about it.
What is Apache Kafka
A powerful distributed publish-subscribe messaging system that is designed to replace old message brokers. It was
originally developed by LinkedIn Now Apache Software Foundation currently manage it. Kafka is used for
application streaming and data processing. It is highly scalable fast and fault-tolerant messaging application. Kafka
was originally written in Java and Scala programming language. It is a strong platform for distributed applications.
Current Apache Kafka stable version is 2.0.0. You can download it from ofcial website and documentation is
available.
Messaging System
A messaging system is a medium that transfer data from one application to another. There is two way to send data
from one end to other. First one is a point-to-point messaging system and other is pub-sub Publish-subscribe
messaging system. Most of the application used a pub-sub pattern for messaging.
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Point-to-point messaging system: - In this pattern a message can be consumed by only one consumer. One who
produces a message called sender and other consumers are known as a receiver. A message is consumed by only
one consumer at a time because only one message can be available in the queue.
Pub-sub messaging system: - This is new technology and most of the applications use this pattern for messaging. A
producer is called publisher and consumer is referred as subscriber. In this system message can be received by
several consumers at a time.
Why Kafka is very much popular
Kafka is mostly used in real-time streaming data architectures that gives real-time analytics. As you know Kafka is
very fast and scalable which makes it applicable for things like tracking service calls or tracking IoT sensor data.
Kafka provides an excellent performance that’s why it is very popular. It is stable and scalable that uses Pub-sub
messaging system to send the message. There are other applications which are available that offers similar
functionality but Kafka is very popular because Apache Kafka replicates events using ingest pipelines.
Kafka Use Cases
Kafka is mostly used for tracking website activity stream processing monitoring log aggregation and real-time
analytics.
Apache Kafka Architecture
Apache Kafka is integrated with Apache storm Apache HBase in order to process real-time streaming data. Kafka
is deployed as a cluster implemented many servers. It is capable to store ‘topics’ which include streams of ‘records’ .
Kafka Cluster
Kafka cluster typically consists of multiple brokers to maintain load balance. The brokers are stateless so they use
ZooKeeper for maintaining their own cluster state.
Apache ZooKeeper
Apache ZooKeeper is used to maintain Kafka broker. It is used to notify producer and consumer about new broker
or failure of a broker in Kafka system.
Producer
A producer is used to push data to broker. When a new broker is appeared in apache cluster producer search it and
send the message to broker.
Consumer
A consumer used to receive message by using partition offset.
Kafka architecture basically used four APIs:
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Producer API: - Producer API give permission to the application to publish stream of records to topics.
Consumer API: - It permits an application to subscribe to topics and processes stream of records.
Connector API: - This API executes the reusable consumer and producer APIs that can link to existing applications.
Streams API: - It convert input stream to output. This API takes input from one topic and produce an output to one
or more.
Kafka T opic
Apache Kafka topics built of several partitions. Kafka stores topic in logs a topic log is broken into partitions. Kafka
store log’s partitions across multiple servers. A T opic can have many subscribers that is called as consumer group. It
is broken into partitions for speed and scalability.
Some of the important Interview questions on Kafka
What is Apache Kafka
What are consumers and users
What are the types of traditional method of message transfer
Explain Apache Kafka Use Cases
What is the role of offset
What is the role of ZooKeeper
What is the main difference between Kafka and Flume
What are Replication tools and its types
Explain Different APIs of Kafka
What is the purpose of retention period in Kafka Cluster
What do you know about partition in Kafka
Difference between traditional queuing systems vs Apache Kafka
Difference between point-to-point and pub-sub messaging system.
What is Data log in Kafka
State Disadvantages of Apache Kafka.
Last Word
Kafka is very fast and powerful among all other distributed messaging system. Apache Kafka Installation process is
simple and available on the internet. A fault-tolerant messaging application makes it more popular nowadays.
Some of the many Kafka Interview Questions listed below will help you get an idea about what questions gets asked
in such jobs related to Software Engineering T ech. Get through the Kafka Interview bar with our selected Kafka
Interview Questions for all Kafka enthusiasts
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