Within the 9 years since its launch in 2011, Kafka has established itself as some of the beneficial instruments for knowledge processing within the technological sphere. Airbnb, Goldman Sachs, Netflix, LinkedIn, Microsoft, Goal and The New York Instances are just some firms constructed on Kafka. 

However what’s Kafka? The straightforward reply to that may be — it’s what helps an Uber driver match with a possible passenger or assist LinkedIn carry out thousands and thousands of real-time analytical or predictable companies. Briefly, Apache is a extremely scalable, open-sourced, fault-tolerant distributed occasion streaming platform created by LinkedIn in 2011. It makes use of a commit log you possibly can subscribe to, which may then be printed on a lot of streaming purposes. 

Its low latency, knowledge integration and excessive throughput contribute to its rising recognition, a lot in order that an experience in Kafka is taken into account to be a glowing addition to a candidate’s resume and professionals with a licensed qualification in it are in excessive demand in the present day. This has additionally resulted in a rise in job alternatives centered round Kafka. 

On this article, we now have compiled a listing of Kafka interview questions and solutions which can be probably to come back up in your subsequent interview session. You may wish to look these as much as brush up your information earlier than you go in to your interview. So, right here we go!

High 11 Kafka Interview Questions and Solutions

 1. What’s Apache Kafka?

Kafka is a free, open-source knowledge processing device created by Apache Software program Basis. It’s written in Scala and Java, and is a distributed, real-time knowledge retailer designed to course of streaming knowledge. It provides a excessive throughput engaged on a good {hardware}.

When hundreds of information sources constantly ship knowledge data on the identical time, streaming knowledge is generated. To deal with this streaming knowledge, a streaming platform would want to course of this knowledge each sequentially and incrementally whereas dealing with the continuous inflow of information. 

Kafka takes this incoming knowledge inflow and builds streaming knowledge pipelines that course of and transfer knowledge from system to system. 

Features of Kafka:

  • It’s liable for publishing streams of information data and subscribing to them
  • It handles efficient storage of information streams within the order that they’re generated
  • It takes care of real-time days processing 

Makes use of of Kafka:

  • Information integration
  • Actual-time analytics 
  • Actual-time storage
  • Message dealer answer
  • Fraud detection
  • Inventory buying and selling

2. Why Do We Use Kafka?

Apache Kafka serves because the central nervous system making streaming knowledge obtainable to all streaming purposes (an utility that makes use of streaming knowledge known as a streaming utility). It does so by constructing real-time pipelines of information which can be liable for processing and transferring knowledge between totally different techniques that want to make use of it. 

Kafka acts as a message dealer system between two purposes by processing and mediating communication. 

It has a various vary of makes use of which embrace messaging, processing, storing, transportation, integration and analytics of real-time knowledge. 

3. What are the important thing Options of Apache Kafka? 

The salient options of Kafka embrace the next:

1. Sturdiness – Kafka permits seamless help for the distribution and replication of information partitions throughout servers that are then written to disk. This reduces the prospect of servers failing, makes the info persistent and tolerant of faults and will increase its sturdiness. 

2. Scalability – Kafka could be disturbed and changed throughout many servers which make it extremely scalable, past the capability of a single server. Kafka’s knowledge partitions don’t have any downtime as a result of this. 

3. Zero Information Loss – With correct help and the fitting configurations, the lack of knowledge could be lowered to zero. 

4. Velocity – Since there may be extraordinarily low latency because of the decoupling of information streams, Apache Kafka may be very quick. It’s used with Apache Spark, Apache Apex, Apache Flink, Apache Storm, and many others, all of that are real-time exterior streaming purposes. 

5. Excessive Throughput & Replication – Kafka has the capability to help thousands and thousands of messages that are replicated throughout a number of servers to offer entry to a number of subscribers. 

4. How does Kafka Work?

Kafka works by combining two messaging fashions, thereby queuing them, and publishing and subscribing to them so it may be made accessible to many shopper cases. 

Queuing promotes scalability by permitting knowledge to be processed and distributed to a number of shopper servers. Nonetheless, these queues usually are not match to be multi-subscribers. That is the place the publishing and subscribing method steps in. Nonetheless, since each message occasion would then be despatched to each subscriber, this method can’t be used for the distribution of information throughout a number of processes. 

Subsequently, Kafka employs knowledge partitions to mix the 2 approaches. It makes use of a partitioned log mannequin by which every log, a sequence of information data, is cut up into smaller segments (partitions), to cater to a number of subscribers. 

This allows totally different subscribers to have entry to the identical matter, making it scalable since every subscriber is supplied a partition. 

Kafka’s partitioned log mannequin can also be replayable, permitting totally different purposes to perform independently whereas nonetheless studying from knowledge streams. 

5. What are the Main 4 Elements of Kafka? 

There are 4 elements of Kafka. They’re:

– Subject

– Producer

– Brokers

– Shopper

Subjects are streams of messages which can be of the identical sort. 

Producers are able to publishing messages to a given matter.

Brokers are servers whereby the streams of messages printed by producers are saved. 

Customers are subscribers that subscribe to matters and entry the info saved by the brokers.

6. What number of APIs does Kafka Have? 

Kafka has 5 principal APIs that are:

Producer API: liable for publishing messages or stream of data to a given matter.

– Shopper API: often known as subscribers of matters that pull the messages printed by producers.

– Streams API: permits purposes to course of streams; this includes processing any given matter’s enter stream and reworking it to an output stream. This output stream might then be despatched to totally different output matters.

– Connector API: acts as an automating system to allow the addition of various purposes to their present Kafka matters.

– Admin API: Kafka matters are managed by the Admin API, as are brokers and a number of other different Kafka objects. 

7. What’s the Significance of the Offset?

The distinctive identification quantity that’s allotted to messages saved in partitions is called the Offset. An offset serves as an identification quantity for each message contained in a partition. 

8. Outline a Shopper Group.

When a bunch of subscribed matters are collectively consumed by multiple shopper, it’s referred to as a Shopper Group. 

9. Clarify the Significance of the Zookeeper. Can Kafka be used With out Zookeeper?

Offsets (distinctive ID numbers) for a specific matter in addition to partitions consumed by a specific shopper group are saved with the assistance of Zookeeper. It serves because the coordination channel between customers. It’s inconceivable to make use of Kafka that doesn’t have Zookeeper. It makes the Kafka server inaccessible and shopper requests can’t be processed if the Zookeeper is bypassed. 

10. What do Chief and Follower In Kafka Imply? 

Every of the partitions in Kafka are assigned a server which serves because the Chief. Each learn/write request is processed by the Chief. The position of the Followers is to observe within the footsteps of the Chief. If the system causes the Chief to fail, one of many Followers will cease replicating and fill in because the Chief to handle load balancing. 

11. How do You Begin a Kafka Server?

Earlier than you begin the Kafka server, energy up the Zookeeper. Comply with the steps beneath: 

Zookeeper Server: 

> bin/zookeeper-server-start.sh config/zookeeper.properties

Kafka Server:

bin/kafka-server-start.sh config/server.properties


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