Kafka is an open-source stream process platform by Apache Software Foundation. It has been written in Java and Scala. Kafka aims to offer a platform to handle real-time data feeds. It can also tackle trillions of events regularly.
Now that you know what is Kafka, we are going to move on to the top Kafka interview questions that will help you ace your interview.
Top 10 Kafka Interview Questions
- What are the Most Impressive Features of Kafka?
The key features of Kafka are given below-
- It is a messaging system created for high throughput and fault tolerance
- The topic is its built-in patriation system.
- It includes a replication feature.
- There is a queue, which can handle a significant amount of data and shift messages from one sender to the other
- Apache Spark is supported well Kafka
- To synchronize and coordinate with other services, Kafka joins hands with Zookeeper.
- It saves the messages to storage and then replicates them across the cluster.
- How are Partitions Distributed in a Kafka Cluster?
A topic’s partitions are distributed across servers present in the Kafka cluster. Every server manages the data and then requests with its own share of partitions. For ascertaining fault tolerance, partitions can be replicated across many servers. Each partition comes with a server, which serves as the partition’s leader. It is the leader that manages all the requests of reading and writing for a certain partition. A leader might have zero or more followers, and they replicate the leader passively. If the leader fails, one of the followers adopts the role of the leader.
- What is Zookeeper, and How can you Use Kafka without Zookeeper?
It is one of the basic interview questions that is asked in an interview. Zookeeper helps with distributed applications that are adapted by Kafka. With this, Kafka can manage all sources easily. Zookeeper is a high-performance and open-source platform that offers a complete coordination service.
You cannot skip Zookeeper and then go over to Kafka broker directly. All Kafka resources are handled by Zookeeper and thus, in case Zookeeper is down, it is not going to serve any client service request. The primary task of the Zookeeper is to serve as the channel of communication for various nodes that are present in a cluster. Kafka’s Zookeeper is used for committing to the offset. In case a node fails, you can easily retrieve from the offset that had been committed previously. Also, the Zookeeper takes care of activities, such as distributed synchronization, detection, configuration management, etc. Using this, it can identify the new nodes, which join or leave the cluster nodes.
- What are the APIs Provided by Apache Kafka?
Apache Kafka mainly has four APIs-
- Connector API: It is used for connecting applications to the topics of Kafka. Connector API offers features to manage the running of consumers and producers and handle the connections between them.
- Producer API: It lets applications publish messages as a stream of records to Kafka topics.
- Streams API: It enables applications to process data as a stream processing paradigm. Streams API can receive data as input streams for Kafka topics, process the streams, and send out the output streams to Kafka topics.
- Consumer API: It lets applications subscribe to Kafka topics. Also, it lets applications process message streams, which are produced to the topic.
- What is the Retention Period on Kafka Cluster?
Messages, which are sent to Kafka clusters are appended to one of the logs. Even after the messages are consumed, the messages remain in the logs for a specific period of time or till the time a configurable size is attained. The time period for which the message stays in the log is called the retention period. This message is available for a specific period of time that is mentioned by the retention period. Kafka lets users configure the message’s retention period on a per-topic basis. 7 days is the default retention period.
- What are Users or Consumers?
Kafka offers single-consumer abstractions, which discover publish-subscribe and queuing consumer groups. It tags itself to a user group, and each communication present on a topic is distributed to a use case within every user group. User instances are present in the disconnected process. You can decide on the consumer’s messaging model depending on the consumer groups.
- In case the consumer instance comes with the same consumer set, it will use the conventional queue to adjust load over the consumers.
- In case the customer instance comes with a different consumer group, it works as a publish-subscribe system, and the messages are sent to the consumers.
- What is the Difference Between Replica and Partition of a Topic in Kafka Cluster?
Partitions are single fragments of the Kafka theme. The total partitions in every subject are adjustable. Added divisions offer greater parallelism in studying the subjects. The number of divisions present in the consumer group has an impact on the group of consumers.
Replicas are partition duplicates. They are not read to or addressed. The primary purpose is to offer redundancy for data. If a subject has n copies, n-1 brokers might fail without leading to data loss. Moreover, no subject will be able to have a factor of replication larger than the total brokers.
- What is the Difference Between Flume and Kafka?
The primary use case of Flume is to ingest data in Hadoop. It is integrated with the monitoring system of Hadoop, file system, file types, and tools, like Morphlines. The Flume is the perfect solution when you work with sources of non-relational data or when you stream a big file into Hadoop.
The main application of Kafka is as the publish-subscribe messaging service. It had not been designed considering Hadoop and using Kafka to collect, and analyze data to Hadoop is more complicated than with Flume.
Kafka is used when a highly scalable and dependable corporate messaging system has to link several systems, like Hadoop.
- How is the Kafka Server Load-Balanced?
As the primary responsibility of the leader is to manage all write and read queries for the partitioning, followers copy the leaders. Thus, when the leader is incapacitated, the followers usurp the position of the leader. This whole procedure guarantees that the load of the server is balanced.
- What are Some of the Disadvantages of using it?
It is one of the most common Kafka interview questions. So, the disadvantages of Kafka are as follows.
- Kafka performance can degrade in the case of message tweaking. If a message doesn’t have to be updated, Kafka will work well.
- Consumers and consumers can reduce the performance of Kafka when it is dealing with large messages by compressing and then decompressing the messages. It affects Kafka’s performance and throughput.
- Kafka doesn’t have a whole set of monitoring tools.
- Some message paradigms, such as point-to-point requests, and queues aren’t supported by Kafka.
The Kafka interview questions given above will help you to qualify for an interview. When you prepare for an interview, make sure that you go through some advanced questions, such as performance tuning.
With the increasing popularity of Apache Kafka, more and more companies are considering hiring trained professionals.