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Apache Kafka Quiz
The only purpose of this Apache Kafka MCQS with Answers is to challenge your expertise and to learn new topics in one place. Whereas, you can note that the questions which we have accommodated here were the Top 45 Apache Kafka Multiple Choice Questions that are been asked frequently in the placement tests or interview. Hence now, dive into the below sections to give a try for the Apache Kafka MCQ Quiz.
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Apache Kafka Quiz – Overview
| Quiz Name | Apache Kafka |
| Exam Type | MCQ (Multiple Choice Questions) |
| Category | Technical Quiz |
| Mode of Quiz | Online |
Top 45 Apache Kafka Multiple Choice Questions
1. What is Apache Kafka?
a. A database management system
b. A streaming platform
c. A web server
d. A programming language
Answer: b. A streaming platform
Explanation: Apache Kafka is an open-source streaming platform that is designed to handle real-time data streaming. It allows applications to publish, subscribe, and process streams of records in a fault-tolerant and scalable way.
2. What is the main use case of Apache Kafka?
a. Data storage
b. Data processing
c. Data streaming
d. Data analysis
Answer: c. Data streaming
Explanation: Apache Kafka is primarily used for data streaming. It allows applications to process and analyze real-time data streams, making it ideal for use cases such as real-time analytics, log processing, and event-driven architectures.
3. What is a Kafka topic?
a. A data record
b. A stream of data records
c. A collection of data streams
d. A message queue
Answer: c. A collection of data streams
Explanation: A Kafka topic is a collection of data streams that share a common identifier. Each stream is made up of data records or messages that are published to the topic by producers and consumed from the topic by consumers.
4. What is a Kafka producer?
a. An application that publishes data to Kafka topics
b. An application that consumes data from Kafka topics
c. An application that stores data in Kafka
d. An application that analyzes data in Kafka
Answer: a. An application that publishes data to Kafka topics
Explanation: A Kafka producer is an application that publishes data to Kafka topics. Producers send data in the form of records or messages to Kafka topics, which can then be consumed by one or more consumers.
5. What is a Kafka consumer?
a. An application that publishes data to Kafka topics
b. An application that consumes data from Kafka topics
c. An application that stores data in Kafka
d. An application that analyzes data in Kafka
Answer: b. An application that consumes data from Kafka topics
Explanation: A Kafka consumer is an application that consumes data from Kafka topics. Consumers read data in the form of records or messages from Kafka topics, which are produced by one or more producers.
6. What is a Kafka broker?
a. An application that manages Kafka producers
b. An application that manages Kafka consumers
c. An application that manages Kafka topics
d. An application that manages Kafka clusters
Answer: d. An application that manages Kafka clusters
Explanation: A Kafka broker is an application that manages a Kafka cluster. A Kafka cluster is made up of one or more brokers that work together to store and distribute data across topics and partitions.
7. What is a Kafka partition?
a. A collection of data streams within a topic
b. A single stream of data records within a topic
c. A message queue within a topic
d. A group of Kafka brokers within a cluster
Answer: b. A single stream of data records within a topic
Explanation: A Kafka partition is a single stream of data records within a topic. Each partition is made up of an ordered sequence of data records that can be consumed by one or more consumers in parallel.
8. What is a Kafka offset?
a. A unique identifier for a message within a partition
b. A unique identifier for a topic within a cluster
c. A unique identifier for a partition within a topic
d. A unique identifier for a consumer within a group
Answer: a. A unique identifier for a message within a partition
Explanation: A Kafka offset is a unique identifier for a message within a partition. It is a numeric value that is assigned to each message as it is produced to the partition and allows consumers to keep track of their progress in reading messages from a topic.
9. What is a Kafka producer API?
a. A set of Java APIs for implementing Kafka producers
b. A set of REST APIs for interacting with Kafka producers
c. A set of Python APIs for implementing Kafka producers
d. A set of Node.js APIs for implementing Kafka producers
Answer: a. A set of Java APIs for implementing Kafka producers
Explanation: The Kafka producer API is a set of Java APIs that allow developers to implement Kafka producers in their applications. The API provides methods for sending data to Kafka topics, as well as configuring the producer’s behavior.
10. What is a Kafka consumer API?
a. A set of Java APIs for implementing Kafka consumers
b. A set of REST APIs for interacting with Kafka consumers
c. A set of Python APIs for implementing Kafka consumers
d. A set of Node.js APIs for implementing Kafka consumers
Answer: a. A set of Java APIs for implementing Kafka consumers
Explanation: The Kafka consumer API is a set of Java APIs that allow developers to implement Kafka consumers in their applications. The API provides methods for reading data from Kafka topics, as well as configuring the consumer’s behavior.
11. What is a Kafka Connect?
a. A tool for connecting Kafka brokers to external systems
b. A tool for connecting Kafka producers to external systems
c. A tool for connecting Kafka consumers to external systems
d. A tool for connecting Kafka topics to external systems
Answer: a. A tool for connecting Kafka brokers to external systems
Explanation: Kafka Connect is a tool for connecting Kafka brokers to external systems. It provides a set of connectors that allow data to be imported into and exported from Kafka topics, as well as a framework for developing custom connectors.
12. What is a Kafka Streams?
a. A tool for processing real-time data streams using Kafka
b. A tool for visualizing data in Kafka topics
c. A tool for managing Kafka clusters
d. A tool for monitoring Kafka performance
Answer: a. A tool for processing real-time data streams using Kafka
Explanation: Kafka Streams is a tool for processing real-time data streams using Kafka. It provides a high-level API for building stream processing applications that can read data from Kafka topics, transform it, and write the results to new Kafka topics.
13. What is a Kafka cluster?
a. A group of producers that publish data to Kafka topics
b. A group of consumers that read data from Kafka topics
c. A group of brokers that work together to store and distribute data across topics and partitions
d. A group of Kafka Connectors that import data into Kafka topics
Answer: c. A group of brokers that work together to store and distribute data across topics and partitions
Explanation: A Kafka cluster is a group of brokers that work together to store and distribute data across topics and partitions. Each broker in the cluster is responsible for a subset of the partitions, and data is replicated across brokers for fault tolerance.
14. What is the default port for Kafka?
a. 9090
b. 9091
c. 9092
d. 9093
Answer: c. 9092
Explanation: The default port for Kafka is 9092. This port is used by clients to connect to Kafka brokers and send and receive data.
15. What is ZooKeeper in Kafka?
a. A messaging system that Kafka uses to send and receive data
b. A database that Kafka uses to store data
c. A tool for managing Kafka brokers
d. A distributed coordination service that Kafka uses for configuration management and leader election
Answer: d. A distributed coordination service that Kafka uses for configuration management and leader election
Explanation: ZooKeeper is a distributed coordination service that Kafka uses for configuration management and leader election. Kafka uses ZooKeeper to maintain metadata about the cluster, such as broker IDs and topic configurations, and to elect a leader for each partition.
16. What is a topic partition in Kafka?
a. A logical division of a Kafka topic that allows for parallel processing
b. A physical division of a Kafka topic that allows for fault tolerance
c. A data structure used by Kafka to store messages
d. A data structure used by Kafka to store consumer offsets
Answer: a. A logical division of a Kafka topic that allows for parallel processing
Explanation: A topic partition in Kafka is a logical division of a Kafka topic that allows for parallel processing. Each partition is an ordered, immutable sequence of messages that can be processed independently of other partitions.
17. What is a consumer group in Kafka?
a. A group of Kafka brokers that work together to store and distribute data across topics and partitions
b. A group of Kafka producers that publish data to a single topic
c. A group of Kafka consumers that read data from a single partition
d. A group of Kafka consumers that work together to read data from one or more partitions of a topic
Answer: d. A group of Kafka consumers that work together to read data from one or more partitions of a topic
Explanation: A consumer group in Kafka is a group of Kafka consumers that work together to read data from one or more partitions of a topic. Each partition can only be consumed by one consumer within a group, but multiple groups can consume from the same topic.
18. What is the purpose of a Kafka partition key?
a. To ensure that messages are evenly distributed across partitions
b. To allow for ordering of messages within a partition
c. To provide a unique identifier for each message within a partition
d. To specify which partition a message should be written to
Answer: d. To specify which partition a message should be written to
Explanation: The purpose of a Kafka partition key is to specify which partition a message should be written to. The key is used to determine the partition based on a hashing algorithm, and messages with the same key will always be written to the same partition.
19. What is the maximum size of a message in Kafka?
a. 1 MB
b. 5 MB
c. 10 MB
d. There is no fixed maximum size for a message in Kafka
Answer: d. There is no fixed maximum size for a message in Kafka
Explanation: There is no fixed maximum size for a message in Kafka. However, it is generally recommended to keep message sizes relatively small (e.g., under 1 MB) to ensure efficient processing and avoid potential performance issues.
20. What is a Kafka Stream?
a. A type of Kafka client used for writing data to Kafka
b. A framework for building stream processing applications using Kafka
c. A tool for monitoring the health and performance of a Kafka cluster
d. A data structure used by Kafka to store consumer offsets
Answer: b. A framework for building stream processing applications using Kafka
Explanation: Kafka Streams is a framework for building stream processing applications using Kafka. It provides an easy-to-use API for processing streams of data in real-time and supports a wide range of stream processing operations.
21. What is the role of a Kafka producer?
a. To read data from a Kafka topic and process it
b. To write data to a Kafka topic
c. To manage the partitioning and replication of a Kafka topic
d. To manage the consumption of data from a Kafka topic
Answer: b. To write data to a Kafka topic
Explanation: The role of a Kafka producer is to write data to a Kafka topic. Producers can write data to one or more partitions of a topic, and can specify a partition key to determine which partition the message should be written to.
22. What is the role of a Kafka consumer?
a. To read data from a Kafka topic and process it
b. To write data to a Kafka topic
c. To manage the partitioning and replication of a Kafka topic
d. To manage the consumption of data from a Kafka topic
Answer: a. To read data from a Kafka topic and process it
Explanation: The role of a Kafka consumer is to read data from a Kafka topic and process it. Consumers can read data from one or more partitions of a topic, and can manage their position in the partition by tracking the offset of the last message they have processed.
23. What is the default retention period for Kafka messages?
a. 1 day
b. 7 days
c. 30 days
d. There is no default retention period for Kafka messages
Answer: d. There is no default retention period for Kafka messages
Explanation: There is no default retention period for Kafka messages. Instead, Kafka uses a retention policy to determine when messages should be deleted from a topic. The retention policy can be based on time (e.g., retain messages for 7 days) or based on the size of the topic (e.g., retain the last 1 GB of messages).
24. What is the role of a Kafka broker?
a. To read data from a Kafka topic and process it
b. To write data to a Kafka topic
c. To manage the partitioning and replication of a Kafka topic
d. To manage the consumption of data from a Kafka topic
Answer: c. To manage the partitioning and replication of a Kafka topic
Explanation: The role of a Kafka broker is to manage the partitioning and replication of a Kafka topic. Brokers store and serve messages for one or more partitions of a topic, and can replicate messages across multiple brokers for fault tolerance.
25. What is the purpose of the Kafka ZooKeeper?
a. To manage the partitioning and replication of Kafka topics
b. To monitor the health and performance of a Kafka cluster
c. To coordinate the activities of Kafka brokers and consumers
d. To process streams of data using Kafka
Answer: c. To coordinate the activities of Kafka brokers and consumers
Explanation: The purpose of the Kafka ZooKeeper is to coordinate the activities of Kafka brokers and consumers. It provides a distributed coordination service that allows Kafka clients to discover brokers, coordinate leader elections, and manage consumer offsets.
26. What is the role of the Kafka Controller?
a. To manage the partitioning and replication of Kafka topics
b. To monitor the health and performance of a Kafka cluster
c. To coordinate the activities of Kafka brokers and consumers
d. To manage the metadata and state of a Kafka cluster
Answer: d. To manage the metadata and state of a Kafka cluster
Explanation: The role of the Kafka Controller is to manage the metadata and state of a Kafka cluster. It is responsible for managing topics, partitions, and replicas, and for detecting and recovering from broker failures.
27. What is the purpose of the Kafka Offset?
a. To manage the partitioning and replication of Kafka topics
b. To track the position of a consumer in a Kafka topic
c. To monitor the health and performance of a Kafka cluster
d. To process streams of data using Kafka
Answer: b. To track the position of a consumer in a Kafka topic
Explanation: The purpose of the Kafka Offset is to track the position of a consumer in a Kafka topic. The offset is a numeric value that represents the position of the last message that the consumer has processed, and is used to resume processing after a failure or shutdown.
28. What is the purpose of the Kafka Log Compaction?
a. To compress the data stored in Kafka topics
b. To remove redundant data from Kafka topics
c. To partition data across multiple Kafka brokers
d. To replicate data across multiple Kafka clusters
Answer: b. To remove redundant data from Kafka topics
Explanation: The purpose of Kafka Log Compaction is to remove redundant data from Kafka topics. Log compaction ensures that only the most recent message for each key is retained in the topic, which is useful for use cases where the most recent state of an entity is more important than its full history.
29. Which of the following is NOT a benefit of using Apache Kafka?
a. High throughput and low latency
b. Fault-tolerant and scalable architecture
c. Support for real-time stream processing
d. Support for batch processing of static data
Answer: d. Support for batch processing of static data
Explanation: While Kafka is primarily designed for real-time stream processing, it does not support batch processing of static data out of the box. However, Kafka can be used in conjunction with other tools to support batch processing use cases.
30. How are messages distributed across Kafka Partitions?
a. In a round-robin fashion
b. Based on the order in which they are received
c. Using a consistent hashing algorithm
d. By a random assignment algorithm
Answer: c. Using a consistent hashing algorithm
Explanation: Messages are distributed across Kafka Partitions using a consistent hashing algorithm. This ensures that messages with the same key are always assigned to the same partition, allowing for efficient message ordering and processing.
31. What is the purpose of a Kafka Connect?
a. To manage the partitioning and replication of Kafka topics
b. To monitor the health and performance of a Kafka cluster
c. To integrate Kafka with external systems
d. To process streams of data using Kafka
Answer: c. To integrate Kafka with external systems
Explanation: The purpose of Kafka Connect is to integrate Kafka with external systems. Connectors can be used to read data from or write data to external systems such as databases, message queues, and file systems.
32. What is the difference between Kafka Streams and Kafka Connect?
a. Kafka Streams is used for real-time processing, while Kafka Connect is used for batch processing
b. Kafka Streams is used for batch processing, while Kafka Connect is used for real-time processing
c. Kafka Streams is used for processing data within Kafka, while Kafka Connect is used for integrating Kafka with external systems
d. Kafka Streams is used for reading data from Kafka, while Kafka Connect is used for writing data to Kafka
Answer: c. Kafka Streams is used for processing data within Kafka, while Kafka Connect is used for integrating Kafka with external systems
Explanation: Kafka Streams is a client library used for processing data within Kafka, while Kafka Connect is used for integrating Kafka with external systems. Both tools are used for real-time processing and can be used to read and write data to Kafka.
33. What is the purpose of Kafka Streams?
a. To manage the partitioning and replication of Kafka topics
b. To monitor the health and performance of a Kafka cluster
c. To integrate Kafka with external systems
d. To process streams of data using Kafka
Answer: d. To process streams of data using Kafka
Explanation: The purpose of Kafka Streams is to process streams of data using Kafka. It is a client library that allows developers to create stream processing applications that can read from and write to Kafka topics.
34. What is a Kafka Topic Partitioner?
a. A component that manages the partitioning and replication of Kafka topics
b. A component that reads data from Kafka topics and writes it to external systems
c. A component that processes streams of data using Kafka
d. A component that determines how messages are assigned to Kafka partitions
Answer: d. A component that determines how messages are assigned to Kafka partitions
Explanation: A Kafka Topic Partitioner is a component that determines how messages are assigned to Kafka partitions. The partitioner can use various strategies, such as a round-robin approach or a consistent hashing algorithm, to distribute messages across partitions.
35. What is Kafka MirrorMaker?
a. A tool used for monitoring the health and performance of a Kafka cluster
b. A tool used for replicating data from one Kafka cluster to another
c. A tool used for integrating Kafka with external systems
d. A tool used for processing streams of data using Kafka
Answer: b. A tool used for replicating data from one Kafka cluster to another
Explanation: Kafka MirrorMaker is a tool used for replicating data from one Kafka cluster to another. It can be used to replicate data between clusters in different data centers or geographic regions.
36. What is the purpose of a Kafka Offset?
a. To determine the order in which messages are processed within a Kafka partition
b. To determine the partition to which a message is written in Kafka
c. To determine the order in which messages are read from a Kafka topic
d. To determine the consumer group that is reading messages from a Kafka topic
Answer: c. To determine the order in which messages are read from a Kafka topic
Explanation: The purpose of a Kafka Offset is to determine the order in which messages are read from a Kafka topic. Each message in a Kafka topic has an associated offset that indicates its position within the topic.
37. What is a Kafka Consumer Group?
a. A group of Kafka brokers that work together to serve messages to consumers
b. A group of Kafka producers that work together to write data to a Kafka topic
c. A group of Kafka consumers that work together to read data from a Kafka topic
d. A group of Kafka Connectors that work together to integrate Kafka with external systems
Answer: c. A group of Kafka consumers that work together to read data from a Kafka topic
Explanation: A Kafka Consumer Group is a group of Kafka consumers that work together to read data from a Kafka topic. Each message in the topic is consumed by one consumer within the group, allowing for parallel processing of messages.
38. What is a Kafka Consumer Offset?
a. An identifier that indicates the position of a consumer within a consumer group
b. An identifier that indicates the position of a message within a Kafka partition
c. An identifier that indicates the position of a message within a Kafka topic
d. An identifier that indicates the position of a partition within a Kafka cluster
Answer: b. An identifier that indicates the position of a message within a Kafka partition
Explanation: A Kafka Consumer Offset is an identifier that indicates the position of a message within a Kafka partition. Consumers use offsets to keep track of their progress through the message stream and to ensure that they do not consume the same message twice.
39. What is Kafka Connect?
a. A tool used for monitoring the health and performance of a Kafka cluster
b. A tool used for replicating data from one Kafka cluster to another
c. A tool used for integrating Kafka with external systems
d. A tool used for processing streams of data using Kafka
Answer: c. A tool used for integrating Kafka with external systems
Explanation: Kafka Connect is a tool used for integrating Kafka with external systems. It allows data to be imported into and exported from Kafka topics, enabling data pipelines to be built between Kafka and other systems.
40. What is a Kafka Connector?
a. A tool used for monitoring the health and performance of a Kafka cluster
b. A tool used for replicating data from one Kafka cluster to another
c. A tool used for integrating Kafka with external systems
d. A tool used for processing streams of data using Kafka
Answer: c. A tool used for integrating Kafka with external systems
Explanation: A Kafka Connector is a tool used for integrating Kafka with external systems. Connectors can be used to import data into Kafka topics from external systems or to export data from Kafka topics to external systems.
41. What is Kafka Retention?
a. The amount of time that messages are stored in Kafka before being deleted
b. The number of messages that are stored in Kafka before being deleted
c. The number of Kafka brokers in a Kafka cluster
d. The amount of time it takes for a message to be processed within Kafka
Answer: a. The amount of time that messages are stored in Kafka before being deleted
Explanation: Kafka Retention refers to the amount of time that messages are stored in Kafka before being deleted. This setting can be configured on a per-topic basis and can be used to ensure that messages are retained for a specific period of time.
42. What is Kafka Log Compaction?
a. A feature that allows Kafka to compress log data to save storage space
b. A feature that allows Kafka to remove duplicate messages from log data
c. A feature that allows Kafka to delete messages that are older than a specified retention period
d. A feature that allows Kafka to merge log data from multiple Kafka clusters
Answer: b. A feature that allows Kafka to remove duplicate messages from log data
Explanation: Kafka Log Compaction is a feature that allows Kafka to remove duplicate messages from log data. It is useful for scenarios where a large number of messages are produced with the same key, as it allows older messages with the same key to be compacted into a single message.
43. What is Kafka Producer Acknowledgement?
a. A setting that determines the maximum number of messages that can be produced by a Kafka producer
b. A setting that determines the maximum size of messages that can be produced by a Kafka producer
c. A setting that determines the level of acknowledgement required from a Kafka broker after a message is produced
d. A setting that determines the compression algorithm used by a Kafka producer
Answer: c. A setting that determines the level of acknowledgement required from a Kafka broker after a message is produced
Explanation: Kafka Producer Acknowledgement refers to the level of acknowledgement required from a Kafka broker after a message is produced. Producers can specify the acknowledgement level using the acks configuration parameter, which can be set to 0 (no acknowledgement), 1 (acknowledgement from the leader only), or -1 (acknowledgement from all replicas).
44. What is Kafka Consumer Offset?
a. The position of a consumer in a Kafka Consumer Group
b. The amount of time it takes for a message to be processed by a Kafka consumer
c. The amount of time that a Kafka consumer waits for new messages to arrive before timing out
d. The position of a consumer in a Kafka topic partition
Answer: d. The position of a consumer in a Kafka topic partition
Explanation: Kafka Consumer Offset refers to the position of a consumer in a Kafka topic partition. Consumers keep track of their offset for each partition they consume, enabling them to resume consuming from the same position in the event of a failure or restart.
45. What is Kafka Streaming?
a. A way of processing data in real-time using Kafka
b. A way of compressing log data in Kafka
c. A way of integrating Kafka with external systems
d. A way of managing the health and performance of a Kafka cluster
Answer: a. A way of processing data in real-time using Kafka
Explanation: Kafka Streaming is a way of processing data in real-time using Kafka. It involves building data pipelines using Kafka to enable data to be processed and analyzed as it is generated.
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