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NEW QUESTION # 38
What are stateful operations in Kafka Streams API? (Choose 2.)
- A. branch
- B. joins
- C. map
- D. windowing
Answer: B,D
NEW QUESTION # 39
Once sent to a topic, a message can be modified
- A. No
- B. Yes
Answer: A
Explanation:
Kafka logs are append-only and the data is immutable
NEW QUESTION # 40
(A consumer application runs once every two weeks and reads from a Kafka topic.
The last time the application ran, the last offset processed was 217.
The application is configured with auto.offset.reset=latest.
The current offsets in the topic start at 318 and end at 588.
Which offset will the application start reading from when it starts up for its next run?)
- A. 0
- B. 1
- C. 2
- D. 3
Answer: A
Explanation:
According to the official Apache Kafka consumer documentation, the auto.offset.reset configuration is only applied when a consumer has no valid committed offset for a partition. In this scenario, the consumer last committed offset 217, but the topic's earliest available offset is now 318. This means the previously committed offset is out of range, most likely due to topic retention cleanup.
When a committed offset is out of range, Kafka treats it as invalid and applies the auto.offset.reset policy.
Since the consumer is configured with auto.offset.reset=latest, it will start reading from the end of the log, not from the earliest available offset.
Kafka defines the "latest" offset as the log end offset, which is the offset of the next message to be written.
Given that the topic's offsets end at 588, the next offset is 589.
Therefore, the consumer will start reading from offset 589, skipping all existing records in the topic, which aligns with the documented Kafka consumer behavior.
NEW QUESTION # 41
The kafka-console-consumer CLI, when used with the default options
- A. always uses the same group id
- B. does not use a group id
- C. uses a random group id
Answer: C
Explanation:
If a group is not specified, the kafka-console-consumer generates a random consumer group.
NEW QUESTION # 42
A consumer sends a request to commit offset 2000. There is a temporary communication problem, so the broker never gets the request and therefore never responds. Meanwhile, the consumer processed another batch and successfully committed offset 3000. What should you do?
- A. Add a new consumer to the group
- B. Restart the consumer
- C. Use the kafka-consumer-group command to manually commit the offsets 2000 for the consumer group
- D. Nothing
Answer: D
Explanation:
In this case, because the offset 3000 has been committed and all the messages between 0 and 3000 have all been processed, it is okay not to have committed offset 2000. The right answer is to do "nothing", this behaviour is acceptable
NEW QUESTION # 43
What are the requirements for a Kafka broker to connect to a Zookeeper ensemble? (select two)
- A. All the brokers must share the same zookeeper.connect parameter
- B. Unique value for each broker's zookeeper.connect parameter
- C. All the brokers must share the same broker.id
- D. Unique values for each broker's broker.id parameter
Answer: A,D
Explanation:
Each broker must have a unique broker id and connect to the same zk ensemble and root zNode
NEW QUESTION # 44
Which of the following Kafka Streams operators are stateless? (select all that apply)
- A. groupBy
- B. flatmap
- C. aggregate
- D. branch
- E. map
- F. filter
Answer: A,B,D,E,F
Explanation:
Seehttps://kafka.apache.org/20/documentation/streams/developer-guide/dsl-api.html#stateless-transformations
NEW QUESTION # 45
What is returned by a producer.send() call in the Java API?
- A. A Boolean indicating if the call succeeded
- B. Future<ProducerRecord> object
- C. Unit
- D. Future<RecordMetadata> object
Answer: D
Explanation:
Seehttps://kafka.apache.org/21/javadoc/org/apache/kafka/clients/producer/KafkaProducer.html
NEW QUESTION # 46
In Avro, adding an element to an enum without a default is a __ schema evolution
- A. full
- B. breaking
- C. backward
- D. forward
Answer: B
Explanation:
Since Confluent 5.4.0, Avro 1.9.1 is used. Since default value was added to enum complex type , the schema resolution changed from:
(<1.9.1) if both are enums:** if the writer's symbol is not present in the reader's enum, then an error is signalled. **(>=1.9.1) if both are enums:
if the writer's symbol is not present in the reader's enum and the reader has a default value, then that value is used, otherwise an error is signalled.
NEW QUESTION # 47
You have a topic with four partitions. The application reads from it using two consumers in a single consumer group.
Processing is CPU-bound, and lag is increasing.
What should you do?
- A. Decrease the max.poll.records property of consumers.
- B. Increase the max.poll.records property of consumers.
- C. Add more consumers to increase the level of parallelism of the processing.
- D. Add more partitions to the topic to increase the level of parallelism of the processing.
Answer: C
Explanation:
If the application isCPU-boundandlagging, addingmore consumersto the group will allow betterparallel processing, especially since the topic has4 partitions, allowing up to 4 active consumers.
FromKafka Consumer Group Docs:
"Kafka achieves parallelism by distributing partitions across consumers in a group. Adding consumers helps reduce lag if partitions are underutilized."
* B may help but requires repartitioning and coordination.
* C or D affects how much data is polled, not how fast it's processed.
Reference:Kafka Consumer Concepts > Parallelism and Scaling
NEW QUESTION # 48
To produce data to a topic, a producer must provide the Kafka client with...
- A. all the brokers from the cluster and the topic name
- B. any broker from the cluster and the topic name
- C. the list of brokers that have the data, the topic name and the partitions list
- D. any broker from the cluster and the topic name and the partitions list
Answer: B
Explanation:
All brokers can respond to a Metadata request, so a client can connect to any broker in the cluster and then figure out on its own which brokers to send data to.
NEW QUESTION # 49
(You started a new Kafka Connect worker.
Which configuration identifies the Kafka Connect cluster that your worker will join?)
- A. group.id
- B. connector.id
- C. cluster.id
- D. worker.id
Answer: A
Explanation:
As documented in the official Apache Kafka Connect framework documentation, Kafka Connect workers form a logical cluster by using a Kafka consumer group. The configuration property that identifies this cluster is group.id.
All Kafka Connect workers configured with the same group.id automatically join the same Connect cluster.
Kafka's group coordination protocol is then used to distribute connector and task configurations among the workers, providing fault tolerance, scalability, and automatic rebalancing.
Option A (cluster.id) is a Kafka internal identifier used by brokers and is not configurable for Kafka Connect workers. Option B (worker.id) does not exist as a valid Kafka Connect configuration. Option D (connector.id) identifies individual connectors within a Connect cluster, not the worker cluster itself.
Therefore, the group.id property is the correct and officially documented configuration that determines which Kafka Connect cluster a worker belongs to.
NEW QUESTION # 50
Which partition assignment minimizes partition movements between two assignments?
- A. RoundRobinAssignor
- B. StickyAssignor
- C. PartitionAssignor
- D. RangeAssignor
Answer: B
NEW QUESTION # 51
(You are configuring a source connector that writes records to an Orders topic.
You need to send some of the records to a different topic.
Which Single Message Transform (SMT) is best suited for this requirement?)
- A. TombstoneHandler
- B. RegexRouter
- C. InsertField
- D. HeaderFrom
Answer: B
Explanation:
According to the official Apache Kafka Connect documentation, RegexRouter is the SMT specifically designed to dynamically change the destination topic name of records produced by a connector. It works by applying a regular expression to the original topic name and rewriting it to a new topic name.
This makes RegexRouter the correct choice when some records must be routed to a different topic, typically in combination with connector-level logic, predicates, or multiple connectors. It is commonly used for topic renaming, topic versioning, or routing records to alternate topics.
InsertField (Option B) only adds metadata fields (such as topic, partition, or timestamp) to the record payload and does not affect routing. TombstoneHandler (Option C) is used to manage null-value records, especially with compacted topics. HeaderFrom (Option D) copies fields into headers but does not change the target topic.
Therefore, RegexRouter is the only SMT that directly supports changing the output topic, as documented in the Kafka Connect SMT reference.
NEW QUESTION # 52
What does producing data to a topic with a message key allow?
- A. Producers to add extra metadata with the message
- B. Messages to be secured with encryption
- C. Messages to have a strategy for partition assignment
- D. Consumers to subscribe to a message with a specific key
Answer: C
NEW QUESTION # 53
is KSQL ANSI SQL compliant?
- A. No
- B. Yes
Answer: A
Explanation:
KSQL is not ANSI SQL compliant, for now there are no defined standards on streaming SQL languages
NEW QUESTION # 54
Which statement is true about how exactly-once semantics (EOS) work in Kafka Streams?
- A. EOS in Kafka Streams relies on transactional producers to atomically commit state updates to changelog topics and output records to Kafka.
- B. Kafka Streams provides EOS by periodically checkpointing state stores and replaying changelogs to recover only unprocessed messages during failure.
- C. Kafka Streams disables log compaction on internal changelog topics to preserve all state changes for potential recovery.
- D. EOS in Kafka Streams is implemented by creating a separate Kafka topic for deduplication of all messages processed by the application.
Answer: A
Explanation:
Kafka Streams usestransactional producersto guaranteeexactly-once semantics (EOS). This ensures that both theoutput recordsandstate store updatesare committed atomically, avoiding duplication or partial writes.
FromKafka Streams Documentation > Processing Guarantees:
"Kafka Streams leveragesKafka's transactional APIsto commit the output records and internal state updates as a single atomic unit, thereby providing exactly-once semantics."
* Option A is incorrect because log compaction is not disabled for EOS.
* Option C incorrectly describes a checkpointing system Kafka Streams does not use.
* Option D refers to deduplication, which is not how EOS is achieved in Streams.
Reference:Kafka Streams Processing Guarantees
NEW QUESTION # 55
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