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Confluent CCAAK Exam Syllabus Topics:
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NEW QUESTION # 31
A company is setting up a log ingestion use case where they will consume logs from numerous systems. The company wants to tune Kafka for the utmost throughput.
In this scenario, what acknowledgment setting makes the most sense?
- A. acks=1
- B. acks=undefined
- C. acks=0
- D. acks=all
Answer: C
Explanation:
acks=0 provides the highest throughput because the producer does not wait for any acknowledgment from the broker. This minimizes latency and maximizes performance.
However, it comes at the cost of no durability guarantees - messages may be lost if the broker fails before writing them. This setting is suitable when throughput is critical and occasional data loss is acceptable, such as in some log ingestion use cases where logs are also stored elsewhere.
NEW QUESTION # 32
Which model does Kafka use for consumers?
- A. Publish
- B. Pull
- C. Push
- D. Enrollment
Answer: B
Explanation:
Kafka uses a pull model for consumers, where consumers poll the broker to retrieve messages at their own pace. This model gives consumers more control over flow and backpressure, improving scalability and reliability.
NEW QUESTION # 33
How can authentication for both internal component traffic and external client traffic be accomplished?
- A. Configure LoadBalancer.
- B. Configure multiple security protocols on the same listener.
- C. Configure multiple brokers.
- D. Configure multiple listeners on the broker.
Answer: D
Explanation:
Kafka supports multiple listeners, each with its own port, hostname, and security protocol. This allows you to:
* Use one listener for internal communication (e.g., brokers, ZooKeeper, Connect, etc.) with one type of authentication (e.g., PLAINTEXT or SASL).
* Use a separate listener for external clients (e.g., producers and consumers) with a different protocol (e.g., SSL or SASL_SSL).
NEW QUESTION # 34
You want to increase Producer throughput for the messages it sends to your Kafka cluster by tuning the batch size ('batch size') and the time the Producer waits before sending a batch ('linger.ms').
According to best practices, what should you do?
- A. Decrease 'batch.size' and increase 'linger.ms'
- B. Increase 'batch.size' and decrease 'linger.ms'
- C. Decrease 'batch.size' and decrease 'linger.ms'
- D. Increase 'batch.size' and increase 'linger.ms'
Answer: D
Explanation:
Increasing batch.size allows the producer to accumulate more messages into a single batch, improving compression and reducing the number of requests sent to the broker.
Increasing linger.ms gives the producer more time to fill up batches before sending them, which improves batching efficiency and throughput.
This combination is a best practice for maximizing throughput, especially when message volume is high or consistent latency is not a strict requirement.
NEW QUESTION # 35
You have a Kafka cluster with topics t1 and t2. In the output below, topic t2 shows Partition 1 with a leader "-1".
What is the most likely reason for this?
...
$ kafka-topics --zookeeper localhost:2181 --describe --topic t1
Topic:t1 PartitionCount 1 ReplicationFactor 1 Configs:
Topic: t1 Partition: 0 Leader: 0 Replicas: 0 Isr: 0
$ kafka-topics --zookeeper localhost:2181 --describe --topic t2
Topic:t2 PartitionCount 2 ReplicationFactor 1 Configs:
Topic: t2 Partition: 0 Leader: 0 Replicas: 0 Isr: 0
Topic: t2 Partition: 1 Leader: -1 Replicas: 1 Isr:
- A. Broker 1 failed.
- B. Broker 1 has another partition clashing with the same name.
- C. Leader shows "-1" while the log cleaner thread runs on Broker 1.
- D. Compression has been enabled on Broker 1.
Answer: A
Explanation:
A Leader of -1 indicates that no broker is currently the leader for that partition. This usually happens when the only replica for that partition is unavailable, often due to the associated broker (in this case, Broker 1) failing or being offline. Kafka cannot elect a leader if no replica is in the in-sync replica (ISR) list, which leads to leader = -1.
NEW QUESTION # 36
An employee in the reporting department needs assistance because their data feed is slowing down. You start by quickly checking the consumer lag for the clients on the data stream.
Which command will allow you to quickly check for lag on the consumers?
- A. bin/kafka-consumer-group-throughput.sh
- B. bin/kafka-consumer-lag.sh
- C. bin/kafka-reassign-partitions.sh
- D. bin/kafka-consumer-groups.sh
Answer: D
Explanation:
The kafka-consumer-groups.sh script is used to inspect consumer group details, including consumer lag, which indicates how far behind a consumer is from the latest data in the partition.
The typical usage is bin/kafka-consumer-groups.sh --bootstrap-server <broker> --describe --group <group_id>
NEW QUESTION # 37
Which tool is used for scalably and reliably streaming data between Kafka and other data systems?
- A. Kafka Streams
- B. Kafka Schema Registry
- C. Kafka Connect
- D. Kafka REST Proxy
Answer: C
Explanation:
Kafka Connect is the tool designed for scalable and reliable integration between Kafka and external data systems (e.g., databases, cloud storage, key-value stores). It supports source connectors (to pull data into Kafka) and sink connectors (to push data from Kafka).
NEW QUESTION # 38
What is the relationship between topics and partitions? (Choose two.)
- A. Atopic always has one partition.
- B. There is no relationship between topics and partitions.
- C. Atopic may have more than one partition.
- D. A partition is always linked to a single topic.
- E. A partition may have more than one topic.
Answer: C,D
Explanation:
Kafka topics are split into one or more partitions to enable parallelism and scalability.
Each partition belongs to exactly one topic; it cannot span multiple topics.
NEW QUESTION # 39
Which use cases would benefit most from continuous event stream processing? (Choose three.)
- A. Context-aware product recommendations for e-commerce
- B. Historical dashboards
- C. End-of-day financial settlement processing
- D. Log monitoring/application fault detection
- E. Fraud detection
Answer: A,D,E
Explanation:
Real-time analysis of transactions helps detect suspicious activity instantly.
Context-aware product recommendations for e-commerce requires real-time user behavior tracking to serve personalized recommendations.
Log monitoring/application fault detection needs immediate processing to alert on system issues or failures.
NEW QUESTION # 40
Which statements are correct about partitions? (Choose two.)
- A. A partition is comprised of one or more segments on a disk.
- B. A partition in Kafka will be represented by a single segment on a disk.
- C. All partition segments reside in a single directory on a broker disk.
- D. A partition size is determined after the largest segment on a disk.
Answer: A,C
NEW QUESTION # 41
What are benefits to gracefully shutting down brokers? (Choose two.)
- A. It will sync all its logs to disk to avoid needing to do any log recovery when it restarts.
- B. It will balance the partitions across brokers before restarting.
- C. It will migrate any partitions the server is the leader for to other replicas prior to shutting down.
- D. It will automatically re-elect leaders on restart.
Answer: A,C
Explanation:
A graceful shutdown ensures that logs are flushed to disk, minimizing recovery time during restart.
Kafka performs controlled leader migration during a graceful shutdown to avoid disruption and ensure availability.
NEW QUESTION # 42
Your Kafka cluster has four brokers. The topic t1 on the cluster has two partitions, and it has a replication factor of three. You create a Consumer Group with four consumers, which subscribes to t1.
In the scenario above, how many Controllers are in the Kafka cluster?
- A. two
- B. three
- C. Four
- D. One
Answer: D
Explanation:
In a Kafka cluster, only one broker acts as the Controller at any given time. The Controller is responsible for managing cluster metadata, such as partition leadership and broker status. Even if the cluster has multiple brokers (in this case, four), only one is elected as the Controller, and others serve as regular brokers. If the current Controller fails, another broker is automatically elected to take its place.
NEW QUESTION # 43
Which technology can be used to perform event stream processing? (Choose two.)
- A. Confluent ksqlDB
- B. Confluent Replicator
- C. Apache Kafka Streams
- D. Confluent Schema Registry
Answer: A,C
Explanation:
Kafka Streams is a client library for building real-time applications that process and analyze data stored in Kafka.
ksqlDB enables event stream processing using SQL-like queries, allowing real-time transformation and analysis of Kafka topics.
NEW QUESTION # 44
In certain scenarios, it is necessary to weigh the trade-off between latency and throughput. One method to increase throughput is to configure batching of messages.
In addition to batch.size, what other producer property can be used to accomplish this?
- A. sendbufferbytes
- B. delivery.timeout.ms
- C. compression
- D. linger.ms
Answer: D
Explanation:
The linger.ms property sets the maximum time the producer will wait before sending a batch, even if the batch isn't full. By increasing linger.ms, you allow more records to accumulate in the batch.
NEW QUESTION # 45
Which valid security protocols are included for broker listeners? (Choose three.)
- A. SASL_SSL
- B. GSSAPI
- C. SASL
- D. PLAINTEXT
- E. SSL
Answer: A,D,E
NEW QUESTION # 46
The Consumer property 'auto offset reset' determines what to do if there is no valid offset for a Consumer Group.
Which scenario is an example of a valid offset and therefore the 'auto.offset.reset' does NOT apply?
- A. The Consumer Group started for the first time.
- B. The Consumer offset is less than the smallest offset in the partition (log start offset).
- C. The Consumer offset is greater than the last offset in the partition (log end offset).
- D. When an offset points to a message that has been removed by compaction but is still within the current partition.offset range.
Answer: D
Explanation:
In this scenario, the offset itself is still valid, even though the record at that offset was compacted away. The consumer can continue consuming from the next available record. Therefore, auto.offset.reset does NOT apply, because there is a valid offset present.
NEW QUESTION # 47
When a broker goes down, what will the Controller do?
- A. Become the leader for the topic/partition that needs a leader, pending the broker return in the cluster.
- B. Wait for a follower to take the lead.
- C. Automatically elect the least loaded broker to become the leader for every orphan's partitions.
- D. Trigger a leader election among the remaining followers to distribute leadership.
Answer: D
Explanation:
When a broker goes down, the Controller detects the failure and triggers a leader election for all partitions that had their leader on the failed broker. The leader is chosen from the in-sync replicas (ISRs) of each partition.
NEW QUESTION # 48
A Kafka administrator notices that their consumers of Topic X are starting to fall behind. The administrator sees that Topic X has four partitions, and the consumer group has two consumers.
Which change can increase the performance of the Consumer Group?
- A. Increase the number of consumers in the consumer group.
- B. Increase the partitions in Topic X.
- C. Create a new consumer group for Topic X containing two (2) consumers.
- D. Decrease the consumer acknowledgment property to increase throughput.
Answer: A
Explanation:
With 4 partitions and only 2 consumers, some consumers are handling multiple partitions, which may cause lag if processing is slow. By increasing the number of consumers in the group (up to 4), Kafka can assign one partition per consumer, improving parallelism and throughput.
NEW QUESTION # 49
A broker in the Kafka cluster is currently acting as the Controller.
Which statement is correct?
- A. All consumers are allowed to fetch messages only from this server.
- B. It can have topic partitions.
- C. It is given precedence for replication to and from replica followers.
- D. It is responsible for sending leader information to all producers.
Answer: B
Explanation:
The Controller broker is a regular broker that also takes on additional responsibilities for managing cluster metadata, such as leader elections and partition assignments. It still hosts topic partitions and participates in replication like any other broker.
NEW QUESTION # 50
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