CCAAK PDF Exam Material 2025 Realistic CCAAK Dumps Questions
Updated Confluent CCAAK Dumps – PDF & Online Engine
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NEW QUESTION # 19
What are important factors in sizing a ksqlDB cluster? (Choose three.)
- A. Topic Data Retention
- B. Data Encryption
- C. Number of Queries
- D. Number of Partitions
- E. Data Schema
Answer: C,D,E
Explanation:
The complexity of the schema (number of fields, data types, etc.) affects processing and memory usage.
Each ksqlDB persistent query consumes resources (CPU, memory), so more queries require more capacity.
More partitions increase parallelism, but also resource usage, especially in scaling and state management.
NEW QUESTION # 20
If a broker's JVM garbage collection takes too long, what can occur?
- A. Log files written to disk are loaded into the page cache.
- B. There will be a trigger of the broker's log cleaner thread.
- C. There is backpressure to, and pausing of, Kafka clients.
- D. ZooKeeper believes the broker to be dead.
Answer: D
Explanation:
If the broker's JVM garbage collection (GC) pause is too long, it may fail to send heartbeats to ZooKeeper within the expected interval. As a result, ZooKeeper considers the broker dead, and the broker may be removed from the cluster, triggering leader elections and partition reassignments.
NEW QUESTION # 21
A customer has a use case for a ksqlDB persistent query. You need to make sure that duplicate messages are not processed and messages are not skipped.
Which property should you use?
- A. ksql.streams auto offset.reset=earliest
- B. ksql.fail.on.production.error=false
- C. processing.guarantee=exactly_once
- D. ksql.streams auto.offset.reset=latest
Answer: C
Explanation:
processing.guarantee=exactly_once ensures that messages are processed exactly once by ksqlDB, preventing both duplicates and message loss.
NEW QUESTION # 22
When using Kafka ACLs, when is the resource authorization checked?
- A. When the client connection is first established.
- B. The initial time the resource is accessed.
- C. Each time the resource is accessed within the configured authorization interval.
- D. Each time the resource is accessed.
Answer: D
Explanation:
Kafka ACLs (Access Control Lists) perform authorization checks every time a client attempts to access a resource (e.g., topic, consumer group). This ensures continuous enforcement of permissions, not just at connection time or intervals. This approach provides fine-grained security, preventing unauthorized actions at any time during a session.
NEW QUESTION # 23
Per customer business requirements, a system's high availability is more important than message reliability.
Which of the following should be set?
- A. The number of brokers in the cluster should be always odd (3, 5. 7 and so on).
- B. Message retention.ms should be set to -1.
- C. Unclean leader election should be enabled.
- D. The linger.ms should be set to '0'.
Answer: C
Explanation:
Enabling unclean leader election allows Kafka to elect a non-in-sync replica as leader if all in-sync replicas are unavailable. This sacrifices message reliability (possible data loss) in favor of high availability, aligning with the requirement.
NEW QUESTION # 24
Where are Apache Kafka Access Control Lists stored'?
- A. Connect
- B. ZooKeeper
- C. Broker
- D. Schema Registry
Answer: B
Explanation:
In Apache Kafka (open-source), Access Control Lists (ACLs) are stored in ZooKeeper. Kafka brokers retrieve and enforce ACLs from ZooKeeper at runtime.
NEW QUESTION # 25
Which model does Kafka use for consumers?
- A. Push
- B. Publish
- C. Enrollment
- D. Pull
Answer: D
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 # 26
Which statements are correct about partitions? (Choose two.)
- A. A partition size is determined after the largest segment on a disk.
- B. All partition segments reside in a single directory on a broker disk.
- C. A partition is comprised of one or more segments on a disk.
- D. A partition in Kafka will be represented by a single segment on a disk.
Answer: B,C
NEW QUESTION # 27
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=0
- B. acks=undefined
- C. acks=1
- D. acks=all
Answer: A
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 # 28
When a broker goes down, what will the Controller do?
- A. Automatically elect the least loaded broker to become the leader for every orphan's partitions.
- B. Wait for a follower to take the lead.
- C. Trigger a leader election among the remaining followers to distribute leadership.
- D. Become the leader for the topic/partition that needs a leader, pending the broker return in the cluster.
Answer: C
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 # 29
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. linger.ms
- B. compression
- C. sendbufferbytes
- D. delivery.timeout.ms
Answer: A
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 # 30
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 has another partition clashing with the same name.
- B. Leader shows "-1" while the log cleaner thread runs on Broker 1.
- C. Broker 1 failed.
- D. Compression has been enabled on Broker 1.
Answer: C
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 # 31
You have a cluster with a topic t1 that already has uncompressed messages. A new Producer starts sending messages to t1 with compression enabled.
Which condition would allow this?
- A. Only if Kafka is also enabled for encryption.
- B. Never, because topic t1 already has uncompressed messages.
- C. If the new Producer is configured to use compression.
- D. Only if the new Producer disables batching.
Answer: C
Explanation:
Kafka allows mixed compression formats within the same topic and even the same partition. Each message batch includes metadata indicating whether and how it is compressed. Therefore, a new producer can send compressed messages to a topic that already contains uncompressed messages, as long as it is configured with a compression codec (e.g., compression.type=gzip, snappy, etc.).
NEW QUESTION # 32
Which out-of-the-box Kafka Authorizer implementation uses ZooKeeper?
- A. ACLs
- B. LDAP
- C. RBAC
- D. Ranger
Answer: A
Explanation:
Kafka's built-in ACL (Access Control List) authorizer stores and manages permissions using ZooKeeper by default. This implementation controls access at the resource level (topics, consumer groups, etc.).
NEW QUESTION # 33
You are using Confluent Schema Registry to provide a RESTful interface for storing and retrieving schemas.
Which types of schemas are supported? (Choose three.)
- A. gRPC
- B. JSON
- C. Thrift
- D. Protobuf
- E. Avro
Answer: B,D,E
Explanation:
Avro is the original and most commonly used schema format supported by Schema Registry.
Confluent Schema Registry supports JSON Schema for validation and compatibility checks.
Protocol Buffers (Protobuf) are supported for schema management in Schema Registry.
NEW QUESTION # 34
How does Kafka guarantee message integrity after a message is written on a disk?
- A. A message cannot be altered once it has been written.
C A message can be grouped with message sharing the same key to improve read performance - B. A message can be edited by the producer, producing to the message offset.
- C. Only message metadata can be altered using command line (CLI) tools.
Answer: A
Explanation:
Kafka ensures message immutability for data integrity. Once a message is written to a Kafka topic and persisted to disk, it cannot be modified. This immutability guarantees that consumers always receive the original message content, which is critical for auditability, fault tolerance, and data reliability.
NEW QUESTION # 35
Kafka Connect is running on a two node cluster in distributed mode. The connector is a source connector that pulls data from Postgres tables (users/payment/orders), writes to topics with two partitions, and with replication factor two. The development team notices that the data is lagging behind.
What should be done to reduce the data lag*?
The Connector definition is listed below:
{
"name": "confluent-postgresql-source",
"connector class": "PostgresSource",
"topic.prefix": "postgresql_",
& nbsp;& nbsp;& nbsp;...
"db.name": "postgres",
"table.whitelist": "users.payment.orders",
"timestamp.column.name": "created_at",
"output.data format": "JSON",
"db.timezone": "UTC",
"tasks.max": "1"
}
- A. Increase the number of Connect Tasks (tasks max value).
- B. Increase the replication factor and increase the number of Connect Tasks.
- C. Increase the number of Connect Nodes.
- D. Increase the number of partitions.
Answer: A
Explanation:
The connector is currently configured with "tasks.max": "1", which means only one task is handling all tables (users, payment, orders). This can create a bottleneck and lead to lag. Increasing tasks.max allows Kafka Connect to parallelize work across multiple tasks, which can pull data from different tables concurrently and reduce lag.
NEW QUESTION # 36
You are managing a cluster with a large number of topics, and each topic has a lot of partitions. A team wants to significantly increase the number of partitions for some topics.
Which parameters should you check before increasing the partitions?
- A. Check the max open file count on brokers.
- B. Check if compression is being used.
- C. Check if acks=all is beina used.
- D. Check the producer batch size and buffer size.
Answer: A
Explanation:
Each Kafka partition maps to multiple log segment files, and each segment results in open file descriptors on the broker. When the number of partitions increases significantly, it can exceed the OS-level limit for open files per broker process, leading to failures or degraded performance. Therefore, it is essential to check and possibly increase the ulimit -n (max open files) setting on the broker machines.
NEW QUESTION # 37
By default, what do Kafka broker network connections have?
- A. Encryption and authentication, but no authorization
- B. Encryption, but no authentication or authorization
- C. No encryption, no authorization, but have authentication
- D. No encryption, no authentication and no authorization
Answer: D
Explanation:
By default, Kafka brokers use the PLAINTEXT protocol for network communication. This means:
* No encryption - data is sent in plain text.
* No authentication - any client can connect without verifying identity.
* No authorization - there are no access control checks by default.
Security features like TLS, SASL, and ACLs must be explicitly configured.
NEW QUESTION # 38
How can load balancing of Kafka clients across multiple brokers be accomplished?
- A. Offsets
- B. Partitions
- C. Connectors
- D. Replicas
Answer: B
Explanation:
Partitions are the primary mechanism for achieving load balancing in Kafka. When a topic has multiple partitions, Kafka clients (producers and consumers) can distribute the load across brokers hosting these partitions.
NEW QUESTION # 39
Which of the following are Kafka Connect internal topics? (Choose three.)
- A. connect-standalone
- B. connect-distributed
- C. connect-status
- D. connect-confiqs
- E. connect-offsets
Answer: C,D,E
Explanation:
connect-configs stores connector configurations.
connect-status tracks the status of connectors and tasks (e.g., RUNNING, FAILED).
connect-offsets stores source connector offsets for reading from external systems.
NEW QUESTION # 40
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 # 41
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