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Confluent CCAAK Exam Syllabus Topics:
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NEW QUESTION # 26
Which technology can be used to perform event stream processing? (Choose two.)
- A. Confluent ksqlDB
- B. Apache Kafka Streams
- C. Confluent Schema Registry
- D. Confluent Replicator
Answer: A,B
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 # 27
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. sendbufferbytes
- C. delivery.timeout.ms
- D. compression
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 # 28
If the Controller detects the failure of a broker that was the leader for some partitions, which actions will be taken? (Choose two.)
- A. The Controller waits for a new leader to be nominated by ZooKeeper.
- B. The Controller sends the new leader and ISR list changes to all brokers.
- C. The Controller sends the new leader and ISR list changes to all producers and consumers.
- D. The Controller persists the new leader and ISR list to ZooKeeper.
Answer: B,D
Explanation:
The Controller updates ZooKeeper with the new leader and in-sync replica (ISR) information to maintain metadata consistency.
Brokers need this information to correctly route client requests and continue replication.
NEW QUESTION # 29
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 offset is greater than the last offset in the partition (log end offset).
- B. When an offset points to a message that has been removed by compaction but is still within the current partition.offset range.
- C. The Consumer Group started for the first time.
- D. The Consumer offset is less than the smallest offset in the partition (log start offset).
Answer: B
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 # 30
A developer is working for a company with internal best practices that dictate that there is no single point of failure for all data stored.
What is the best approach to make sure the developer is complying with this best practice when creating Kafka topics?
- A. Use the parameter --partitions=3 when creating the topic.
- B. Make sure the topics are created with linger.ms=0 so data is written immediately and not held in batch.
- C. Set 'min.insync.replicas' to 1.
- D. Set the topic replication factor to 3.
Answer: D
Explanation:
Replication factor determines how many copies of each partition exist across different brokers. A replication factor of 3 ensures that even if one or two brokers fail, the data is still available, thus eliminating a single point of failure.
NEW QUESTION # 31
Where are Apache Kafka Access Control Lists stored'?
- A. Connect
- B. ZooKeeper
- C. Schema Registry
- D. Broker
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 # 32
Which of the following are Kafka Connect internal topics? (Choose three.)
- A. connect-distributed
- B. connect-offsets
- C. connect-status
- D. connect-confiqs
- E. connect-standalone
Answer: B,C,D
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 # 33
Which ksqlDB statement produces data that is persisted into a Kafka topic?
- A. SELECT (Push Query)
- B. CREATE TABLE
- C. INSERT VALUES
- D. SELECT (Pull Query)
Answer: C
Explanation:
INSERT VALUES is used to write data directly into a Kafka topic through a ksqlDB stream or table. This data is persisted.
NEW QUESTION # 34
Per customer business requirements, a system's high availability is more important than message reliability.
Which of the following should be set?
- A. Unclean leader election should be enabled.
- B. Message retention.ms should be set to -1.
- C. The linger.ms should be set to '0'.
- D. The number of brokers in the cluster should be always odd (3, 5. 7 and so on).
Answer: A
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 # 35
Why does Kafka use ZooKeeper? (Choose two.)
- A. To scale the number of brokers in the cluster
- B. To access information about the leaders and partitions
- C. To prevent replication between clusters
- D. For controller election
Answer: B,D
Explanation:
ZooKeeper stores metadata such as partition leadership and ISR (in-sync replicas), which brokers use to coordinate.
Kafka uses ZooKeeper to perform leader election for the Controller broker, which manages cluster metadata and leadership changes.
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-groups.sh
- B. bin/kafka-consumer-group-throughput.sh
- C. bin/kafka-reassign-partitions.sh
- D. bin/kafka-consumer-lag.sh
Answer: A
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
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=all
- B. acks=0
- C. acks=1
- D. acks=undefined
Answer: B
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 # 38
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. ZooKeeper believes the broker to be dead.
- C. There will be a trigger of the broker's log cleaner thread.
- D. There is backpressure to, and pausing of, Kafka clients.
Answer: B
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 # 39
How can load balancing of Kafka clients across multiple brokers be accomplished?
- A. Offsets
- B. Connectors
- C. Replicas
- D. Partitions
Answer: D
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 # 40
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. Thrift
- B. JSON
- C. Protobuf
- D. gRPC
- E. Avro
Answer: B,C,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 # 41
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=all
- B. acks=0
- C. acks=1
- D. acks=undefined
Answer: B
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 # 42
Which connector type takes data from a topic and sends it to an external data system?
- A. Sink Connector
- B. SvsIog Connector
- C. Streams Connector
- D. Source Connector
Answer: A
Explanation:
A Sink Connector reads data from a Kafka topic and writes it to an external data system, such as a database, file system, or cloud service.
NEW QUESTION # 43
Which property in broker configuration specifies that a broker belongs to a particular rack?
Which property in broker configuration specifies that a broker belongs to a particular rack?
- A. broker.rack
- B. client.rack
- C. zookeeper.rack
- D. kafka.rack
Answer: A
Explanation:
The broker.rack property is used in a Kafka broker's configuration to specify the rack or availability zone the broker belongs to. This is important for rack-aware replica placement, allowing Kafka to distribute replicas across different racks for fault tolerance.
NEW QUESTION # 44
Which valid security protocols are included for broker listeners? (Choose three.)
- A. SASL
- B. PLAINTEXT
- C. GSSAPI
- D. SSL
- E. SASL_SSL
Answer: B,D,E
NEW QUESTION # 45
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 number of partitions.
- C. Increase the number of Connect Nodes.
- D. Increase the replication factor and increase the number of Connect Tasks.
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 # 46
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