What Simulation CCDAK Real Exam Is

NEW QUESTION 1
When auto.create.topics.enable is set to true in Kafka configuration, what are the circumstances under which a Kafka broker automatically creates a topic? (select three)

• A. Client requests metadata for a topic
• B. Consumer reads message from a topic
• C. Client alters number of partitions of a topic
• D. Producer sends message to a topic

Answer: ABD

Explanation:
A kafka broker automatically creates a topic under the following circumstances- When a producer starts writing messages to the topic - When a consumer starts reading messages from the topic - When any client requests metadata for the topic

NEW QUESTION 2
Producing with a key allows to...

• A. Ensure per-record level security
• B. Influence partitioning of the producer messages
• C. Add more information to my message
• D. Allow a Kafka Consumer to subscribe to a (topic,key) pair and only receive that data

Answer: B

Explanation:
Keys are necessary if you require strong ordering or grouping for messages that share the same key. If you require that messages with the same key are always seen in the correct order, attaching a key to messages will ensure messages with the same key always go to the same partition in a topic. Kafka guarantees order within a partition, but not across partitions in a topic, so alternatively not providing a key - which will result in round-robin distribution across partitions - will not maintain such order.

NEW QUESTION 3
What is a generic unique id that I can use for messages I receive from a consumer?

• A. topic + partition + timestamp
• B. topic + partition + offset
• C. topic + timestamp

Answer: B

Explanation:
(Topic,Partition,Offset) uniquely identifies a message in Kafka

NEW QUESTION 4
What happens when broker.rack configuration is provided in broker configuration in Kafka cluster?

• A. You can use the same broker.id as long as they have different broker.rack configuration
• B. Replicas for a partition are placed in the same rack
• C. Replicas for a partition are spread across different racks
• D. Each rack contains all the topics and partitions, effectively making Kafka highly available

Answer: C

Explanation:
Partitions for newly created topics are assigned in a rack alternating manner, this is the only change broker.rack does

NEW QUESTION 5
How often is log compaction evaluated?

• A. Every time a new partition is created
• B. Every time a segment is closed
• C. Every time a message is sent to Kafka
• D. Every time a message is flushed to disk

Answer: B

Explanation:
Log compaction is evaluated every time a segment is closed. It will be triggered if enough data is "dirty" (see dirty ratio config)

NEW QUESTION 6
How will you find out all the partitions where one or more of the replicas for the partition are not in-sync with the leader?

• A. kafka-topics.sh --bootstrap-server localhost:9092 --describe --unavailable- partitions
• B. kafka-topics.sh --zookeeper localhost:2181 --describe --unavailable- partitions
• C. kafka-topics.sh --broker-list localhost:9092 --describe --under-replicated-partitions
• D. kafka-topics.sh --zookeeper localhost:2181 --describe --under-replicated-partitions

Answer: D

NEW QUESTION 7
Kafka is configured with following parameters - log.retention.hours = 168 log.retention.minutes = 168 log.retention.ms = 168 How long will the messages be retained for?

• A. Broker will not start due to bad configuration
• B. 168 ms
• C. 168 hours
• D. 168 minutes

Answer: B

Explanation:
If more than one similar config is specified, the smaller unit size will take precedence.

NEW QUESTION 8
What is the default port that the KSQL server listens on?

• A. 9092
• B. 8088
• C. 8083
• D. 2181

Answer: B

Explanation:
Default port of KSQL server is 8088

NEW QUESTION 9
Which of the following setting increases the chance of batching for a Kafka Producer?

• A. Increase batch.size
• B. Increase message.max.bytes
• C. Increase the number of producer threads
• D. Increase linger.ms

Answer: D

Explanation:
linger.ms forces the producer to wait to send messages, hence increasing the chance of creating batches

NEW QUESTION 10
The kafka-console-consumer CLI, when used with the default options

• A. uses a random group id
• B. always uses the same group id
• C. does not use a group id

Answer: A

Explanation:
If a group is not specified, the kafka-console-consumer generates a random consumer group.

NEW QUESTION 11
There are two consumers C1 and C2 belonging to the same group G subscribed to topics T1 and T2. Each of the topics has 3 partitions. How will the partitions be assigned to consumers with Partition Assigner being Round Robin Assigner?

• A. C1 will be assigned partitions 0 and 2 from T1 and partition 1 from T2. C2 will have partition 1 from T1 and partitions 0 and 2 from T2.
• B. Two consumers cannot read from two topics at the same time
• C. C1 will be assigned partitions 0 and 1 from T1 and T2, C2 will be assigned partition 2 from T1 and T2.
• D. All consumers will read from all partitions

Answer: A

Explanation:
The correct option is the only one where the two consumers share an equal number of partitions amongst the two topics of three partitions. An interesting article to read ishttps://medium.com/@anyili0928/what-i-have-learned-from-kafka-partition-assignment- strategy-799fdf15d3ab

NEW QUESTION 12
We have a store selling shoes. What dataset is a great candidate to be modeled as a KTable in Kafka Streams?

• A. Money made until now
• B. The transaction stream
• C. Items returned
• D. Inventory contents right now

Answer: AC

Explanation:
Aggregations of stream are stored in table, whereas Streams must be modeled as a KStream to avoid data explosion

NEW QUESTION 13
You want to sink data from a Kafka topic to S3 using Kafka Connect. There are 10 brokers in the cluster, the topic has 2 partitions with replication factor of 3. How many tasks will you configure for the S3 connector?

• A. 10
• B. 6
• C. 3
• D. 2

Answer: D

Explanation:
You cannot have more sink tasks (= consumers) than the number of partitions, so 2.

NEW QUESTION 14
A topic has three replicas and you set min.insync.replicas to 2. If two out of three replicas are not available, what happens when a produce request with acks=all is sent to broker?

• A. NotEnoughReplicasException will be returned
• B. Produce request is honored with single in-sync replica
• C. Produce request will block till one of the two unavailable partition is available again.

Answer: A

Explanation:
With this configuration, a single in-sync replica becomes read-only. Produce request will receive NotEnoughReplicasException.

NEW QUESTION 15
How do you create a topic named test with 3 partitions and 3 replicas using the Kafka CLI?

• A. bin/kafka-topics.sh --create --broker-list localhost:9092 --replication-factor 3 --partitions 3--topic test
• B. bin/kafka-topics-create.sh --zookeeper localhost:9092 --replication-factor 3 --partitions 3--topic test
• C. bin/kafka-topics.sh --create --bootstrap-server localhost:9092 --replication-factor 3 -- partitions 3 --topic test
• D. bin/kafka-topics.sh --create --bootstrap-server localhost:2181 --replication-factor 3 -- partitions 3 --topic test

Answer: C

Explanation:
As of Kafka 2.3, the kafka-topics.sh command can take --bootstrap-server localhost:9092 as an argument. You could also use the (now deprecated) option of --zookeeper localhost:2181.

NEW QUESTION 16
A bank uses a Kafka cluster for credit card payments. What should be the value of the property unclean.leader.election.enable?

• A. FALSE
• B. TRUE

Answer: A

Explanation:
Setting unclean.leader.election.enable to true means we allow out-of-sync replicas to become leaders, we will lose messages when this occurs, effectively losing credit card payments and making our customers very angry.

NEW QUESTION 17
In Avro, removing or adding a field that has a default is a schema evolution

• A. full
• B. backward
• C. breaking
• D. forward

Answer: A

Explanation:
Clients with new schema will be able to read records saved with old schema and clients with old schema will be able to read records saved with new schema.

NEW QUESTION 18
What exceptions may be caught by the following producer? (select two) ProducerRecord<String, String> record =
new ProducerRecord<>("topic1", "key1", "value1"); try {
producer.send(record);
} catch (Exception e) { e.printStackTrace();
}

• A. BrokerNotAvailableException
• B. SerializationException
• C. InvalidPartitionsException
• D. BufferExhaustedException

Answer: BD

Explanation:
These are the client side exceptions that may be encountered before message is sent to the broker, and before a future is returned by the .send() method.

NEW QUESTION 19
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