Valid CCDAK Study Guide For Helping You Pass Confluent Certified Developer for Apache Kafka Certification Examination

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ITExamShop offers valid CCDAK study guide for helping you pass Confluent Certified Developer for Apache Kafka Certification Examination successfully. The CCDAK Confluent certification exam validates your Apache Kafka®️ expertise with a well respected and highly recognized Confluent Certification. From beginners to advanced users, you’ll find comprehensive learning resources, study guides, and step-by-step training materials to help you get certified the easiest way possible. The valid CCDAK study guide with real exam questions and precise answers of ITExamShop are based on the CCDAK exam objectives, you’ll need to do with regards to the preparation on the CCDAK exam questions would be to appear for the valid and most up-to-date CCDAK study guide. These CCDAK exam questions and answers will play a essential function inside your preparation for the Confluent Certified Developer for Apache Kafka Certification Examination.

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1. What kind of delivery guarantee this consumer offers?

while (true) {

ConsumerRecords<String, String> records = consumer.poll(100);

try {

consumer.commitSync();

} catch (CommitFailedException e) { log.error("commit failed", e)

}

for (ConsumerRecord<String, String> record records)

{

System.out.printf("topic = %s, partition = %s, offset = %d, customer = %s, country = %s

",

record.topic(), record.partition(), record.offset(), record.key(), record.value());

}

}

Exactly-once

At-least-once

At-most-once

2. What is the disadvantage of request/response communication?

Scalability

Reliability

Coupling

Cost

3. You are using JDBC source connector to copy data from a table to Kafka topic. There is one connector created with max.tasks equal to 2 deployed on a cluster of 3 workers .

How many tasks are launched?

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

You can use the same broker.id as long as they have different broker.rack configuration

Replicas for a partition are placed in the same rack

Replicas for a partition are spread across different racks

Each rack contains all the topics and partitions, effectively making Kafka highly available

5. What data format isn't natively available with the Confluent REST Proxy?

avro

binary

protobuf

json

6. Which of the following setting increases the chance of batching for a Kafka Producer?

Increase batch.size

Increase message.max.bytes

Increase the number of producer threads

Increase linger.ms

7. How often is log compaction evaluated?

Every time a new partition is created

Every time a segment is closed

Every time a message is sent to Kafka

Every time a message is flushed to disk

8. How will you read all the messages from a topic in your KSQL query?

KSQL reads from the beginning of a topic, by default.

KSQL reads from the end of a topic. This cannot be changed.

Use KSQL CLI to set auto.offset.reset property to earliest

9. A consumer has auto.offset.reset=latest, and the topic partition currently has data for offsets going from 45 to 2311. The consumer group never committed offsets for the topic before.

Where will the consumer read from?

offset 2311

offset 0

offset 45

it will crash

10. The exactly once guarantee in the Kafka Streams is for which flow of data?

Kafka => Kafka

Kafka => External

External => Kafka

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11. What happens if you write the following code in your producer?

producer.send(producerRecord).get()

Compression will be increased

Throughput will be decreased

It will force all brokers in Kafka to acknowledge the producerRecord

Batching will be increased

12. You have a consumer group of 12 consumers and when a consumer gets killed by the process management system, rather abruptly, it does not trigger a graceful shutdown of your consumer. Therefore, it takes up to 10 seconds for a rebalance to happen. The business would like to have a 3 seconds rebalance time .

What should you do? (select two)

Increase session.timeout.ms

Decrease session.timeout.ms

Increase heartbeat.interval.ms

decrease max.poll.interval.ms

increase max.poll.interval.ms

Decrease heartbeat.interval.ms

13. A topic "sales" is being produced to in the Americas region. You are mirroring this topic using Mirror Maker to the European region. From there, you are only reading the topic for analytics purposes .

What kind of mirroring is this?

Passive-Passive

Active-Active

Active-Passive

14. A consumer starts and has auto.offset.reset=latest, and the topic partition currently has data for offsets going from 45 to 2311. The consumer group has committed the offset 643 for the topic before.

Where will the consumer read from?

it will crash

offset 2311

offset 643

offset 45

15. A producer just sent a message to the leader broker for a topic partition. The producer used acks=1 and therefore the data has not yet been replicated to followers.

Under which conditions will the consumer see the message?

Right away

When the message has been fully replicated to all replicas

Never, the produce request will fail

When the high watermark has advanced

16. You are receiving orders from different customer in an "orders" topic with multiple partitions. Each message has the customer name as the key. There is a special customer named ABC that generates a lot of orders and you would like to reserve a partition exclusively for ABC. The rest of the message should be distributed among other partitions .

How can this be achieved?

Add metadata to the producer record

Create a custom partitioner

All messages with the same key will go the same partition, but the same partition may have messages with different keys. It is not possible to reserve

Define a Kafka Broker routing rule

17. In Avro, removing or adding a field that has a default is a __ schema evolution

full

backward

breaking

forward

18. Compaction is enabled for a topic in Kafka by setting log.cleanup.policy=compact .

What is true about log compaction?

After cleanup, only one message per key is retained with the first value

Each message stored in the topic is compressed

Kafka automatically de-duplicates incoming messages based on key hashes

After cleanup, only one message per key is retained with the latest value Compaction changes the offset of messages

19. A client connects to a broker in the cluster and sends a fetch request for a partition in a topic. It gets an exception Not Leader For Partition Exception in the response .

How does client handle this situation?

Get the Broker id from Zookeeper that is hosting the leader replica and send request to it

Send metadata request to the same broker for the topic and select the broker hosting the leader replica

Send metadata request to Zookeeper for the topic and select the broker hosting the leader replica

Send fetch request to each Broker in the cluster

20. If I supply the setting compression.type=snappy to my producer, what will happen? (select two)

The Kafka brokers have to de-compress the data

The Kafka brokers have to compress the data

The Consumers have to de-compress the data

The Consumers have to compress the data

The Producers have to compress the data

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21. If I produce to a topic that does not exist, and the broker setting auto.create.topic.enable=true, what will happen?

Kafka will automatically create the topic with 1 partition and 1 replication factor

Kafka will automatically create the topic with the indicated producer settings num.partitions and default.replication.factor

Kafka will automatically create the topic with the broker settings num.partitions and default.replication.factor

Kafka will automatically create the topic with num.partitions=#of brokers and replication.factor=3

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Valid CCDAK Study Guide For Helping You Pass Confluent Certified Developer for Apache Kafka Certification Examination

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