2022 Updated Verified CCDAK Q&As – Pass Guarantee or Full Refund [Q28-Q42]

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2022 Updated Verified CCDAK Q&As – Pass Guarantee or Full Refund

[Jun-2022] CCDAK Certification with Actual Questions from SurePassExams

NEW QUESTION 28
We would like to be in an at-most once consuming scenario. Which offset commit strategy would you recommend?

Commit the offsets on disk, after processing the data

Do not commit any offsets and read from beginning

Commit the offsets in Kafka, after processing the data

Commit the offsets in Kafka, before processing the data

Here, we must commit the offsets right after receiving a batch from a call to .poll()

NEW QUESTION 29
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?

NotEnoughReplicasException will be returned

Produce request is honored with single in-sync replica

Produce request will block till one of the two unavailable partition is available again.

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

NEW QUESTION 30
A Kafka producer application wants to send log messages to a topic that does not include any key. What are the properties that are mandatory to configure for the producer configuration? (select three)

bootstrap.servers

partition

key.serializer

value.serializer

key

value

Both key and value serializer are mandatory.

NEW QUESTION 31
If I want to have an extremely high confidence that leaders and replicas have my data, I should use

acks=all, replication factor=2, min.insync.replicas=1

acks=1, replication factor=3, min.insync.replicas=2

acks=all, replication factor=3, min.insync.replicas=2

acks=all, replication factor=3, min.insync.replicas=1

acks=all means the leader will wait for all in-sync replicas to acknowledge the record. Also the min in-sync replica setting specifies the minimum number of replicas that need to be in-sync for the partition to remain available for writes.

NEW QUESTION 32
You have a Zookeeper cluster that needs to be able to withstand the loss of 2 servers and still be able to function. What size should your Zookeeper cluster have?

Your Zookeeper cluster needs to have an odd number of servers, and must maintain a majority of servers up to be able to vote. Therefore, a 2N+1 zookeeper cluster can survive to N zookeeper being down, so here the right answer is N=2, 2*N+1=5

NEW QUESTION 33
What’s a Kafka partition made of?

One file and one index

One file

One file and two indexes per segment

One file and two indexes

Kafka partitions are made of segments (usually each segment is 1GB), and each segment has two corresponding indexes (offset index and time index)

NEW QUESTION 34
By default, which replica will be elected as a partition leader? (select two)

Preferred leader broker if it is in-sync and auto.leader.rebalance.enable=true

Any of the replicas

Preferred leader broker if it is in-sync and auto.leader.rebalance.enable=false

An in-sync replica

Preferred leader is a broker that was leader when topic was created. It is preferred because when partitions are first created, the leaders are balanced between brokers. Otherwise, any of the in-sync replicas (ISR) will be elected leader, as long as unclean.leader.election=false (by default)

NEW QUESTION 35
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

The broker settings comes into play when a topic is auto created

NEW QUESTION 36
What is not a valid authentication mechanism in Kafka?

SASL/GSSAPI

SASL/SCRAM

SAML

SSL

Learn more about security herehttps://kafka.apache.org/documentation/#security

NEW QUESTION 37
A producer application was sending messages to a partition with a replication factor of 2 by connecting to Broker 1 that was hosting partition leader. If the Broker 1 goes down, what will happen?

The producer will automatically produce to the broker that has been elected leader

The topic will be unavailable

The producer will stop working

Once the client connects to any broker, it is connected to the entire cluster and in case of leadership changes, the clients automatically do a Metadata Request to an available broker to find out who is the new leader for the topic. Hence the producer will automatically keep on producing to the correct Kafka Broker

NEW QUESTION 38
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

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 39
You have a Kafka cluster and all the topics have a replication factor of 3. One intern at your company stopped a broker, and accidentally deleted all the data of that broker on the disk. What will happen if the broker is restarted?

The broker will start, and other topics will also be deleted as the broker data on the disk got deleted

The broker will start, and won’t be online until all the data it needs to have is replicated from other leaders

The broker will crash

The broker will start, and won’t have any data. If the broker comes leader, we have a data loss

Kafka replication mechanism makes it resilient to the scenarios where the broker lose data on disk, but can recover from replicating from other brokers. This makes Kafka amazing!

NEW QUESTION 40
What is the default port that the KSQL server listens on?

9092

8088

8083

2181

Default port of KSQL server is 8088

NEW QUESTION 41
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

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