What Verified CCDAK Study Guide Is

NEW QUESTION 1
In Kafka, every broker... (select three)

• A. contains all the topics and all the partitions
• B. knows all the metadata for all topics and partitions
• C. is a controller
• D. knows the metadata for the topics and partitions it has on its disk
• E. is a bootstrap broker
• F. contains only a subset of the topics and the partitions

Answer: BEF

Explanation:
Kafka topics are divided into partitions and spread across brokers. Each brokers knows about all the metadata and each broker is a bootstrap broker, but only one of them is elected controller

NEW QUESTION 2
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?

• A. The producer will automatically produce to the broker that has been elected leader
• B. The topic will be unavailable
• C. The producer will stop working

Answer: A

Explanation:
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 3
A producer application in a developer machine was able to send messages to a Kafka topic. After copying the producer application into another developer's machine, the producer is able to connect to Kafka but unable to produce to the same Kafka topic because of an authorization issue. What is the likely issue?

• A. Broker configuration needs to be changed to allow a different producer
• B. You cannot copy a producer application from one machine to another
• C. The Kafka ACL does not allow another machine IP
• D. The Kafka Broker needs to be rebooted

Answer: C

Explanation:
ACLs take "Host" as a parameter, which represents an IP. It can be * (all IP), or a specific IP. Here, it's a specific IP as moving a producer to a different machine breaks the consumer, so the ACL needs to be updated

NEW QUESTION 4
What is the risk of increasing max.in.flight.requests.per.connection while also enabling retries in a producer?

• A. At least once delivery is not guaranteed
• B. Message order not preserved
• C. Reduce throughput
• D. Less resilient

Answer: B

Explanation:
Some messages may require multiple retries. If there are more than 1 requests in flight, it may result in messages received out of order. Note an exception to this rule is if you enable the producer settingenable.idempotence=true which takes care of the out of ordering case on its own. Seehttps://issues.apache.org/jira/browse/KAFKA-5494

NEW QUESTION 5
A kafka topic has a replication factor of 3 and min.insync.replicas setting of 2. How many brokers can go down before a producer with acks=all can't produce?

• A. 2
• B. 1
• C. 3

Answer: C

Explanation:
acks=all and min.insync.replicas=2 means we must have at least 2 brokers up for the partition to be available

NEW QUESTION 6
If a topic has a replication factor of 3...

• A. 3 replicas of the same data will live on 1 broker
• B. Each partition will live on 4 different brokers
• C. Each partition will live on 2 different brokers
• D. Each partition will live on 3 different brokers

Answer: D

Explanation:
Replicas are spread across available brokers, and each replica = one broker. RF 3 = 3 brokers

NEW QUESTION 7
What happens if you write the following code in your producer? producer.send(producerRecord).get()

• A. Compression will be increased
• B. Throughput will be decreased
• C. It will force all brokers in Kafka to acknowledge the producerRecord
• D. Batching will be increased

Answer: B

Explanation:
Using Future.get() to wait for a reply from Kafka will limit throughput.

NEW QUESTION 8
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 9
An ecommerce wesbite sells some custom made goods. What's the natural way of modeling this data in Kafka streams?

• A. Purchase as stream, Product as stream, Customer as stream
• B. Purchase as stream, Product as table, Customer as table
• C. Purchase as table, Product as table, Customer as table
• D. Purchase as stream, Product as table, Customer as stream

Answer: B

Explanation:
Mostly-static data is modeled as a table whereas business transactions should be modeled as a stream.

NEW QUESTION 10
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?

• A. offset 2311
• B. offset 0
• C. offset 45
• D. it will crash

Answer: A

Explanation:
Latest means that data retrievals will start from where the offsets currently end

NEW QUESTION 11
A consumer wants to read messages from a specific partition of a topic. How can this be achieved?

• A. Call subscribe(String topic, int partition) passing the topic and partition number as the arguments
• B. Call assign() passing a Collection of TopicPartitions as the argument
• C. Call subscribe() passing TopicPartition as the argument

Answer: B

Explanation:
assign() can be used for manual assignment of a partition to a consumer, in which case subscribe() must not be used. Assign() takes a collection of TopicPartition object as an argument https://kafka.apache.org/23/javadoc/org/apache/kafka/clients/consumer/KafkaConsumer.ht
ml#assign-java.util.Collection-

NEW QUESTION 12
Select all the way for one consumer to subscribe simultaneously to the following topics - topic.history, topic.sports, topic.politics? (select two)

• A. consumer.subscribe(Pattern.compile("topic\..*"));
• B. consumer.subscribe("topic.history"); consumer.subscribe("topic.sports"); consumer.subscribe("topic.politics");
• C. consumer.subscribePrefix("topic.");
• D. consumer.subscribe(Arrays.asList("topic.history", "topic.sports", "topic.politics"));

Answer: AD

Explanation:
Multiple topics can be passed as a list or regex pattern.

NEW QUESTION 13
There are 3 producers writing to a topic with 5 partitions. There are 10 consumers consuming from the topic as part of the same group. How many consumers will remain idle?

• A. 10
• B. 3
• C. None
• D. 5

Answer: D

Explanation:
One consumer per partition assignment will keep 5 consumers idle.

NEW QUESTION 14
What is true about replicas ?

• A. Produce requests can be done to the replicas that are followers
• B. Produce and consume requests are load-balanced between Leader and Follower replicas
• C. Leader replica handles all produce and consume requests
• D. Follower replica handles all consume requests

Answer: C

Explanation:
Replicas are passive - they don't handle produce or consume request. Produce and consume requests get sent to the node hosting partition leader.

NEW QUESTION 15
Where are the dynamic configurations for a topic stored?

• A. In Zookeeper
• B. In an internal Kafka topic topic_configuratins
• C. In server.properties
• D. On the Kafka broker file system

Answer: A

Explanation:
Dynamic topic configurations are maintained in Zookeeper.

NEW QUESTION 16
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 17
You are sending messages with keys to a topic. To increase throughput, you decide to
increase the number of partitions of the topic. Select all that apply.

• A. All the existing records will get rebalanced among the partitions to balance load
• B. New records with the same key will get written to the partition where old records with that key were written
• C. New records may get written to a different partition
• D. Old records will stay in their partitions

Answer: CD

Explanation:
Increasing the number of partition causes new messages keys to get hashed differently, and breaks the guarantee "same keys goes to the same partition". Kafka logs are immutable and the previous messages are not re-shuffled

NEW QUESTION 18
Which KSQL queries write to Kafka?

• A. COUNT and JOIN
• B. SHOW STREAMS and EXPLAIN <query> statements
• C. CREATE STREAM WITH <topic> and CREATE TABLE WITH <topic>
• D. CREATE STREAM AS SELECT and CREATE TABLE AS SELECT

Answer: CD

Explanation:
SHOW STREAMS and EXPLAIN <query> statements run against the KSQL server that the KSQL client is connected to. They don't communicate directly with Kafka. CREATE STREAM WITH <topic> and CREATE TABLE WITH <topic> write metadata to the KSQL command topic. Persistent queries based on CREATE STREAM AS SELECT and CREATE TABLE AS SELECT read and write to Kafka topics. Non-persistent queries based on SELECT that are stateless only read from Kafka topics, for example SELECT … FROM foo WHERE …. Non-persistent queries that are stateful read and write to Kafka, for example, COUNT and JOIN. The data in Kafka is deleted automatically when you terminate the query with CTRL-C.

NEW QUESTION 19
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