Latest CCDAK exam dumps with real Confluent questions and answers [Q49-Q72]

Aktuelle CCDAK-Prüfungsunterlagen mit echten Confluent-Fragen und Antworten [Q49-Q72]

ExamBoosts 3. September 2022 CCDAK > Konfluent 0

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Latest CCDAK exam dumps with real Confluent questions and answers

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Q49. A Zookeeper configuration has tickTime of 2000, initLimit of 20 and syncLimit of 5. What’s the timeout value for followers to connect to Zookeeper?

20 sec

10 sec

2000 ms

40 sec

tick time is 2000 ms, and initLimit is the config taken into account when establishing a connection to Zookeeper, so the answer is 2000 * 20 = 40000 ms = 40s

Q50. The exactly once guarantee in the Kafka Streams is for which flow of data?

Kafka => Kafka

Kafka => External

External => Kafka

Kafka Streams can only guarantee exactly once processing if you have a Kafka to Kafka topology.

Q51. Using the Confluent Schema Registry, where are Avro schema stored?

In the Schema Registry embedded SQL database

In the Zookeeper node /schemas

In the message bytes themselves

In the _schemas topic

The Schema Registry stores all the schemas in the _schemas Kafka topic

Q52. Select all the way for one consumer to subscribe simultaneously to the following topics – topic.history, topic.sports, topic.politics? (select two)

consumer.subscribe(Pattern.compile(“topic..*”));

consumer.subscribe(“topic.history”); consumer.subscribe(“topic.sports”); consumer.subscribe(“topic.politics”);

consumer.subscribePrefix(“topic.”);

consumer.subscribe(Arrays.asList(“topic.history”, “topic.sports”, “topic.politics”));

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

Q53. What is the disadvantage of request/response communication?

Scalability

Reliability

Coupling

Kosten

Point-to-point (request-response) style will couple client to the server.

Q54. A Zookeeper ensemble contains 5 servers. What is the maximum number of servers that can go missing and the ensemble still run?

majority consists of 3 zk nodes for 5 nodes zk cluster, so 2 can fail

Q55. 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

Consumers can set auto.offset.reset property to earliest to start consuming from beginning. For KSQL, SET ‘auto.offset.reset’=’earliest’;

Q56. If I want to send binary data through the REST proxy to topic “test_binary”, it needs to be base64 encoded. A consumer connecting directly into the Kafka topic

“test_binary” will receive

binary data

avro data

json data

base64 encoded data, it will need to decode it

On the producer side, after receiving base64 data, the REST Proxy will convert it into bytes and then send that bytes payload to Kafka. Therefore consumers reading directly from Kafka will receive binary data.

Q57. An ecommerce website maintains two topics – a high volume “purchase” topic with 5 partitions and low volume “customer” topic with 3 partitions. You would like to do a stream-table join of these topics. How should you proceed?

Repartition the purchase topic to have 3 partitions

Repartition customer topic to have 5 partitions

Model customer as a GlobalKTable

Do a KStream / KTable join after a repartition step

In case of KStream-KStream join, both need to be co-partitioned. This restriction is not applicable in case of join with GlobalKTable, which is the most efficient here.

Q58. What is true about replicas ?

Produce requests can be done to the replicas that are followers

Produce and consume requests are load-balanced between Leader and Follower replicas

Leader replica handles all produce and consume requests

Follower replica handles all consume requests

Replicas are passive – they don’t handle produce or consume request. Produce and consume requests get sent to the node hosting partition leader.

Q59. A consumer wants to read messages from a specific partition of a topic. How can this be achieved?

Call subscribe(String topic, int partition) passing the topic and partition number as the arguments

Call assign() passing a Collection of TopicPartitions as the argument

Call subscribe() passing TopicPartition as the argument

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.html#assign-java.util.Collection-

Q60. Your topic is log compacted and you are sending a message with the key K and value null. What will happen?

The broker will delete all messages with the key K upon cleanup

The producer will throw a Runtime exception

The broker will delete the message with the key K and null value only upon cleanup

The message will get ignored by the Kafka broker

Sending a message with the null value is called a tombstone in Kafka and will ensure the log compacted topic does not contain any messages with the key K upon compaction

Q61. What is a generic unique id that I can use for messages I receive from a consumer?

topic + partition + timestamp

topic + partition + offset

topic + timestamp

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

Q62. 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

Q63. 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

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

Q64. is KSQL ANSI SQL compliant?

Nein

KSQL is not ANSI SQL compliant, for now there are no defined standards on streaming SQL languages

Q65. We have a store selling shoes. What dataset is a great candidate to be modeled as a KTable in Kafka Streams?

Money made until now

The transaction stream

Items returned

Inventory contents right now

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

Q66. How much should be the heap size of a broker in a production setup on a machine with 256 GB of RAM, in PLAINTEXT mode?

4 GB

128 GB

16 GB

512 MB

In Kafka, a small heap size is needed, while the rest of the RAM goes automatically to the page cache (managed by the OS). The heap size goes slightly up if you need to enable SSL

Q67. 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)

Q68. You are building a consumer application that processes events from a Kafka topic. What is the most important metric to monitor to ensure real-time processing?

UnderReplicatedPartitions

records-lag-max

MessagesInPerSec

BytesInPerSec

This metric shows the current lag (number of messages behind the broker)

Q69. What is the default port that the KSQL server listens on?

9092

8088

8083

2181

Default port of KSQL server is 8088

Q70. What is the protocol used by Kafka clients to securely connect to the Confluent REST Proxy?

Kerberos

SASL

HTTPS (SSL/TLS)

HTTP

TLS – but it is still called SSL.

Q71. 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

A Custom Partitioner allows you to easily customise how the partition number gets computed from a source message.

Q72. 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

In case the consumer has the wrong leader of a partition, it will issue a metadata request. The Metadata request can be handled by any node, so clients know afterwards which broker are the designated leader for the topic partitions. Produce and consume requests can only be sent to the node hosting partition leader.

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