2022 Realistic CCDAK Dumps Questions To Gain Brilliant Result
Start your CCDAK Exam Questions Preparation with Updated 150 Questions
NEW QUESTION 22
To produce data to a topic, a producer must provide the Kafka client with...
- A. any broker from the cluster and the topic name and the partitions list
- B. all the brokers from the cluster and the topic name
- C. the list of brokers that have the data, the topic name and the partitions list
- D. any broker from the cluster and the topic name
Answer: D
Explanation:
All brokers can respond to a Metadata request, so a client can connect to any broker in the cluster and then figure out on its own which brokers to send data to.
NEW QUESTION 23
Which Kafka CLI should you use to consume from a topic?
- A. kafka-console-consumer
- B. kafka-topics
- C. kafka-consumer-groups
- D. kafka-console
Answer: A
Explanation:
Examplekafka-console-consumer --bootstrap-server 127.0.0.1:9092 --topic test --from-beginning
NEW QUESTION 24
What is the risk of increasing max.in.flight.requests.per.connection while also enabling retries in a producer?
- A. Less resilient
- B. Message order not preserved
- C. Reduce throughput
- D. At least once delivery is not guaranteed
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 25
Where are the dynamic configurations for a topic stored?
- A. On the Kafka broker file system
- B. In server.properties
- C. In an internal Kafka topic __topic_configuratins
- D. In Zookeeper
Answer: D
Explanation:
Dynamic topic configurations are maintained in Zookeeper.
NEW QUESTION 26
There are five brokers in a cluster, a topic with 10 partitions and replication factor of 3, and a quota of producer_bytes_rate of 1 MB/sec has been specified for the client. What is the maximum throughput allowed for the client?
- A. 5 MB/s
- B. 10 MB/s
- C. 0.33 MB/s
- D. 1 MB/s
Answer: A
Explanation:
Each producer is allowed to produce @ 1MB/s to a broker. Max throughput 5 * 1MB, because we have 5 brokers.
NEW QUESTION 27
In Avro, adding a field to a record without default is a __ schema evolution
- A. backward
- B. full
- C. forward
- D. breaking
Answer: C
Explanation:
Clients with old schema will be able to read records saved with new schema.
NEW QUESTION 28
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. BufferExhaustedException
- B. BrokerNotAvailableException
- C. SerializationException
- D. InvalidPartitionsException
Answer: A,C
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 29
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?
- A. 4 GB
- B. 16 GB
- C. 128 GB
- D. 512 MB
Answer: A
Explanation:
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
NEW QUESTION 30
Using the Confluent Schema Registry, where are Avro schema stored?
- A. In the _schemas topic
- B. In the Schema Registry embedded SQL database
- C. In the Zookeeper node /schemas
- D. In the message bytes themselves
Answer: A
Explanation:
The Schema Registry stores all the schemas in the _schemas Kafka topic
NEW QUESTION 31
We have a store selling shoes. What dataset is a great candidate to be modeled as a KTable in Kafka Streams?
- A. Inventory contents right now
- B. Money made until now
- C. The transaction stream
- D. Items returned
Answer: B,D
Explanation:
Aggregations of stream are stored in table, whereas Streams must be modeled as a KStream to avoid data explosion
NEW QUESTION 32
To allow consumers in a group to resume at the previously committed offset, I need to set the proper value for...
- A. group.id
- B. enable.auto.commit
- C. value.deserializer
- D. auto.offset.resets
Answer: A
Explanation:
Setting a group.id that's consistent across restarts will allow your consumers part of the same group to resume reading from where offsets were last committed for that group
NEW QUESTION 33
If a topic has a replication factor of 3...
- A. Each partition will live on 2 different brokers
- B. Each partition will live on 4 different brokers
- C. Each partition will live on 3 different brokers
- D. 3 replicas of the same data will live on 1 broker
Answer: C
Explanation:
Replicas are spread across available brokers, and each replica = one broker. RF 3 = 3 brokers
NEW QUESTION 34
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.html#assign-java.util.Collection-
NEW QUESTION 35
Producing with a key allows to...
- A. Influence partitioning of the producer messages
- B. Allow a Kafka Consumer to subscribe to a (topic,key) pair and only receive that data
- C. Add more information to my message
- D. Ensure per-record level security
Answer: A
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 36
Your producer is producing at a very high rate and the batches are completely full each time. How can you improve the producer throughput? (select two)
- A. Disable compression
- B. Decrease linger.ms
- C. Enable compression
- D. Increase batch.size
- E. Decrease batch.size
Answer: C,D
Explanation:
Increase linger.ms
Explanation:
batch.size controls how many bytes of data to collect before sending messages to the Kafka broker. Set this as high as possible, without exceeding available memory. Enabling compression can also help make more compact batches and increase the throughput of your producer. Linger.ms will have no effect as the batches are already full
NEW QUESTION 37
You are doing complex calculations using a machine learning framework on records fetched from a Kafka topic. It takes more about 6 minutes to process a record batch, and the consumer enters rebalances even though it's still running. How can you improve this scenario?
- A. Increase session.timeout.ms to 600000
- B. Increase max.poll.interval.ms to 600000
- C. Increase heartbeat.interval.ms to 600000
- D. Add consumers to the consumer group and kill them right away
Answer: B
Explanation:
Here, we need to change the setting max.poll.interval.ms (default 300000) to its double in order to tell Kafka a consumer should be considered dead if the consumer only if it hasn't called the .poll() method in 10 minutes instead of 5.
NEW QUESTION 38
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