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NEW QUESTION # 65
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. Increase batch.size
- B. Decrease batch.size
- C. Decrease linger.ms
- D. Disable compression
- E. Enable compression
Answer: A,E
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 # 66
The rule "same key goes to the same partition" is true unless...
- A. the number of partition changes
- B. the number of kafka broker changes
- C. the number of producer changes
- D. the replication factor changes
Answer: A
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 # 67
A topic receives all the orders for the products that are available on a commerce site. Two applications want to process all the messages independently - order fulfilment and monitoring. The topic has 4 partitions, how would you organise the consumers for optimal performance and resource usage?
- A. Create 8 consumers in the same group with 4 consumers for each application
- B. Create four consumers in the same group, one for each partition - two for fulfilment and two for monitoring
- C. Create two consumer groups for two applications with 4 consumers in each
- D. Create two consumers groups for two applications with 8 consumers in each
Answer: C
Explanation:
two partitions groups - one for each application so that all messages are delivered to both the application. 4 consumers in each as there are 4 partitions of the topic, and you cannot have more consumers per groups than the number of partitions (otherwise they will be inactive and wasting resources)
NEW QUESTION # 68
You have a consumer group with default configuration settings reading messages from your Kafka cluster.
You want to optimize its throughput so the consumer group processes more messages in the same amount of time.
Which changes increase the consumption throughput?
- A. Remove some consumers from the consumer group.
- B. Disable auto commit and have the consumers manually commit offsets.
- C. Increase the number of bytes the consumers read with each fetch request.
- D. Decrease the session timeout of each consumer.
Answer: C
NEW QUESTION # 69
You are working on an Orders microservice Thai is publishing messages lo an Orders topic. II is a business requirement that the Orders for a given customer are processed sequentially. Also, the Orders topic is partitioned tor scalability.
Which factors would you need to address during application development?
- A. Ensure the message key is set to customer id, max-in-flight requests per connection is set to less than or equal to 5, and number of partitions is not changed.
- B. Enable producer Idempotence. set batch.size = 1. and set lioq.er.ms to 0. and number ot partitions is not changed.
- C. Enable producer Idempotence. set max-in-flight requests per connection to 1. and number of partitions is not changed.
- D. Enable producer Idempotence. set llnger.ms to 0. set acks='all\ and number of partitions is not changed.
Answer: A
NEW QUESTION # 70
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 hours
- C. 168 ms
- D. 168 minutes
Answer: C
Explanation:
If more than one similar config is specified, the smaller unit size will take precedence.
NEW QUESTION # 71
A producer is sending messages with null key to a topic with 6 partitions using the DefaultPartitioner. Where will the messages be stored?
- A. Partition 0
- B. Partition 5
- C. Any of the topic partitions
- D. The partition for the null key
Answer: B
Explanation:
Message with no keys will be stored with round-robin strategy among partitions.
NEW QUESTION # 72
In Avro, removing a field that does not have a default is a __ schema evolution
- A. breaking
- B. full
- C. backward
- D. forward
Answer: C
Explanation:
Clients with new schema will be able to read records saved with old schema.
NEW QUESTION # 73
Partition leader election is done by
- A. The consumers
- B. The Kafka Broker that is the Controller
- C. Vote amongst the brokers
- D. Zookeeper
Answer: D
Explanation:
The Controller is a broker that is responsible for electing partition leaders
NEW QUESTION # 74
A Zookeeper ensemble contains 3 servers. Over which ports the members of the ensemble should be able to communicate in default configuration? (select three)
- A. 0
- B. 1
- C. 2
- D. 3
- E. 4
- F. 5
Answer: A,D,E
Explanation:
2181 - client port, 2888 - peer port, 3888 - leader port
NEW QUESTION # 75
Where are the dynamic configurations for a topic stored?
- A. In an internal Kafka topic __topic_configuratins
- B. In Zookeeper
- C. On the Kafka broker file system
- D. In server.properties
Answer: B
Explanation:
Dynamic topic configurations are maintained in Zookeeper.
NEW QUESTION # 76
Which of the following is a push query?
- A. SELECT *
FROM NUMBER_OF_TESTS
WHERE ID='10'; - B. SELECT windowstart, windowend, item_id, SUM(quantity)
FROM orders
WINDOW TUMBLING (SIZE 20 SECONDS)
GROUP BY item_id
EMIT CHANGES; - C. CREATE STREAM STUDENTS (ID STRING KEY, SCORE INT)
WITH (kafka_topic='students_topic', value_format='JSON', partitions=4); - D. CREATE TABLE LEFT_TABLE (ID BIGINT PRIMARY KEY, NAME varchar, VALUE bigint) WITH (kafka_topic='left_topic', value_format='JSON', partitions=4);
Answer: B
NEW QUESTION # 77
You want to send a message of size 3 MB to a topic with default message size configuration. How does KafkaProducer handle large messages?
- A. MessageSizeTooLarge exception will be thrown, KafkaProducer retries until the number of retries are exhausted
- B. KafkaProducer divides messages into sizes of message.max.bytes and sends them in order
- C. KafkaProducer divides messages into sizes of max.request.size and sends them in order
- D. MessageSizeTooLarge exception will be thrown, KafkaProducer will not retry and return exception immediately
Answer: D
Explanation:
MessageSizeTooLarge is not a retryable exception.
NEW QUESTION # 78
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)
- A. decrease max.poll.interval.ms
- B. Increase heartbeat.interval.ms
- C. Increase session.timeout.ms
- D. Decrease heartbeat.interval.ms
- E. Decrease session.timeout.ms
- F. increase max.poll.interval.ms
Answer: E,F
Explanation:
session.timeout.ms must be decreased to 3 seconds to allow for a faster rebalance, and the heartbeat thread must be quicker, so we also need to decrease heartbeat.interval.ms
NEW QUESTION # 79
If I want to send binary data through the REST proxy, it needs to be base64 encoded. Which component needs to encode the binary data into base 64?
- A. Zookeeper
- B. The Kafka Broker
- C. The Producer
- D. The REST Proxy
Answer: C
Explanation:
The REST Proxy requires to receive data over REST that is already base64 encoded, hence it is the responsibility of the producer
NEW QUESTION # 80
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=1 can't produce?
- A. 0
- B. 1
- C. 2
- D. 3
Answer: D
Explanation:
min.insync.replicas does not impact producers when acks=1 (only when acks=all)
NEW QUESTION # 81
Where are the ACLs stored in a Kafka cluster by default?
- A. Inside the Zookeeper's data directory
- B. Under Zookeeper node /kafka-acl/
- C. Inside the broker's data directory
- D. In Kafka topic __kafka_acls
Answer: C
Explanation:
ACLs are stored in Zookeeper node /kafka-acls/ by default.
NEW QUESTION # 82
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 hours
- C. 168 ms
- D. 168 minutes
Answer: C
Explanation:
If more than one similar config is specified, the smaller unit size will take precedence.
NEW QUESTION # 83
The Controller is a broker that is... (select two)
- A. elected by Zookeeper ensemble
- B. is responsible for consumer group rebalances
- C. elected by broker majority
- D. is responsible for partition leader election
Answer: A,D
Explanation:
Controller is a broker that in addition to usual broker functions is responsible for partition leader election. The election of that broker happens thanks to Zookeeper and at any time only one broker can be a controller
NEW QUESTION # 84
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?
- A. 0
- B. 1
- C. 2
- D. 3
- E. 4
Answer: A
Explanation:
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 # 85
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 # 86
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?
- A. Create a custom partitioner
- B. Define a Kafka Broker routing rule
- C. 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
- D. Add metadata to the producer record
Answer: A
Explanation:
A Custom Partitioner allows you to easily customise how the partition number gets computed from a source message.
NEW QUESTION # 87
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());
}
}
What kind of delivery guarantee this consumer offers?
- A. At-most-once
- B. At-least-once
- C. Exactly-once
Answer: A
Explanation:
Here offset is committed before processing the message. If consumer crashes before processing the message, message will be lost when it comes back up.
NEW QUESTION # 88
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
- A. json data
- B. "test_binary" will receive
- C. base64 encoded data, it will need to decode it
- D. avro data
- E. binary data
Answer: E
Explanation:
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.
NEW QUESTION # 89
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