Questions2.md

Question 11

In the Kafka producer API, what is the purpose of the acks configuration parameter?

• A. To specify the number of acknowledgments the producer requires the leader to have received before considering a request complete
• B. To specify the number of replicas that must acknowledge a write for the write to be considered successful
• C. To specify the number of times the producer will retry a failed request
• D. To specify the number of partitions a topic must have for the producer to send messages to it

Answer: A

Explanation: The acks parameter in the Kafka producer API controls the durability of writes from the producer to the Kafka broker. It specifies the number of acknowledgments the producer requires the leader to have received before considering a request complete.

The valid values for acks are:

• 0: The producer will not wait for any acknowledgment from the server at all. The message will be immediately added to the socket buffer and considered sent.
• 1: The leader will write the record to its local log and respond without awaiting full acknowledgement from all followers.
• all: The leader will wait for the full set of in-sync replicas to acknowledge the record before responding to the producer.

The higher the acks value, the stronger the durability guarantee, but also the slower the write performance.

• B is incorrect because acks is about acknowledgments from the leader, not the number of replicas that must acknowledge.
• C is incorrect because acks is not related to the number of retries.
• D is incorrect because acks is not related to the number of partitions in a topic.

Question 12

How does the min.insync.replicas broker configuration interact with the acks producer configuration?

• A. They are completely independent settings
• B. acks must always be set to all for min.insync.replicas to have any effect
• C. min.insync.replicas is only relevant if acks is set to 1 or all
• D. If acks is set to all, writes will only succeed if the number of in-sync replicas is at least min.insync.replicas

Answer: D

Explanation: The min.insync.replicas broker configuration and the acks producer configuration work together to control the durability of writes in Kafka:

• min.insync.replicas specifies the minimum number of replicas that must acknowledge a write for the write to be considered successful.
• acks specifies the number of acknowledgments the producer requires the leader to have received before considering a request complete.

When acks is set to all, the leader will wait for the full set of in-sync replicas to acknowledge the write before responding to the producer. However, if the number of in-sync replicas is less than min.insync.replicas, the write will fail even if acks=all.

This ensures that a minimum number of replicas have the data, providing a stronger durability guarantee.

• A is incorrect because the settings are not independent, they interact.
• B is incorrect because min.insync.replicas can have an effect even if acks is not all.
• C is incorrect because min.insync.replicas is not directly relevant to acks=1, only to acks=all.

Question 13

What happens if a Kafka producer sends a message with acks=all to a topic partition with 3 replicas, but only 2 replicas are currently in-sync?

• A. The write will succeed and the producer will receive an acknowledgment
• B. The write will succeed but the producer will not receive an acknowledgment
• C. The write will be queued until the third replica comes back in-sync
• D. The write will fail and the producer will receive an error

Answer: D

Explanation: In this scenario, the producer is configured with acks=all, meaning it requires an acknowledgment from all in-sync replicas before considering a write successful. The topic partition has 3 replicas configured, but only 2 are currently in-sync.

When the producer sends a message to this partition, the leader will attempt to replicate the write to all in-sync replicas. However, since the number of in-sync replicas (2) is less than the total number of replicas (3), the leader will not receive acknowledgments from all replicas.

• A. a result, the write will fail and the producer will receive an error (a NotEnoughReplicasException). The message will not be written to the Kafka log.

This behavior protects against data loss by ensuring that writes are only considered successful if they have been durably written to the full set of in-sync replicas.

• A and B are incorrect because the write will not succeed in this scenario.
• C is incorrect because the write will not be queued, it will fail immediately.

Question 14

Can a producer configured with acks=all and retries=Integer.MAX_VALUE ever experience data loss?

• A. No, this configuration guarantees no data loss under all circumstances
• B. Yes, if the total number of replicas for a partition drops below min.insync.replicas
• C. Yes, if unclean.leader.election.enable=true and all in-sync replicas fail
• D. Yes, if the producer crashes after the broker acknowledges the write but before the producer records the acknowledgment

Answer: B, C, D

Explanation: While a producer configured with acks=all and retries=Integer.MAX_VALUE provides a very strong durability guarantee, there are still some edge cases where data loss can occur:

1. If the number of in-sync replicas for a partition drops below min.insync.replicas, the broker will start rejecting writes to that partition. If this happens, and the producer exhausts its retries, the write will fail and the data will be lost. This can happen if replicas crash or become unavailable.

2. If unclean.leader.election.enable=true and all in-sync replicas for a partition fail, an out-of-sync replica can be elected as the new leader. This replica may be missing some of the latest messages, causing data loss.

3. If the producer crashes (or loses connectivity) after the broker acknowledges a write but before the producer records the acknowledgment, the producer will treat the write as failed and may retry it. This can lead to duplicate messages, but from the perspective of the crashed producer instance, the original message is lost.

So while acks=all and retries=Integer.MAX_VALUE provide a very strong durability guarantee, they cannot completely eliminate the possibility of data loss in all failure scenarios.

• A is incorrect because, as explained above, there are edge cases where data loss can still occur even with this configuration.

Question 15

You want to produce messages to a Kafka topic using a Java client. Which of the following is NOT a required configuration for the producer?

• A. bootstrap.servers
• B. key.serializer
• C. value.serializer
• D. partitioner.class

Answer: D

Explanation: When creating a Kafka producer in Java, there are several required configurations:

• bootstrap.servers: This specifies the list of broker addresses the producer should contact to bootstrap initial cluster metadata. It is required for the producer to know where to send requests.
• key.serializer: This specifies the serializer class for keys. It is required because Kafka needs to know how to serialize the key object to bytes.
• value.serializer: This specifies the serializer class for values. It is required because Kafka needs to know how to serialize the value object to bytes.

The partitioner.class configuration is optional. It specifies the partitioner class that should be used to determine which partition to send each message to. If not specified, the default partitioner will be used, which is sufficient for most use cases.

Question 16

Which of the following is true about the relationship between producers and consumers in Kafka?

• A. Producers and consumers must use the same serialization format
• B. Producers and consumers must be written in the same programming language
• C. Producers and consumers are decoupled by the Kafka topic
• D. Producers must know about the consumers to send messages to them

Answer: C

Explanation: One of the key design principles of Kafka is the decoupling of producers and consumers:

• Producers write messages to a Kafka topic, without needing to know about the consumers that will read those messages.
• Consumers read messages from a Kafka topic, without needing to know about the producers that wrote those messages.

This decoupling is achieved through the Kafka topic, which acts as a buffer between producers and consumers. Producers write to the topic and consumers read from the topic, but they don't need to be aware of each other.

This decoupling allows for several benefits:

• Producers and consumers can be scaled independently, as they are not directly dependent on each other.
• Producers and consumers can be written in different programming languages and use different serialization formats, as long as they agree on the data format of the messages in the topic.
• New consumers can be added to read from the topic without affecting the producers.

Therefore, statements A, B, and D are incorrect. Producers and consumers do not need to use the same serialization format, be written in the same language, or know about each other. They are decoupled by the Kafka topic.

Question 17

What happens if a Kafka producer sends a message to a topic partition and does not receive an acknowledgment from the broker?

• A. The producer will consider the message as successfully sent
• B. The producer will wait indefinitely for the acknowledgment
• C. The producer will retry sending the message based on its retry configuration
• D. The producer will immediately send the next message in the queue

Answer: C

Explanation: When a Kafka producer sends a message, it waits for an acknowledgment from the broker before considering the send operation complete. If the acknowledgment is not received within the configured request.timeout.ms, the send operation is considered failed.

In case of a failure, the producer's behavior depends on its retries configuration:

• If retries is set to 0, the producer will not retry the send operation. It will consider the message as failed and will either throw an exception or invoke the callback function with an error, depending on how the send operation was invoked.
• If retries is set to a value greater than 0, the producer will retry sending the message up to the specified number of times. It will wait for retry.backoff.ms before each retry attempt.

If the producer exhausts all retry attempts without receiving an acknowledgment, it will consider the message as failed.

Therefore, statement C is correct. The producer will retry sending the message based on its retry configuration.

• A is incorrect because the producer will not consider the message as successfully sent until it receives an acknowledgment.
• B is incorrect because the producer will not wait indefinitely. It will timeout after request.timeout.ms.
• D is incorrect because the producer will not immediately send the next message. It will attempt to retry the failed message first.

Question 18

What is the purpose of the acks parameter in Kafka producer configuration?

• A. To specify the number of partitions the producer should write to
• B. To specify the number of replicas that must acknowledge a write for it to be considered successful
• C. To specify the number of times the producer should retry sending a message
• D. To specify the maximum size of a batch of messages

Answer: B

Explanation: The acks parameter in Kafka producer configuration is used to specify the number of acknowledgments the producer requires the leader to have received before considering a write request complete. It controls the durability and reliability of message writes.

The acks parameter can have the following values:

• 0: The producer does not wait for any acknowledgment from the server. The message is considered sent as soon as it is written to the network. This provides the lowest latency but also the lowest durability guarantee.

• 1: The leader writes the message to its local log and responds without waiting for acknowledgment from the followers. This provides better durability than acks=0 but still has the risk of message loss if the leader fails before the followers have replicated the message.

• all or -1: The leader waits for the full set of in-sync replicas (ISR) to acknowledge the message before responding to the producer. This provides the highest level of durability and ensures that the message is committed by all in-sync replicas before the write is considered successful.

• B. setting acks to all, you can ensure that a write is considered successful only when it has been acknowledged by all in-sync replicas, providing the highest level of durability. However, this also introduces additional latency as the producer waits for all acknowledgments.

The choice of the acks value depends on the specific requirements of your application regarding durability, latency, and throughput.

Question 19

What happens if the acks parameter is set to all and the minimum in-sync replicas (min.insync.replicas) setting is not satisfied?

• A. The producer will retry sending the message until the min.insync.replicas requirement is met
• B. The producer will write the message successfully, ignoring the min.insync.replicas setting
• C. The producer will receive an error indicating that the min.insync.replicas requirement is not met
• D. The producer will wait indefinitely until the min.insync.replicas requirement is met

Answer: C

Explanation: When the acks parameter is set to all in the Kafka producer configuration, the producer requires acknowledgment from all in-sync replicas (ISR) before considering a write successful. The min.insync.replicas setting specifies the minimum number of replicas that must be in-sync for a partition to accept writes.

If the min.insync.replicas requirement is not met, meaning there are fewer in-sync replicas than the specified minimum, the producer will receive an error indicating that the write cannot be completed successfully. The error typically indicates that the number of in-sync replicas is insufficient.

In this case, the producer will not retry sending the message automatically. It is the responsibility of the application to handle the error and decide on the appropriate action, such as retrying the write, logging an error, or taking alternative measures.

Setting min.insync.replicas to a value greater than 1 in combination with acks=all ensures that writes are only considered successful if a minimum number of replicas have acknowledged the message. This provides additional durability guarantees by preventing writes from succeeding if the specified number of replicas is not available.

It's important to note that setting min.insync.replicas too high can impact the availability of the system, as writes will fail if the required number of replicas is not available. It's recommended to find a balance between durability and availability based on the specific requirements of your application.

Question 20

What is the relationship between the acks parameter and the request.required.acks parameter in Kafka?

• A. They are the same parameter, just with different names
• B. acks is used in the producer configuration, while request.required.acks is used in the consumer configuration
• C. acks is used in the new producer API, while request.required.acks is used in the old producer API
• D. They are completely unrelated parameters

Answer: C

Explanation: The acks parameter and the request.required.acks parameter in Kafka are related to the acknowledgment mechanism for producer writes, but they are used in different versions of the producer API.

In the new producer API (introduced in Kafka 0.8.2 and later), the acks parameter is used to specify the number of acknowledgments the producer requires the leader to have received before considering a write request complete. It is part of the producer configuration.

On the other hand, request.required.acks is a parameter used in the old producer API (prior to Kafka 0.8.2). It serves a similar purpose as acks but with a slightly different syntax and behavior.

The request.required.acks parameter can have the following values:

• 0: The producer does not wait for any acknowledgment from the server.
• 1: The leader writes the message to its local log and responds without waiting for acknowledgment from the followers.
• -1: The leader waits for the full set of in-sync replicas (ISR) to acknowledge the message before responding to the producer.

In the old producer API, request.required.acks is used in the producer configuration to specify the acknowledgment level.

It's important to note that the old producer API and the request.required.acks parameter are deprecated and have been replaced by the new producer API and the acks parameter. It is recommended to use the new producer API and the acks parameter in Kafka versions 0.8.2 and later.

When migrating from the old producer API to the new producer API, you should replace request.required.acks with the equivalent acks configuration.