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| Section | Objectives |
|---|---|
| Kafka Fundamentals | - Kafka architecture and core concepts
|
| Kafka Ecosystem and Confluent Platform | - Schema Registry
|
| Kafka Streams and Processing | - Kafka Streams API
|
| Kafka Producers and Consumers | - Consumer API
|
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NEW QUESTION # 19
You are working on a Kafka cluster with three nodes. You create a topic named orders with:
* replication.factor = 3
* min.insync.replicas = 2
* acks = allWhat exception will be generated if two brokers are down due to network delay?
Answer: A
Explanation:
With acks=all and min.insync.replicas=2, Kafka requiresat least two in-sync replicasto acknowledge a write.
If onlyone broker is alive, the condition fails, andNotEnoughReplicasExceptionis thrown by the producer.
FromKafka Producer Exception Docs:
"NotEnoughReplicasException is thrown when the number of in-sync replicas is insufficient to satisfy acks=all with min.insync.replicas."
* NetworkException is generic and not raised here.
* NotCoordinatorException is related to consumer group coordination.
* NotLeaderForPartitionException is unrelated unless accessing an unassigned leader.
Reference:Kafka Producer Error Handling
NEW QUESTION # 20
(You want to enrich the content of a topic by joining it with key records from a second topic.
The two topics have a different number of partitions.
Which two solutions can you use?
Select two.)
Answer: C,D
Explanation:
The Apache Kafka Streams documentation defines a co-partitioning requirement for KStream-KTable and KStream-KStream joins. Both input topics must have the same number of partitions and the same key partitioning strategy.
One valid solution is to use a GlobalKTable (Option A). A GlobalKTable is fully replicated to every Kafka Streams instance, removing the co-partitioning requirement. This approach is recommended when the reference data is relatively small and changes infrequently.
Another valid solution is to repartition one topic so that both topics have the same number of partitions (Option B). Kafka Streams provides repartition topics specifically for this purpose, allowing proper KStream- KTable joins.
Option C does not resolve the partition mismatch, as increasing instances does not change partitioning. Option D is incorrect because Kafka Streams does not automatically repartition both topics for joins; repartitioning must be explicitly configured.
Therefore, the correct and officially supported solutions are using a GlobalKTable and explicitly repartitioning one topic.
NEW QUESTION # 21
Select all that applies (select THREE)
Answer: B,E,F
Explanation:
acks is a producer setting min.insync.replicas is a topic or broker setting and is only effective when acks=all
NEW QUESTION # 22
You are creating a Kafka Streams application to process retail data.
Match the input data streams with the appropriate Kafka Streams object.
Answer:
Explanation:
Explanation:
Table # Product, Customers
Stream # Orders_Placed, Shipment_Of_Orders
Tables represent slowly changing, reference data - e.g., customer profiles, product info.
Streams represent real-time event data - e.g., orders placed, shipments processed.
From Kafka Streams Documentation:
"Use KTable for reference datasets, and KStream for event-based processing such as orders or logs." Reference: Kafka Streams API Concepts
NEW QUESTION # 23
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?
Answer: B
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 # 24
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