Apache Kafka - Real-time Stream Processing (Master Class) - Caution with States

The video tutorial addresses a problem in Kafka stream processing where invoices from different stores are partitioned based on store ID, leading to issues with local state stores. The solution involves ensuring all invoices for a customer are sent to the same partition, either by changing the message key to customer ID or using a custom partitioner. The tutorial explains how to implement these solutions using Kafka's API, emphasizing the importance of repartitioning and its impact on performance.

What is the main issue with using store ID as a key in Kafka streams?

• Invoices are not sent to any partition.

• Invoices from the same store always land in different partitions.

• Invoices from the same store always land in the same partition.

• Invoices from different stores land in the same partition.

Why do loyalty points not accumulate correctly across different stores?

• Because the invoices are sent to the wrong topic.

• Because the customer ID is not used.

• Because the state stores are local to each task.

• Because the invoices are not processed.

How can you ensure all invoices for a customer land in the same partition?

• By using store ID as the message key.

• By using a custom partitioner.

• By using customer ID as the message key.

• By sending invoices to different topics.

What is the purpose of the 'through' method in Kafka streams?

• To merge multiple streams into one.

• To split a stream into multiple partitions.

• To delete the current stream.

• To write the current stream to a given topic and repartition it.

What is the role of a custom partitioner in Kafka streams?

• To change the message value.

• To change the message key.

• To determine the partition based on a custom logic.

• To delete messages from a partition.

What should be considered when creating an intermediate topic for repartitioning?

• The type of messages.

• The number of partitions and retention settings.

• The size of the messages.

• The speed of the network.

Why is repartitioning considered an expensive activity?

• It requires additional hardware.

• It duplicates the messages.

• It impacts the performance of the streaming application.

• It increases the size of the messages.