CQRS pattern in Kafka - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to produce a command message to Kafka.

Kafka

producer.send(new ProducerRecord<>("[1]", "CreateOrder", orderData));

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Alogs

Bevents

Cqueries

Dcommands

Attempts:

3 left

💡 Hint

Common Mistakes

Using the events topic instead of commands.

Using queries topic for commands.

The command messages are sent to the commands topic in CQRS.

2fill in blank

medium

Complete the code to consume events from Kafka for updating read models.

Kafka

consumer.subscribe(Collections.singletonList("[1]"));

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Aevents

Blogs

Cqueries

Dcommands

Attempts:

3 left

💡 Hint

Common Mistakes

Subscribing to commands topic instead of events.

Using queries topic for event consumption.

Event consumers listen to the events topic to update read models in CQRS.

3fill in blank

hard

Fix the error in the Kafka consumer group id for event processing.

Kafka

props.put("group.id", "[1]");

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Aevent-processors

Bquery-handlers

Ccommand-processors

Dlog-consumers

Attempts:

3 left

💡 Hint

Common Mistakes

Using command-processors group id for event consumers.

Using query-handlers group id for event consumers.

The consumer group for event processing should be event-processors to separate concerns.

4fill in blank

hard

Fill both blanks to create a Kafka Streams topology that processes commands and produces events.

Kafka

KStream<String, String> commands = builder.stream("[1]");
KStream<String, String> events = commands.mapValues(command -> [2]);
events.to("events");

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Acommands

Bevents

CprocessCommand(command)

DhandleEvent(command)

Attempts:

3 left

💡 Hint

Common Mistakes

Using events as input stream instead of commands.

Using handleEvent instead of processCommand for mapping.

The stream reads from the commands topic and processes commands using processCommand(command) to produce events.

5fill in blank

hard

Fill all three blanks to implement a Kafka Streams processor that filters commands, maps them to events, and writes to the events topic.

Kafka

KStream<String, String> commands = builder.stream("[1]");
KStream<String, String> filtered = commands.filter((key, value) -> value.contains("[2]"));
filtered.mapValues(value -> [3]).to("events");

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Acommands

BCreateOrder

CprocessCommand(value)

Devents

Attempts:

3 left

💡 Hint

Common Mistakes

Filtering on wrong keyword.

Mapping with incorrect function.

The code reads from the commands topic, filters commands containing CreateOrder, processes them with processCommand(value), and writes events.