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Kafkadevops~10 mins

Stream topology in Kafka - Interactive Code Practice

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Practice - 5 Tasks
Answer the questions below
1fill in blank
easy

Complete the code to create a stream builder instance.

Kafka
StreamsBuilder builder = new [1]();
Drag options to blanks, or click blank then click option'
AStreamsBuilder
BKafkaStreams
CStreamConfig
DTopology
Attempts:
3 left
💡 Hint
Common Mistakes
Using KafkaStreams instead of StreamsBuilder.
Using Topology directly without builder.
2fill in blank
medium

Complete the code to define a source stream from a topic named 'input-topic'.

Kafka
KStream<String, String> source = builder.stream([1]);
Drag options to blanks, or click blank then click option'
A"output-topic"
B"input-topic"
Cinput-topic
Dsource-topic
Attempts:
3 left
💡 Hint
Common Mistakes
Not using quotes around the topic name.
Using the wrong topic name.
3fill in blank
hard

Fix the error in the code to send the processed stream to an output topic.

Kafka
processedStream.to([1]);
Drag options to blanks, or click blank then click option'
A"output-topic"
BoutputTopic
Coutput-topic
DprocessedStream
Attempts:
3 left
💡 Hint
Common Mistakes
Passing a variable name without quotes.
Passing the stream variable itself.
4fill in blank
hard

Fill both blanks to build and start the Kafka Streams application.

Kafka
Topology topology = builder.[1]();
KafkaStreams streams = new KafkaStreams(topology, [2]);
streams.start();
Drag options to blanks, or click blank then click option'
Abuild
Bstart
Cprops
Dconfig
Attempts:
3 left
💡 Hint
Common Mistakes
Using start() instead of build() on builder.
Passing config instead of props.
5fill in blank
hard

Fill all three blanks to create a stream, filter messages with value length > 5, and send to 'filtered-topic'.

Kafka
KStream<String, String> stream = builder.stream([1]);
KStream<String, String> filtered = stream.filter((key, value) -> value.[2]() > [3]);
filtered.to("filtered-topic");
Drag options to blanks, or click blank then click option'
A"input-topic"
Blength
C5
Dsize
Attempts:
3 left
💡 Hint
Common Mistakes
Using size() instead of length() for strings.
Not quoting the topic name.

Practice

(1/5)
1. What does a Kafka Streams topology represent?
easy
A. The configuration settings for Kafka brokers
B. The flow and processing steps of data in a Kafka Streams application
C. The list of Kafka topics available in the cluster
D. The schema of messages in a Kafka topic

Solution

  1. Step 1: Understand the role of topology in Kafka Streams

    A topology defines how data flows and is processed in a Kafka Streams app.
  2. Step 2: Differentiate topology from other Kafka concepts

    It is not about broker configs, topic lists, or message schemas, but about processing steps.
  3. Final Answer:

    The flow and processing steps of data in a Kafka Streams application -> Option B
  4. Quick Check:

    Topology = Data flow and processing [OK]
Hint: Topology means data flow and processing steps [OK]
Common Mistakes:
  • Confusing topology with Kafka broker settings
  • Thinking topology lists topics
  • Assuming topology defines message schema
2. Which code snippet correctly builds a Kafka Streams topology?
easy
A. StreamsBuilder builder = new StreamsBuilder(); builder.run();
B. StreamsBuilder builder = new StreamsBuilder(); builder.start();
C. StreamsBuilder builder = new StreamsBuilder(); builder.create();
D. StreamsBuilder builder = new StreamsBuilder(); builder.build();

Solution

  1. Step 1: Recall the correct method to build topology

    The method to finalize and get the topology is build().
  2. Step 2: Check each option's method

    Only StreamsBuilder builder = new StreamsBuilder(); builder.build(); uses build(), others use invalid methods.
  3. Final Answer:

    StreamsBuilder builder = new StreamsBuilder(); builder.build(); -> Option D
  4. Quick Check:

    Use build() to create topology [OK]
Hint: Use build() method on StreamsBuilder to create topology [OK]
Common Mistakes:
  • Using start(), create(), or run() instead of build()
  • Confusing topology building with starting the stream
3. Given the code snippet:
StreamsBuilder builder = new StreamsBuilder();
builder.stream("input-topic").mapValues(value -> value.toUpperCase()).to("output-topic");
Topology topology = builder.build();
System.out.println(topology.describe());

What will the printed topology description include?
medium
A. A sink node for 'input-topic' and a source node for 'output-topic'
B. Only a source node for 'input-topic' without any processing
C. A source node for 'input-topic', a processor node for mapValues, and a sink node for 'output-topic'
D. An error because mapValues is not allowed in topology

Solution

  1. Step 1: Analyze the stream processing steps

    The code reads from 'input-topic', applies mapValues to uppercase, then writes to 'output-topic'.
  2. Step 2: Understand topology description output

    The description shows source nodes (input), processor nodes (mapValues), and sink nodes (output).
  3. Final Answer:

    A source node for 'input-topic', a processor node for mapValues, and a sink node for 'output-topic' -> Option C
  4. Quick Check:

    Topology describe shows source, processor, sink [OK]
Hint: Topology describe shows source, processor, and sink nodes [OK]
Common Mistakes:
  • Thinking mapValues is not part of topology
  • Confusing source and sink nodes
  • Expecting no processor nodes in description
4. Identify the error in this Kafka Streams topology code:
StreamsBuilder builder = new StreamsBuilder();
builder.stream("input-topic").filter(value -> value.length() > 5);
Topology topology = builder.build();
System.out.println(topology.describe());
medium
A. The filtered stream is not sent to any sink topic, so no output node is created
B. The filter method is invalid and causes a syntax error
C. StreamsBuilder cannot build topology without a source topic
D. Calling build() before defining streams causes runtime error

Solution

  1. Step 1: Check the stream processing chain

    The code filters the stream but does not write the result to any output topic.
  2. Step 2: Understand topology implications

    Without a sink node, the topology has no output, which is usually an error or incomplete.
  3. Final Answer:

    The filtered stream is not sent to any sink topic, so no output node is created -> Option A
  4. Quick Check:

    Missing sink node causes incomplete topology [OK]
Hint: Always send processed stream to sink topic [OK]
Common Mistakes:
  • Assuming filter causes syntax error
  • Thinking build() requires no streams
  • Ignoring missing sink topic after processing
5. You want to create a Kafka Streams topology that reads from two topics, merges their streams, filters messages containing 'error', and writes to an output topic. Which code snippet correctly builds this topology?
hard
A. StreamsBuilder builder = new StreamsBuilder(); KStream stream1 = builder.stream("topic1"); KStream stream2 = builder.stream("topic2"); KStream merged = stream1.merge(stream2); merged.filter((k, v) -> v.contains("error")).to("output-topic"); Topology topology = builder.build();
B. StreamsBuilder builder = new StreamsBuilder(); KStream stream = builder.stream("topic1", "topic2"); stream.filter(v -> v.contains("error")).to("output-topic"); Topology topology = builder.build();
C. StreamsBuilder builder = new StreamsBuilder(); KStream stream1 = builder.stream("topic1"); KStream stream2 = builder.stream("topic2"); KStream merged = stream1.join(stream2, (v1, v2) -> v1 + v2); merged.filter((k, v) -> v.contains("error")).to("output-topic"); Topology topology = builder.build();
D. StreamsBuilder builder = new StreamsBuilder(); builder.stream("topic1").filter(v -> v.contains("error")).to("output-topic"); builder.stream("topic2").filter(v -> v.contains("error")).to("output-topic"); Topology topology = builder.build();

Solution

  1. Step 1: Understand the requirement

    Read from two topics, merge streams, filter messages with 'error', write to output.
  2. Step 2: Evaluate each option

    StreamsBuilder builder = new StreamsBuilder(); KStream stream1 = builder.stream("topic1"); KStream stream2 = builder.stream("topic2"); KStream merged = stream1.merge(stream2); merged.filter((k, v) -> v.contains("error")).to("output-topic"); Topology topology = builder.build(); merges streams correctly, filters, then writes once. StreamsBuilder builder = new StreamsBuilder(); KStream stream = builder.stream("topic1", "topic2"); stream.filter(v -> v.contains("error")).to("output-topic"); Topology topology = builder.build(); incorrectly tries to stream two topics in one call. StreamsBuilder builder = new StreamsBuilder(); KStream stream1 = builder.stream("topic1"); KStream stream2 = builder.stream("topic2"); KStream merged = stream1.join(stream2, (v1, v2) -> v1 + v2); merged.filter((k, v) -> v.contains("error")).to("output-topic"); Topology topology = builder.build(); joins streams (not merge). StreamsBuilder builder = new StreamsBuilder(); builder.stream("topic1").filter(v -> v.contains("error")).to("output-topic"); builder.stream("topic2").filter(v -> v.contains("error")).to("output-topic"); Topology topology = builder.build(); filters separately and writes twice, not merging.
  3. Final Answer:

    Option A correctly merges, filters, and writes to output topic -> Option A
  4. Quick Check:

    Merge streams, filter, then write [OK]
Hint: Merge streams before filtering and writing output [OK]
Common Mistakes:
  • Using join instead of merge for combining streams
  • Trying to stream multiple topics in one call incorrectly
  • Writing filtered streams separately without merging
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10 questions~5 mineasy hard