Filter and map operations in Kafka - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Kafka Streams: What is the output of this filter and map operation?

Consider a Kafka Streams application that processes a stream of integers. It filters out even numbers and then maps each remaining number to its square. What will be the output for the input stream [1, 2, 3, 4, 5]?

Kafka

KStream<Integer, Integer> input = builder.stream("input-topic");
KStream<Integer, Integer> processed = input
    .filter((key, value) -> value % 2 != 0)
    .mapValues(value -> value * value);
processed.to("output-topic");

A [1, 4, 9, 16, 25]

B [1, 9, 25]

C [2, 4]

D [1, 3, 5]

💡 Hint

Remember that filter removes even numbers, and mapValues squares the remaining numbers.

The filter keeps only odd numbers: 1, 3, 5. Then mapValues squares each: 1*1=1, 3*3=9, 5*5=25. So the output is [1, 9, 25].

❓ Predict Output

intermediate

Kafka Streams: Result of chaining filter and map with keys

Given a Kafka Streams pipeline that filters records with keys less than 3 and maps values by adding 10, what is the output for input records with keys and values: (1, 5), (2, 7), (3, 9), (4, 11)?

Kafka

KStream<Integer, Integer> input = builder.stream("input-topic");
KStream<Integer, Integer> result = input
    .filter((key, value) -> key < 3)
    .mapValues(value -> value + 10);
result.to("output-topic");

A [(1, 15), (2, 17)]

B [(3, 19), (4, 21)]

C [(1, 5), (2, 7)]

D [(1, 15), (2, 17), (3, 19), (4, 21)]

💡 Hint

Filter keeps keys less than 3, then values get 10 added.

Only records with keys 1 and 2 pass the filter. Their values 5 and 7 become 15 and 17 after adding 10.

🔧 Debug

advanced

Why does this Kafka Streams filter-map code cause a runtime error?

Examine the following Kafka Streams code snippet. It attempts to filter and map values but causes a runtime NullPointerException. What is the cause?

Kafka

KStream<Integer, String> input = builder.stream("input-topic");
KStream<Integer, String> result = input
    .filter((key, value) -> value.length() > 3)
    .mapValues(value -> value.toUpperCase());
result.to("output-topic");

A The stream is missing a call to selectKey before filter, causing runtime failure.

B The mapValues function is incorrectly used and causes a syntax error.

C The filter predicate should use key instead of value, causing a type error.

D Some values in the stream are null, causing value.length() to throw NullPointerException.

💡 Hint

Think about what happens if value is null when calling value.length().

If any record has a null value, calling value.length() causes a NullPointerException at runtime.

📝 Syntax

advanced

Which Kafka Streams filter-map code snippet is syntactically correct?

Choose the syntactically correct Kafka Streams code that filters values greater than 10 and maps values to their double.

A input.filter((k, v) -> { v > 10 }).mapValues(v -> v * 2);

B input.filter(k, v -> v > 10).mapValues(v -> v * 2);

C input.filter((k, v) -> v > 10).mapValues(v -> v * 2);

D input.filter((k, v) => v > 10).mapValues(v -> v * 2);

💡 Hint

Check the syntax of lambda expressions in Java.

Option C uses correct Java lambda syntax. Option C misses parentheses around parameters. Option C uses JavaScript arrow syntax. Option C uses braces without return statement causing no boolean result.

🚀 Application

expert

How many records are in the output after this Kafka Streams filter and map chain?

A Kafka Streams application reads from a topic with 6 records having values: [5, 12, 7, 20, 3, 15]. It filters values greater than 10 and then maps values to value minus 5. How many records are in the output topic?

Kafka

KStream<Integer, Integer> input = builder.stream("input-topic");
KStream<Integer, Integer> output = input
    .filter((k, v) -> v > 10)
    .mapValues(v -> v - 5);
output.to("output-topic");

A 3

B 4

C 2

D 6

💡 Hint

Count how many values are greater than 10 before mapping.

Values greater than 10 are 12, 20, and 15. So 3 records pass the filter and appear in output.