Testing stream topologies in Kafka - Time & Space Complexity

Time Complexity: Testing stream topologies

O(n)

Understanding Time Complexity

When testing stream topologies, we want to know how the time to run tests changes as the data size grows.

We ask: How does the test execution time grow when we add more input records?

Scenario Under Consideration

Analyze the time complexity of the following Kafka Streams test code snippet.

TopologyTestDriver testDriver = new TopologyTestDriver(topology, props);
TestInputTopic<String, String> inputTopic = testDriver.createInputTopic("input", stringSerializer, stringSerializer);
TestOutputTopic<String, String> outputTopic = testDriver.createOutputTopic("output", stringDeserializer, stringDeserializer);

for (int i = 0; i < n; i++) {
    inputTopic.pipeInput("key" + i, "value" + i);
}

List<KeyValue<String, String>> results = outputTopic.readKeyValuesToList();

This code feeds n records into the input topic and reads all output records after processing.

Identify Repeating Operations

Look for repeated actions that take time.

• Primary operation: Loop feeding n input records one by one.
• How many times: Exactly n times, once per input record.
• Secondary operation: Reading all output records after processing, which depends on n.

How Execution Grows With Input

As you add more input records, the test runs longer because each record is processed.

Input Size (n)	Approx. Operations
10	About 10 input operations + reading outputs
100	About 100 input operations + reading outputs
1000	About 1000 input operations + reading outputs

Pattern observation: The time grows roughly in direct proportion to the number of input records.

Final Time Complexity

Time Complexity: O(n)

This means the test time increases linearly as you add more input records.

Common Mistake

[X] Wrong: "The test time stays the same no matter how many records I add."

[OK] Correct: Each input record triggers processing, so more records mean more work and longer test time.

Interview Connect

Understanding how test time grows helps you write efficient tests and reason about system behavior under load.

Self-Check

"What if we batch input records instead of sending them one by one? How would the time complexity change?"

Practice

1. What is the main purpose of using TopologyTestDriver in Kafka Streams testing?

easy

A. To simulate the stream processing logic without a real Kafka cluster

B. To deploy the Kafka Streams application to production

C. To monitor Kafka cluster health

D. To create new Kafka topics automatically

Solution

1. Step 1: Understand the role of TopologyTestDriver

   It runs the Kafka Streams topology in memory for testing purposes.

2. Step 2: Compare with other options

   Options A, B, and C relate to topic creation, deployment, or monitoring, which are not testing functions.

3. Final Answer:

   To simulate the stream processing logic without a real Kafka cluster -> Option A

4. Quick Check:

   TopologyTestDriver = simulate streams [OK]

Hint: Remember: TopologyTestDriver runs streams in memory for tests [OK]

Common Mistakes:

• Confusing testing with deployment
• Thinking it manages Kafka topics
• Assuming it monitors Kafka cluster health

2. Which of the following is the correct way to create a TopologyTestDriver instance in Java?

easy

A. TopologyTestDriver.create(topology, properties);

B. new TopologyTestDriver(topology, properties);

C. TopologyTestDriver.start(topology, properties);

D. new TopologyTestDriver(properties, topology);

Solution

1. Step 1: Recall the constructor signature

   The constructor takes the topology first, then the properties.

2. Step 2: Check each option

   new TopologyTestDriver(topology, properties); matches the correct constructor call. Options B and C use non-existent static methods. new TopologyTestDriver(properties, topology); reverses the argument order.

3. Final Answer:

   new TopologyTestDriver(topology, properties); -> Option B

4. Quick Check:

   Constructor = topology, properties [OK]

Hint: Constructor order: topology first, then properties [OK]

Common Mistakes:

• Using static methods instead of constructor
• Swapping argument order
• Calling non-existent start or create methods

3. Given the following code snippet using TopologyTestDriver:

var driver = new TopologyTestDriver(topology, props);
var inputTopic = driver.createInputTopic("input", Serdes.String().serializer(), Serdes.String().serializer());
var outputTopic = driver.createOutputTopic("output", Serdes.String().deserializer(), Serdes.String().deserializer());

inputTopic.pipeInput("key1", "value1");
var result = outputTopic.readKeyValue();
System.out.println(result.key + ":" + result.value);

What will be printed if the topology simply forwards input to output unchanged?

medium

A. key1:value1

B. null:null

C. value1:key1

D. Exception thrown

Solution

1. Step 1: Understand the topology behavior

   The topology forwards input key-value pairs unchanged to the output topic.

2. Step 2: Trace the test driver code

   Input "key1" and "value1" is piped in; outputTopic reads the same key-value pair.

3. Final Answer:

   key1:value1 -> Option A

4. Quick Check:

   Forwarded key-value = key1:value1 [OK]

Hint: If topology forwards, output matches input exactly [OK]

Common Mistakes:

• Mixing key and value order
• Expecting null output without input
• Assuming exceptions without errors

4. Identify the error in this test code snippet using TopologyTestDriver:

var driver = new TopologyTestDriver(topology, props);
var inputTopic = driver.createInputTopic("input", Serdes.String().deserializer(), Serdes.String().serializer());
inputTopic.pipeInput("key", "value");

medium

A. pipeInput method is called with wrong argument types

B. TopologyTestDriver constructor arguments are reversed

C. Input topic serializers and deserializers are swapped

D. Missing call to driver.close()

Solution

1. Step 1: Check serializer/deserializer usage

   Input topic requires serializers for key and value, not deserializers.

2. Step 2: Identify the swapped serializers

   Code uses deserializer for key and serializer for value, which is incorrect.

3. Final Answer:

   Input topic serializers and deserializers are swapped -> Option C

4. Quick Check:

   Input topic needs serializers [OK]

Hint: Input topics need serializers, output topics need deserializers [OK]

Common Mistakes:

• Using deserializers for input topic
• Ignoring proper resource closing
• Confusing constructor argument order

5. You want to test a Kafka Streams topology that filters out records with null values before forwarding. Which approach correctly verifies this behavior using TopologyTestDriver?

hard

A. Send records with null values and expect an exception from TopologyTestDriver

B. Send only null values to input topic and expect output topic to have the same null values

C. Send records with null values and check that output topic is empty without reading

D. Send records with null and non-null values to input topic, then assert output topic only has non-null values

Solution

1. Step 1: Prepare test input with null and non-null values

   This tests the filter logic by including both cases.

2. Step 2: Verify output topic contents

   Assert that only records with non-null values appear in the output topic.

3. Final Answer:

   Send records with null and non-null values to input topic, then assert output topic only has non-null values -> Option D

4. Quick Check:

   Filter test = input mixed, output filtered [OK]

Hint: Test filters by sending mixed input, check filtered output [OK]

Common Mistakes:

• Expecting null values to appear in output
• Not reading output topic to verify results
• Assuming exceptions occur on null values