Error handling in clients in Kafka - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to catch exceptions when sending a message.

Kafka

try {
    producer.send(record).get();
} catch ([1] e) {
    e.printStackTrace();
}

Drag options to blanks, or click blank then click option'

AInterruptedException

BExecutionException

CTimeoutException

DIOException

Attempts:

3 left

💡 Hint

Common Mistakes

Using IOException which is unrelated to Kafka send failures.

Catching TimeoutException instead of ExecutionException.

The ExecutionException is thrown when the send operation fails asynchronously.

2fill in blank

medium

Complete the code to handle interrupted exceptions during send.

Kafka

try {
    producer.send(record).get();
} catch (ExecutionException e) {
    e.printStackTrace();
} catch ([1] e) {
    Thread.currentThread().interrupt();
}

Drag options to blanks, or click blank then click option'

AIOException

BTimeoutException

CKafkaException

DInterruptedException

Attempts:

3 left

💡 Hint

Common Mistakes

Catching TimeoutException instead of InterruptedException.

Not restoring the thread interrupt status.

The InterruptedException must be caught to handle thread interruption properly.

3fill in blank

hard

Fix the error in the catch block to handle Kafka exceptions correctly.

Kafka

try {
    producer.send(record).get();
} catch ([1] e) {
    System.err.println("Kafka error: " + e.getMessage());
}

Drag options to blanks, or click blank then click option'

AExecutionException

BKafkaException

CInterruptedException

DIOException

Attempts:

3 left

💡 Hint

Common Mistakes

Catching KafkaException which is not directly thrown by get().

Catching IOException which is unrelated.

The ExecutionException wraps Kafka client errors thrown during the send operation.

4fill in blank

hard

Fill both blanks to create a retry loop that handles send failures.

Kafka

int retries = 0;
boolean sent = false;
while (!sent && retries < 3) {
    try {
        producer.send(record).get();
        sent = true;
    } catch ([1] e) {
        retries++;
        System.out.println("Retry " + retries);
        Thread.sleep([2]);
    }
}

Drag options to blanks, or click blank then click option'

AExecutionException

B1000

C500

DInterruptedException

Attempts:

3 left

💡 Hint

Common Mistakes

Using InterruptedException which handles interruptions rather than send failures.

Using too long or zero sleep time.

Use ExecutionException to catch send failures and 500 milliseconds as sleep time between retries.

5fill in blank

hard

Fill all three blanks to log error details and rethrow the exception.

Kafka

try {
    producer.send(record).get();
} catch ([1] e) {
    logger.error("Send failed: {}", [2]);
    throw new [3](e);
}

Drag options to blanks, or click blank then click option'

AExecutionException

Be.getMessage()

CRuntimeException

DInterruptedException

Attempts:

3 left

💡 Hint

Common Mistakes

Logging the exception object directly without calling getMessage().

Throwing InterruptedException which is unrelated here.

Catch ExecutionException, log the error message with e.getMessage(), and rethrow as a RuntimeException.

Practice

1. What is the main purpose of error handling in Kafka clients?

easy

A. To increase the speed of message processing

B. To keep the client stable and responsive during failures

C. To reduce the size of messages sent

D. To automatically create Kafka topics

Solution

1. Step 1: Understand error handling role

   Error handling helps the client manage unexpected problems without crashing.

2. Step 2: Identify the main goal in Kafka clients

   Keeping the client stable and responsive ensures smooth operation even if errors occur.

3. Final Answer:

   To keep the client stable and responsive during failures -> Option B

4. Quick Check:

   Error handling = stability and responsiveness [OK]

Hint: Error handling keeps your client stable and responsive [OK]

Common Mistakes:

• Thinking error handling speeds up processing
• Confusing error handling with message size control
• Assuming error handling creates topics automatically

2. Which syntax correctly wraps a Kafka producer send call to catch exceptions in Java?

easy

A. producer.send(record).catch(e => console.log(e));

B. if (producer.send(record)) { } else { handleError(); }

C. try { producer.send(record); } catch (Exception e) { e.printStackTrace(); }

D. try catch producer.send(record);

Solution

1. Step 1: Identify correct Java try-catch syntax

   Java requires try { ... } catch (Exception e) { ... } to handle exceptions.

2. Step 2: Match syntax with Kafka producer send call

   try { producer.send(record); } catch (Exception e) { e.printStackTrace(); } correctly wraps the send call in try-catch block.

3. Final Answer:

   try { producer.send(record); } catch (Exception e) { e.printStackTrace(); } -> Option C

4. Quick Check:

   Java try-catch syntax = try { producer.send(record); } catch (Exception e) { e.printStackTrace(); } [OK]

Hint: Use try-catch blocks in Java to catch Kafka errors [OK]

Common Mistakes:

• Using if-else instead of try-catch for exceptions
• Using JavaScript syntax in Java code
• Missing braces in try-catch block

3. Given this Java Kafka consumer code snippet, what will be printed if a network error occurs during poll?

try {
  ConsumerRecords records = consumer.poll(Duration.ofMillis(100));
  for (var record : records) {
    System.out.println(record.value());
  }
} catch (WakeupException e) {
  System.out.println("Consumer interrupted");
} catch (Exception e) {
  System.out.println("Error during poll");
}

medium

A. Error during poll

B. Consumer interrupted

C. No output

D. Exception stack trace

Solution

1. Step 1: Identify exception types caught

   WakeupException prints "Consumer interrupted"; all other exceptions print "Error during poll".

2. Step 2: Determine exception for network error

   Network errors throw general exceptions, not WakeupException.

3. Final Answer:

   Error during poll -> Option A

4. Quick Check:

   Network error triggers general Exception = Error during poll [OK]

Hint: General exceptions print "Error during poll" [OK]

Common Mistakes:

• Confusing WakeupException with network errors
• Expecting no output on error
• Assuming stack trace prints automatically

4. Identify the error in this Kafka producer error handling code snippet:

try {
  producer.send(record);
} catch (KafkaException e) {
  System.out.println("Error sending message");
}
producer.close();

medium

A. producer.send() does not throw exceptions

B. Catch block should catch Exception, not KafkaException

C. Missing return statement after catch

D. producer.close() should be inside finally block

Solution

1. Step 1: Check resource cleanup

   producer.close() must run regardless of exceptions to free resources.

2. Step 2: Use finally block for cleanup

   Placing close() inside finally ensures it always executes.

3. Final Answer:

   producer.close() should be inside finally block -> Option D

4. Quick Check:

   Always close resources in finally block [OK]

Hint: Put cleanup code in finally block to always run [OK]

Common Mistakes:

• Closing producer only on success
• Catching too broad or wrong exceptions
• Assuming send() never throws exceptions

5. You want to build a Kafka consumer that retries polling up to 3 times on recoverable errors, then logs and stops. Which approach correctly implements this error handling?

hard

A. Use a loop with try-catch around poll; on exception increment retry count; break after 3 retries; finally close consumer

B. Call consumer.poll() once; if exception, immediately close consumer without retry

C. Wrap poll in try-catch but ignore exceptions and continue polling forever

D. Use multiple nested try-catch blocks without retry logic

Solution

1. Step 1: Understand retry logic requirements

   Retry polling up to 3 times on recoverable errors, then stop and log.

2. Step 2: Identify correct control flow

   Loop with try-catch, count retries, break after 3 attempts, and close consumer in finally block is correct.

3. Final Answer:

   Use a loop with try-catch around poll; on exception increment retry count; break after 3 retries; finally close consumer -> Option A

4. Quick Check:

   Retry with loop and try-catch = Use a loop with try-catch around poll; on exception increment retry count; break after 3 retries; finally close consumer [OK]

Hint: Use loop with try-catch and retry count for controlled retries [OK]

Common Mistakes:

• Not retrying on recoverable errors
• Ignoring exceptions and continuing endlessly
• Closing consumer too early without retries