Partitioner behavior in Kafka - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to specify the partition key for a Kafka message.

Kafka

producer.send(topic, key=[1], value="message")

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

A"user123"

B123

CNone

Dvalue

Attempts:

3 left

💡 Hint

Common Mistakes

Using an integer as key without serialization

Passing None as key when a key is expected

The partition key is usually a string or bytes that Kafka uses to decide the partition. Here, a string key "user123" is correct.

2fill in blank

medium

Complete the code to create a custom partitioner class in Kafka.

Kafka

class CustomPartitioner:
    def partition(self, key, partitions, [1]):
        return hash(key) % len(partitions)

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

Aconfig

Bvalue

Ctopic

Dmetadata

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong parameter names

Ignoring the metadata parameter

The partition method usually receives key, partitions, and metadata. Metadata provides extra info about the message.

3fill in blank

hard

Fix the error in the partitioner code to correctly compute the partition index.

Kafka

def partition(key, partitions):
    index = hash(key) [1] len(partitions)
    return index

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

A+

B%

C-

D//

Attempts:

3 left

💡 Hint

Common Mistakes

Using division or subtraction instead of modulo

Returning a value outside partition range

The modulo operator % is used to ensure the partition index is within the range of available partitions.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that maps partitions to message counts greater than 10.

Kafka

partition_counts = {p: counts[p] [1] p [2] counts if counts[p] > 10}

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

Afor

Bin

Cif

Delse

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'if' or 'else' in place of 'for' or 'in'

Incorrect comprehension syntax

The syntax for dictionary comprehension is: {key: value for key in iterable if condition}. Here, 'for' and 'in' are needed.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps uppercase keys to values greater than 5.

Kafka

filtered = [1]: [2] for [3] in data if data[[3]] > 5

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

Ak.upper()

Bdata[k]

Ck

Dv

Attempts:

3 left

💡 Hint

Common Mistakes

Using values instead of keys in iteration

Not transforming keys to uppercase

Incorrect comprehension syntax

The comprehension maps uppercase keys (k.upper()) to their values (data[k]) for keys k in data where value > 5.

Practice

1.

What does a Kafka partitioner do?

partitioner decides:

easy

A. Which partition a message is sent to

B. How to compress messages

C. The message format

D. The topic name

Solution

1. Step 1: Understand the role of a partitioner

   A partitioner decides the partition inside a Kafka topic where a message will be stored.

2. Step 2: Match the function to the options

   Only Which partition a message is sent to correctly describes this role.

3. Final Answer:

   Which partition a message is sent to -> Option A

4. Quick Check:

   Partitioner = decides message partition [OK]

Hint: Partitioner chooses partition for messages [OK]

Common Mistakes:

• Confusing partitioner with compression
• Thinking partitioner sets topic name
• Assuming partitioner changes message format

2.

Which of the following is the correct way to specify a default partitioner class in Kafka producer configuration?

props.put("partitioner.class", ?);

easy

A. "org.apache.kafka.clients.producer.KeyPartitioner"

B. "org.apache.kafka.clients.producer.RoundRobinPartitioner"

C. "org.apache.kafka.clients.producer.CustomPartitioner"

D. "org.apache.kafka.clients.producer.internals.DefaultPartitioner"

Solution

1. Step 1: Recall default partitioner class name

   The default partitioner class in Kafka is DefaultPartitioner located in org.apache.kafka.clients.producer.internals.

2. Step 2: Match the correct class name

   "org.apache.kafka.clients.producer.internals.DefaultPartitioner" matches the default partitioner class name exactly.

3. Final Answer:

   "org.apache.kafka.clients.producer.internals.DefaultPartitioner" -> Option D

4. Quick Check:

   Default partitioner class = DefaultPartitioner [OK]

Hint: Default partitioner class is DefaultPartitioner [OK]

Common Mistakes:

• Using non-existent class names
• Confusing round-robin with default partitioner
• Misspelling package or class names

3.

Given a Kafka topic with 3 partitions and a producer sending messages with keys "key1", "key2", and "key1" again, which partitions will the messages go to if the default partitioner is used?

medium

A. [0, 0, 1]

B. [1, 2, 0]

C. [0, 1, 0]

D. [2, 1, 0]

Solution

1. Step 1: Understand key-based partitioning

   Messages with the same key go to the same partition. Different keys may go to different partitions.

2. Step 2: Assign partitions for keys

   Assuming hash(key) mod 3, "key1" maps to partition 0, "key2" maps to partition 1. So messages go to partitions [0, 1, 0].

3. Final Answer:

   [0, 1, 0] -> Option C

4. Quick Check:

   Same key = same partition [OK]

Hint: Same key always same partition [OK]

Common Mistakes:

• Assuming keys distribute randomly
• Assigning different partitions to same key
• Ignoring modulo partition count

4.

Consider this code snippet for sending messages without keys:

for i in range(4):
    producer.send("topic", value=f"msg{i}")

What is the likely issue if all messages end up in the same partition?

medium

A. Messages have keys that force same partition

B. Topic has only one partition

C. The producer is not configured to use round-robin partitioning

D. Producer is using a custom partitioner ignoring keys

Solution

1. Step 1: Analyze message keys and partition count

   Messages have no keys, so default partitioner uses round-robin if multiple partitions exist.

2. Step 2: Check topic partition count

   If all messages go to the same partition, likely the topic has only one partition.

3. Final Answer:

   Topic has only one partition -> Option B

4. Quick Check:

   Single partition topic = all messages same partition [OK]

Hint: Single partition topic sends all messages there [OK]

Common Mistakes:

• Assuming round-robin works with one partition
• Thinking keys are present when they are not
• Ignoring topic partition count

5.

You want to ensure messages with the same user ID always go to the same partition, but messages without user ID keys should be evenly distributed. Which partitioner behavior should you rely on?

hard

A. Default partitioner: keyed messages to same partition, unkeyed round-robin

B. Custom partitioner that ignores keys and uses random partition

C. Round-robin partitioner for all messages

D. Partitioner that sends all messages to partition 0

Solution

1. Step 1: Understand keyed message behavior

   Default partitioner sends messages with the same key to the same partition.

2. Step 2: Understand unkeyed message behavior

   Messages without keys are distributed evenly using round-robin by default partitioner.

3. Step 3: Match behavior to requirement

   Default partitioner: keyed messages to same partition, unkeyed round-robin matches the requirement exactly.

4. Final Answer:

   Default partitioner: keyed messages to same partition, unkeyed round-robin -> Option A

5. Quick Check:

   Default partitioner fits keyed + unkeyed needs [OK]

Hint: Default partitioner handles keyed and unkeyed well [OK]

Common Mistakes:

• Choosing custom partitioner ignoring keys
• Using round-robin for keyed messages
• Sending all messages to one partition