Partitioner behavior in Kafka - Mini Project: Build & Apply

Partitioner Behavior in Kafka

📖 Scenario: You are working with Apache Kafka, a system that helps send messages between different parts of an application. Messages are sent to topics, which are divided into partitions. How messages are assigned to partitions depends on the partitioner.Understanding partitioner behavior helps ensure messages are distributed correctly for processing.

🎯 Goal: Build a simple Kafka producer that sends messages to a topic using a custom partitioner. You will create the data to send, configure the partitioner, implement the partitioning logic, and then print which partition each message goes to.

📋 What You'll Learn

Create a list of messages with exact values

Create a configuration variable for the number of partitions

Implement a custom partitioner function that assigns partitions based on message key length

Print the message and its assigned partition

💡 Why This Matters

🌍 Real World

Kafka is used in many applications to handle streams of data. Understanding how partitioners work helps distribute data evenly and maintain order where needed.

💼 Career

Kafka developers and data engineers often customize partitioners to optimize data flow and processing in real-time systems.

1

Create the list of messages

Create a list called messages with these exact string values: 'apple', 'banana', 'cherry', 'date', 'elderberry'.

Kafka

# Create the list of messages
# Your code here

Hint

Use square brackets [] to create a list and separate items with commas.

2

Set the number of partitions

Create a variable called num_partitions and set it to 3.

Kafka

messages = ['apple', 'banana', 'cherry', 'date', 'elderberry']
# Set the number of partitions
# Your code here

Hint

Just assign the number 3 to the variable num_partitions.

3

Implement the custom partitioner function

Define a function called custom_partitioner that takes a message string and returns the partition number by calculating len(message) % num_partitions.

Kafka

messages = ['apple', 'banana', 'cherry', 'date', 'elderberry']
num_partitions = 3
# Define the custom_partitioner function
# Your code here

Hint

Use the len() function to get the length of the message string.

4

Print each message with its assigned partition

Use a for loop with variable msg to iterate over messages. Inside the loop, print the message and its partition using custom_partitioner(msg) in this exact format: Message: {msg}, Partition: {partition}.

Kafka

messages = ['apple', 'banana', 'cherry', 'date', 'elderberry']
num_partitions = 3

def custom_partitioner(message):
    return len(message) % num_partitions

# Print each message with its partition
# Your code here

Hint

Use an f-string to format the print output exactly as shown.

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