Fair dispatch with prefetch in RabbitMQ - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to set the prefetch count to 1 for fair dispatch.

RabbitMQ

channel.basic_qos(prefetch_count=[1])

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

A1

B0

C5

D10

Attempts:

3 left

💡 Hint

Common Mistakes

Setting prefetch_count to 0 disables prefetch and can cause unfair dispatch.

Using a high prefetch_count can overload a single worker.

Setting prefetch_count to 1 tells RabbitMQ to send only one message at a time to a worker, enabling fair dispatch.

2fill in blank

medium

Complete the code to acknowledge a message manually after processing.

RabbitMQ

channel.basic_ack(delivery_tag=[1])

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

Amethod.delivery_tag

Bmessage

Cchannel

Dprefetch_count

Attempts:

3 left

💡 Hint

Common Mistakes

Trying to acknowledge using the message body instead of delivery tag.

Using channel or prefetch_count as delivery tag.

The delivery_tag from the method frame is used to acknowledge the message manually.

3fill in blank

hard

Fix the error in the consumer callback to enable fair dispatch with manual acknowledgments.

RabbitMQ

def callback(ch, method, properties, body):
    print(f"Received {body}")
    # Process message
    ch.basic_ack(delivery_tag=[1])

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

Abody

Bproperties

Cmethod.delivery_tag

Dch

Attempts:

3 left

💡 Hint

Common Mistakes

Using the message body or channel object as delivery tag.

Not acknowledging messages causing them to be requeued.

Manual acknowledgment requires the delivery tag from the method parameter, which is method.delivery_tag.

4fill in blank

hard

Fill both blanks to set up a channel with fair dispatch and manual acknowledgments.

RabbitMQ

channel.basic_qos(prefetch_count=[1])
channel.basic_consume(queue='task_queue', on_message_callback=callback, auto_ack=[2])

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

A1

BTrue

CFalse

D5

Attempts:

3 left

💡 Hint

Common Mistakes

Setting auto_ack to True disables manual acknowledgment.

Using a prefetch count higher than 1 reduces fairness.

Setting prefetch_count to 1 enables fair dispatch. Setting auto_ack to False requires manual acknowledgment.

5fill in blank

hard

Fill all three blanks to complete the consumer setup for fair dispatch with manual ack and a callback function.

RabbitMQ

def callback(ch, method, properties, body):
    print(f"Received {body}")
    # Process message
    ch.basic_ack(delivery_tag=[1])

channel.basic_qos(prefetch_count=[2])
channel.basic_consume(queue='task_queue', on_message_callback=callback, auto_ack=[3])

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

Amethod.delivery_tag

B1

CFalse

DTrue

Attempts:

3 left

💡 Hint

Common Mistakes

Using auto_ack=True disables manual ack.

Not setting prefetch count to 1 reduces fairness.

The callback acknowledges messages using method.delivery_tag. Prefetch count is set to 1 for fair dispatch. auto_ack is False to require manual acknowledgment.

Practice

1. What is the main purpose of setting prefetch_count=1 in RabbitMQ fair dispatch?

easy

A. To ensure each worker receives only one task at a time

B. To allow workers to receive unlimited tasks simultaneously

C. To disable message acknowledgments

D. To increase the queue size automatically

Solution

1. Step 1: Understand prefetch_count meaning

   Prefetch_count controls how many messages a worker can receive before acknowledging previous ones.

2. Step 2: Effect of setting prefetch_count=1

   Setting it to 1 means the worker gets one task at a time, preventing overload and balancing workload.

3. Final Answer:

   To ensure each worker receives only one task at a time -> Option A

4. Quick Check:

   prefetch_count=1 means one task per worker [OK]

Hint: Prefetch 1 means one task per worker at a time [OK]

Common Mistakes:

• Thinking prefetch_count controls queue size
• Believing it disables acknowledgments
• Assuming workers get unlimited tasks

2. Which of the following is the correct way to set prefetch count to 1 using RabbitMQ's channel in Python?

easy

A. channel.set_prefetch(1)

B. channel.qos(prefetch=1)

C. channel.prefetch(1)

D. channel.basic_qos(prefetch_count=1)

Solution

1. Step 1: Recall RabbitMQ Python API method

   The method to set prefetch count is basic_qos with prefetch_count argument.

2. Step 2: Match correct syntax

   Only channel.basic_qos(prefetch_count=1) matches the official API syntax.

3. Final Answer:

   channel.basic_qos(prefetch_count=1) -> Option D

4. Quick Check:

   basic_qos with prefetch_count sets prefetch [OK]

Hint: Use basic_qos(prefetch_count=1) to set prefetch in Python [OK]

Common Mistakes:

• Using incorrect method names like set_prefetch
• Passing wrong argument names
• Confusing prefetch with qos

3. Given the following Python code snippet using RabbitMQ, what will be the output behavior when multiple workers consume from the same queue with prefetch_count=1?

channel.basic_qos(prefetch_count=1)
channel.basic_consume(queue='task_queue', on_message_callback=callback, auto_ack=False)
channel.start_consuming()

medium

A. Messages are processed only by the first worker

B. All workers receive all messages simultaneously

C. Each worker processes one message at a time, distributing tasks evenly

D. Workers process messages without waiting for acknowledgments

Solution

1. Step 1: Understand prefetch_count=1 effect

   With prefetch_count=1, each worker gets one message and must ack before next.

2. Step 2: Effect on multiple workers

   This causes RabbitMQ to distribute messages fairly, so tasks are balanced among workers.

3. Final Answer:

   Each worker processes one message at a time, distributing tasks evenly -> Option C

4. Quick Check:

   prefetch_count=1 balances tasks fairly [OK]

Hint: Prefetch 1 means tasks spread evenly, one per worker [OK]

Common Mistakes:

• Thinking all workers get all messages
• Assuming one worker gets all tasks
• Ignoring manual acknowledgments

4. You set prefetch_count=1 but notice one worker is still overloaded while others are idle. What is the most likely cause?

medium

A. The worker is not sending message acknowledgments properly

B. Prefetch count is set too high

C. The queue is empty

D. Multiple workers have the same consumer tag

Solution

1. Step 1: Analyze prefetch_count=1 behavior

   Prefetch_count=1 limits unacknowledged messages to one per worker.

2. Step 2: Identify cause of overload

   If a worker does not ack messages, RabbitMQ won't send new ones, causing that worker to hold tasks and appear overloaded.

3. Final Answer:

   The worker is not sending message acknowledgments properly -> Option A

4. Quick Check:

   Missing ack blocks new messages [OK]

Hint: Check if worker sends acknowledgments to avoid overload [OK]

Common Mistakes:

• Assuming prefetch count is too high
• Ignoring message acknowledgments
• Confusing consumer tags with load balancing

5. You want to optimize a RabbitMQ system where some workers are slower. How should you configure prefetch to ensure fair dispatch and prevent slow workers from blocking others?

hard

A. Set prefetch_count to a high number to maximize throughput

B. Set prefetch_count=1 so each worker gets one task at a time

C. Disable acknowledgments to speed up processing

D. Use multiple queues instead of prefetch settings

Solution

1. Step 1: Understand slow worker impact

   Slow workers holding many tasks block others if prefetch is high.

2. Step 2: Apply prefetch_count=1 for fair dispatch

   Setting prefetch_count=1 ensures each worker processes one task at a time, preventing blocking.

3. Step 3: Evaluate other options

   High prefetch or disabling acks causes imbalance; multiple queues add complexity.

4. Final Answer:

   Set prefetch_count=1 so each worker gets one task at a time -> Option B

5. Quick Check:

   Prefetch 1 prevents slow worker blocking [OK]

Hint: Use prefetch_count=1 to balance slow and fast workers [OK]

Common Mistakes:

• Setting prefetch too high causing imbalance
• Disabling acknowledgments causing message loss
• Ignoring prefetch and using multiple queues unnecessarily