Concurrent and Parallel Programming in Python - Improving All Workers and Adding Monitoring

Concurrent and Parallel Programming in Python - Improving All Workers and Adding Monitoring

Assessment

Interactive Video

•

Information Technology (IT), Architecture

•

University

•

Practice Problem

•

Hard

Created by

Wayground Content

FREE Resource

The video tutorial focuses on optimizing a YAML pipeline executor by improving worker communication and threading. It addresses issues with sending 'done' signals and introduces a method to track worker and queue status. The tutorial demonstrates implementing monitoring and sending done signals only after all workers have finished. It includes testing and debugging the implementation, with a discussion on final adjustments and queue monitoring, particularly on Linux systems.

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10 questions

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1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the main issue with sending 'done' signals prematurely in the pipeline?

It duplicates the data in the queue.

It increases the processing speed.

It leads to incomplete data processing.

It causes the pipeline to restart.

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What happens if 'done' is sent before all workers finish?

The pipeline will execute faster.

The queue will be cleared.

All workers will restart.

Some data may remain unprocessed.

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

How does moving the 'done' signal to the main worker improve the pipeline?

It increases the number of output queues.

It reduces the number of workers needed.

It ensures all workers finish before sending 'done'.

It allows for faster execution.

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the role of the main worker in the optimized pipeline?

To reduce the number of queues.

To increase the number of threads.

To monitor progress and send 'done' signals.

To execute all tasks.

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the purpose of tracking queue consumers and downstream queues?

To increase the number of workers.

To ensure each queue is specific to one worker.

To reduce the number of queues.

To duplicate the data in the queues.

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What assumption is made about each queue in the pipeline?

Each queue is shared among all workers.

Each queue must be duplicated.

Each queue is specific to one worker.

Each queue can be used by multiple workers.

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What method is used to check if a worker thread is still running?

isRunning()

isAlive()

checkStatus()

isFinished()

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