Скачать или смотреть Understanding Concurrency, Parallelism, and Sequential Execution in Go

Discover the differences between `concurrency`, `parallelism`, and `sequential` execution in Go programming. Learn how these concepts apply to real-world scenarios for efficient coding and performance.
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Understanding Concurrency, Parallelism, and Sequential Execution in Go

As you dive into Go programming, you might find yourself grappling with some complex concepts, especially when it comes to executing tasks. Three terms that are often mixed up are concurrency, parallelism, and sequential execution. Understanding how these concepts differ can significantly improve your coding efficiency and project outcomes. In this guide, we'll break down these terms, provide helpful examples, and clarify any misunderstandings you may have regarding their usage.

The Challenge: Unpacking the Terms

In your learning journey, you encountered different methods of executing a process that scraps data from multiple URLs. Here's a quick recap of your process:

Scrapping a slice of 5 URLs, with each URL taking 2 seconds to complete.

The results you had:

Sequentially: 10 seconds (one after the other)

Parallel: Less than 10 seconds (simultaneously using multiple processors)

Concurrently: Less than 10 seconds (without requiring multiple processors)

Your confusion stemmed from wanting to understand how concurrency can be faster than a sequential approach while not using multiple threads or processors.

An Analogy to Understand

To clarify these concepts, let's use an analogy involving frying eggs:

Sequential Approach: Imagine you fry one egg at a time. You crack it onto a griddle, wait for it to cook completely, and then take it off before starting on the next egg. This method will take you a total of 10 seconds for 5 eggs.

Parallel Approach: Now, picture hiring 5 cooks, each assigned to fry one egg simultaneously. This method can be completed in less than 10 seconds, as all 5 eggs are cooked at the same time.

Concurrent Approach: In this method, you are cooking all 5 eggs yourself, but instead of waiting for each egg to finish before starting the next, you quickly crack each egg onto the pan. You take each egg off the griddle as soon as it is ready. This allows you to manage your time more effectively and still cook all eggs faster than the sequential method without needing additional cooks.

Why Concurrency Can Be Efficient

The beauty of the concurrent approach lies in the way tasks are managed. Here are some key points to understand:

Resource Management: Just like cooking eggs, the Go runtime is designed to optimize task handling. While waiting for a network response, it reallocates the processor to tackle other tasks. This reduces idle time and improves performance.

Resource Contention: The goal of concurrency is to handle tasks efficiently despite limited resources (CPU, memory, network, etc.). It's not just about the number of processors, but also about effectively utilizing other resources.

Real-Life Application: In your original example, while waiting for one URL to respond, you could be preparing for the next request or executing some other necessary tasks. This overlap leads to time savings, even if no additional threads are involved.

Conclusion

By understanding the distinctions between concurrency, parallelism, and sequential execution, you can write more efficient Go programs. Remember that concurrency focuses on effectively managing resources, while parallelism revolves around performing tasks simultaneously. With these insights, you're better equipped to tackle more complex programming challenges in Go.

Happy coding!