Memory management is crucial for JavaScript applications, particularly as they scale. Whether building web apps or complex server-side applications...
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Whole of react casual reducer with big array modification is looks memory leak way when write this way?:
When every modification is create a whole new array.
My real life experience is: this is not effect the memory so much. Maybe use a bit higher amount, but not cause leak. We are real time working on big data in this way.
Hey Peter, great question! You’ve touched on an important point about memory management in React. While creating a new array for each modification follows React's immutable state principle, it’s true that this may seem memory-heavy. However, React's virtual DOM efficiently handles these changes. If memory optimization is crucial, consider using techniques like linked lists for extensive modifications or incorporating memoization to reduce re-rendering overhead. Libraries like
immer
can also help manage immutability more efficiently. BTW, good call! 🖤😉Great tips! I have a question, though.
In number three, you've said that
Map
andSet
are more efficient in comparison with objects and arrays regarding large amounts of data. Can you please tell me more about this?Thank you!
Thank you for your thoughtful question!!! When it comes to large data sets,
Map
andSet
indeed have significant advantages over objects and arrays.Map
is optimized for key-value pair management and provides constant-time complexity (O(1)
) for operations like lookup and insertion, which are more efficient than an object’sO(n)
in worst-case scenarios due to potential key collisions. Similarly,Set
is ideal for managing unique values with optimized operations, preventing duplicate entries and ensuring faster access and modifications. This efficiency makes them powerful tools for handling larger data effectively😊😊😊Now I get it. Thank you so much!
Dear Shafayet Hossain,
I hope this message finds you well. My name is Liu, and I am a blogger in China. I recently read your excellent article titled "JavaScript Memory Management and Optimization Techniques for Large-Scale Applications" on dev.to, and I believe it would be incredibly helpful for the JavaScript community here.
I would like to ask for your permission to translate your article into Chinese and publish it on the Juejin platform, a popular technical blog site in China. I will, of course, fully credit you as the original author and include a link to the original article on dev.to.
Please let me know if you are open to this request and if you have any specific conditions or guidelines for the translation and publication.
Thank you very much for your time and consideration. I look forward to your response.
Best regards,
Liu
I hope you’ve already proceeded with the translation! Apologies for the delayed response. I appreciate your interest in sharing my article with the JavaScript community in China. I’m happy to grant permission for the translation, provided that you fully credit me as the original author and include a link back to the original article on DEV. Thank you for your effort to make this knowledge more accessible
Of course, thank you.
You're absolutely right, memory management is a crucial aspect of JavaScript development. Understanding how memory allocation and garbage collection work in JavaScript can help you optimize your code and ensure that it runs smoothly.
When working with large datasets or complex applications, it's important to be mindful of how you're allocating memory and to avoid creating unnecessary references that can lead to memory leaks. Techniques such as using smaller data structures, avoiding global variables, and explicitly releasing references can all help to improve memory management in JavaScript.
Thanks ChatGPT 😂
Thanks Dhanush, I agree with you😊😊😊
Good work @shafayeat. You are right and thank God that somebody else - besides me - states the obvious: "JS does not automagically solve all of RAM issues and the GC can only do so much". This is true pretty much for any programming language that I use.
People just don't get it and that's why we have so many heavy and faulty applications...
The programming paradigms and your suggestion to use the profilers is on the spot and to the right direction.
I have built large infrastructures and open source enterprise solutions with all that in mind such as:
Thanks for chiming in, George! Couldn't agree more, it's surprising how often developers take memory management for granted, thinking the garbage collector will handle everything without fail😅😅 Your emphasis on real, conscious handling of resources and using profilers hits the nail on the head. We need more discussions like this to keep reminding developers that robust, efficient applications come from thoughtful coding, not just automated processes. Glad to have voices like yours contributing to this perspective!!!🖤🖤🖤
Hello! Thanks for this great article!
I didn't quite understand the example in "4. Pooling Resources". Wouldn't createPooledObject() always return new LargeObject(), since we never actually populate anything into the pool, and it's length is always zero?
Hey Mihail! You’re absolutely right, and I appreciate you catching that oversight. In this example,
createPooledObject()
would indeed return a newLargeObject()
every time since the pool isn’t actually being filled with existing objects. Ideally, we’d populate the pool first, then retrieve objects from it rather than creating them each time. I’ll clarify that to prevent any confusion. Thanks again for the keen eye!🖤🖤🖤Thanks for the clarification! I also did a little research on that concept because everything you wrote looked interesting - thanks for listing it here. It all starts with knowing what options you have. The details come later 😃
7 is misleading - neither have a memory leak and the "unoptimized" version is actually more memory efficient. But the optimized version is more computationally efficient because it has a memory-safe implementation of memoization, which by definition trades memory for speed. But in most cases, you would probably use a normal map for memoization.
Hey Mike! I appreciate your sharp observation—it’s spot-on that memory usage can often be balanced against computational efficiency when using memoization. The “unoptimized” example can indeed show better memory retention in straightforward cases, while the “optimized” one aims for speed through controlled caching. Using a standard map can be optimal in many scenarios, though the choice depends on the specific performance needs and data scale. Your insights add valuable perspective, and I’m glad you shared them! 😊
thank you so much for sharing in this important lesson.
Thank you Nozibul🖤I always count you in...😊
Welcome...
This is good
Thank you, Aadarsh😊😊😊
Great article on memory management for JavaScript developers. Memory management can be challenging, but it's essential to address it! 👍👍
Thank You🖤🖤🖤
I just created an account then i saw your post!!Your post literally made my day!😊
I'm so happy to hear that😊
❤❤❤
Really Great And Interesting Article
Glad you found that helpful😊🖤
Its Nice
Thank you Mamata...🖤
"Thank you so much for sharing this invaluable lesson. It truly means a lot!"
Thank you Barkot😊