Mark-Compacts is a garbage collection algorithm used in Node.js to free up memory that is no longer in use. When memory is no longer in use, the garbage collector marks it as available for future use. However, when the heap nears its size limit, the Mark-Compacts algorithm may fail to reclaim enough memory to satisfy the program’s demand, triggering the error.
This error can occur due to various reasons like running a program that requires more memory than what is available, a memory leak in program code, or due to a configuration that sets the memory limit too low.
To fix this error, try to optimize the program code, reduce the memory usage, and/or increase the amount of memory allocated to Node.js using the –max-old-space-size flag. This will allocate more memory to Node.js and reduce the likelihood of memory-related errors like “Mark-Compacts Near Heap Limit Allocation Failed”.
Fortunately, there are several tips and best practices you can follow to help prevent this error from occurring:
- Optimize your code: Inefficient and poorly optimized code can cause your application to use more memory than necessary. Make sure to write clean, optimized code that minimizes unnecessary memory usage.
- Consider using a garbage collector: A garbage collector is a tool that can help manage memory usage by automatically freeing up memory that is no longer needed by your application. This can be especially useful in large-scale applications with complex memory requirements.
How to Increase Heap Memory Limit in Node.js?
1. Use the flag `–max-old-space-size` to set the maximum heap size. For example, to increase the heap memory limit to 2 GB, you can use the following command:
node –max-old-space-size=2048 index.js
2. You can also set the `NODE_OPTIONS` environment variable to specify the maximum heap size. For example, to set the maximum heap size to 2 GB, you can use the following command:
NODE_OPTIONS=”–max-old-space-size=2048″ node index.js
This will pass the `–max-old-space-size` flag to the Node.js runtime whenever you run your application.
Note that increasing the heap memory limit can have an impact on the performance of your application and can lead to slower response times. It is recommended to analyze the memory usage of your application and optimize it before increasing the heap memory limit.
- Minimize global variables: Avoid defining variables in the global scope. Instead, use local variables and declare them using var, let, or const.
- Avoid memory leaks: Be careful when creating closures or circular references, as they can cause memory leaks that gradually consume more and more memory over time.
- Use object pooling: Instead of creating and destroying objects frequently, consider reusing them. Object pooling can help reduce memory allocation and improve performance.
- Limit unnecessary DOM manipulation: DOM manipulation can be expensive in terms of memory usage. Try to minimize the number of times you modify the DOM, and use methods that are optimized for performance.
- Optimize recursion: Recursive functions can quickly consume a lot of memory if not optimized properly. Consider using iteration instead of recursion, or optimizing your code to minimize the amount of stack space used.
Fortunately, there are several techniques that can be used to debug these errors:
- Identify the source of the problem: Inspect the code and identify which part is consuming excessive memory. Memory profiling tools such as Chrome DevTools and Node.js built-in profiler can help analyze the heap usage of the application.
- Optimize memory usage: Once the problem area is identified, optimize the memory usage of the code. This might involve changing your data structures, reducing the number of unnecessary objects, or streamlining your application’s codebase.
One best practice is to monitor heap memory usage regularly. This can be done using tools like Chrome DevTools that provide real-time data on memory usage. By keeping an eye on memory usage, you can identify potential memory leaks or inefficient memory allocation patterns.
Another recommendation is to optimize your code for efficient memory management. This can be done by reducing the number of unnecessary objects and variables created in your code. Using object pools can also help reduce the number of allocations and deallocations in memory.
In addition, it is recommended to use a garbage collector that is suited for your specific application. Different garbage collectors have their own strengths and weaknesses, so choosing the right one for your application can improve memory usage and performance.
Finally, minimizing the size of dependencies and libraries used in your application can also help reduce memory usage. It’s important to only include necessary dependencies and optimize their usage for efficient memory allocation.