How to Optimize Memory Usage in Promise.all with High Concurrency?

Resolving the Memory Consumption Issue in Promise.all

In situations where a large number of promises are managed by Promise.all, memory consumption can become a significant concern. This is particularly true when the resolved data of each promise is not required, leading to unnecessary RAM usage.

To resolve this issue, one approach is to limit the number of concurrent requests in flight at any given time. This technique reduces the overall memory footprint by ensuring that no more than a specified number of promises are active simultaneously.

Bluebird's Promise.map() method offers a built-in mechanism to control concurrency by specifying the desired number of in-flight promises. Alternatively, custom coding solutions can be employed to achieve the same result.

Another optimization technique is to replace the resolved data with a placeholder to make it eligible for garbage collection earlier. For example, setting the resolved value to a simple number allows the original data to be released, freeing up RAM.

Finally, an effective implementation that limits in-flight requests to a specified maximum can be achieved through the mapConcurrent function. This function iterates over an array of items, executing a specified function for each item, but ensures that no more than the specified concurrency limit is exceeded at any time.

Additional Considerations:

• Experiment with different concurrency values to determine the optimal settings for both memory usage and performance.
• For requests that target the same host, limiting concurrency to around 5-10 is often appropriate.
• Requests targeting different hosts may allow for higher concurrency values.
• Continuously monitoring memory usage is crucial to detect any potential issues and adjust concurrency limits accordingly.

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