How to Optimize Promise.all Memory Consumption?

Promise.all Memory Consumption Optimization

In situations where numerous promises are encountered, such as in the scenario described, excessive memory consumption can occur due to the accumulation of unresolved promises and their associated data.

To mitigate this issue, it's essential to avoid maintaining large numbers of promises simultaneously. Instead, consider limiting the concurrency of active promises to a manageable level. By running a limited number of operations concurrently, you reduce the memory footprint associated with the promises and their resolved data.

Experimentation is recommended to determine the optimal concurrency level for your specific use case. For example, in scenarios with rate limits or high-latency requests, a lower concurrency may be preferable to avoid overwhelming the system.

Additionally, if the resolved data is not essential, you can replace it with a simple value once it has been received. This allows the original data to be garbage-collected more efficiently, further reducing memory consumption.

Here are examples of coding techniques that support limiting the number of concurrent promises:

• Bluebird's Promise.map() method provides a concurrency option that allows you to control the number of promises executed simultaneously.
• Iterating through an array with a loop and starting subsequent requests only when previous ones are completed.
• Utilizing external libraries like "request-promise-native" or "axios," which can handle rate-limiting and concurrency management.

By implementing these strategies, you can effectively manage the memory consumption associated with Promise.all and prevent excessive resource utilization.

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