When Building Promise Chains Recursively in JavaScript, Are Memory Considerations Significant?

Building a Promise Chain Recursively in JavaScript: Memory Considerations

In JavaScript, constructing a promise chain recursively can give rise to both a call stack and a "resolve chain." While it might seem that this would lead to a larger memory spike than either performing recursion or building a promise chain alone, this is not the case.

The resolve chain is essentially a series of promises that are resolved with the innermost one, representing the same result. When the base case of the recursion is met, the innermost promise is resolved with an actual value, and all of the previous promises are resolved with the same value.

Unlike a promise chain built using then(), this resolve chain does not create a "wide" chain of promises. Instead, it builds a "deep" chain, resulting in O(n) memory cost for walking up the resolve chain. After the result is resolved, all but the outermost promise can be garbage collected.

In contrast, a promise chain constructed using a method like reduce would create a memory spike by allocating n promises at once. These promises are then slowly resolved one by one, with the previously resolved promises being garbage collected.

While some might anticipate a memory spike with the recursive resolve chain, its constant space and time complexity make it a viable technique for asynchronous loops with a dynamic condition. In fact, this construct is commonly used in Haskell's IO monad for such loops.

As for memory consumption differences between promise libraries, yes, they can vary. The ES6 specification mandates Promises to inspect the value at every resolve call, which prevents collapsing the chain. This means that using a leaking promise implementation can lead to memory leakage when using asynchronous recursion. In such cases, it may be preferable to use callbacks and the "deferred antipattern" to achieve the desired result.

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