This is fundamentally different from Web streams' pipeThrough(), which starts actively pumping data from the source to the transform as soon as you set up the pipe. Pull semantics mean you control when processing happens, and stopping iteration stops processing.
What if you create a truly unique routing profile that's wildly different from the common ones for which shortcuts were pre-calculated? The system is smart. If it detects that too many shortcuts (~50, for example) need on-the-fly recalculation and deviate significantly, it might determine that falling back to the original, comprehensive A* algorithm for the entire route would actually be faster than doing many small, heavily modified A* calculations.
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This Tweet is currently unavailable. It might be loading or has been removed.，这一点在搜狗输入法下载中也有详细论述
Екатерина Улитина (Редактор отдела «Забота о себе»)。关于这个话题，同城约会提供了深入分析
The problem gets worse in pipelines. When you chain multiple transforms — say, parse, transform, then serialize — each TransformStream has its own internal readable and writable buffers. If implementers follow the spec strictly, data cascades through these buffers in a push-oriented fashion: the source pushes to transform A, which pushes to transform B, which pushes to transform C, each accumulating data in intermediate buffers before the final consumer has even started pulling. With three transforms, you can have six internal buffers filling up simultaneously.