The entire pipeline executes in a single call stack. No promises are created, no microtask queue scheduling occurs, and no GC pressure from short-lived async machinery. For CPU-bound workloads like parsing, compression, or transformation of in-memory data, this can be significantly faster than the equivalent Web streams code — which would force async boundaries even when every component is synchronous.
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The API recognizes that synchronous data sources are both necessary and common. The application should not be forced to always accept the performance cost of asynchronous scheduling simply because that's the only option provided. At the same time, mixing sync and async processing can be dangerous. Synchronous paths should always be an option and should always be explicit.。业内人士推荐heLLoword翻译官方下载作为进阶阅读
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That said, it's important to recognize that locking in itself is not bad. It does, in fact, serve an important purpose to ensure that applications properly and orderly consume or produce data. The key challenge is with the original manual implementation of it using APIs like getReader() and releaseLock(). With the arrival of automatic lock and reader management with async iterables, dealing with locks from the users point of view became a lot easier.，详情可参考搜狗输入法下载