Node has single main thread to handle all synchronous code execution from your scripts, and in the case of a Node API, all client requests. When a blocking request comes in, it actually delegates the I/O tasks to a worker thread present in the thread pool. So we can conclude that Node is **not** totally end-to-end single-threaded.
Node has single “main” thread to handle all synchronous code execution from your scripts, and in the case of a Node API, all client requests. When a blocking request comes in, it actually delegates the I/O tasks to a worker thread present in the thread pool. So we can conclude that Node is not totally end-to-end single-threaded.
Note: Worker threads are not the main thread.
Okay, that’s fine. But if we say this about NodeJS:
In Node.js everything runs in parallel, except your code. What this means is that all I/O code that you write in Node.js is non-blocking, while (conversely) all non-I/O code that you write in Node.js is blocking.
If the above statement is true (which it is), then if a very very heavy CPU task comes as a client request, what happens? You may think you can’t do anything but wonder if you could have used another language.
But no my dear friend, we can even delegate this CPU intensive task to a worker a thread.
How do we do that?
I will explain this with a proper example here
As you can see I have created a function called heavyTask Which runs a for loop for 5000000000000 times. The main thread will be busy for a long time and it will deny serving any other client request.
How do we delegate this CPU task to one of the worker threads present in thread pool.
workerpool offers an easy way to create a pool of workers for both dynamically offloading computations as well as managing a pool of dedicated workers. It basically implements a thread pool pattern. There is a pool of workers to execute tasks. New tasks are put in a queue. A worker executes one task at a time, and once finished, picks a new task from the queue.
In the above example there is a function
heavyTask, which is offloaded dynamically to a worker to be executed for a given set of arguments.
This is how you can handle a CPU intensive task by offloading that work to a worker thread.
Github link reference: https://github.com/yogain123/Workers-Pool
Thanks for Reading
Happing Learning :)
Originally published by Yogendra Saxena at levelup.gitconnected.com
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