Camilo Reyes shows explores the Node.js Event Loop, showing how it deals with the problem of multiple threads and managing context switch. The event loop is a single-threaded, non-blocking, and asynchronously concurrent loop.
Camilo Reyes shows explores the Node.js Event Loop, showing how it deals with the problem of multiple threads and managing context switch.
Asynchrony in any programming language is hard. Concepts like concurrency, parallelism, and deadlocks make even the most seasoned engineers shiver. Code that executes asynchronously is unpredictable and difficult to trace when there are bugs. The problem is inescapable because modern computing has multiple cores. There’s a thermal limit in each single core of the CPU, and nothing is getting any faster. This puts pressure on the developer to write efficient code that takes advantage of the hardware.
The event loop is a single-threaded, non-blocking, and asynchronously concurrent loop. For those without a computer science degree, imagine a web request that does a database lookup. A single thread can only do one thing at a time. Instead of waiting on the database to respond, it continues to pick up other tasks in the queue. In the event loop, the main loop unwinds the call stack and doesn’t wait on callbacks. Because the loop doesn’t block, it’s free to work on more than one web request at a time. Multiple requests can get queued at the same time, which makes it concurrent. The loop doesn’t wait for everything from one request to complete, but picks up callbacks as they come without blocking.
The loop itself is semi-infinite, meaning if the call stack or the callback queue are empty it can exit the loop. Think of the call stack as synchronous code that unwinds, like
console.log, before the loop polls for more work. Node uses libuv under the covers to poll the operating system for callbacks from incoming connections.
You may be wondering, why does the event loop execute in a single thread? Threads are relatively heavy in memory for the data it needs per connection. Threads are operating system resources that spin up, and this doesn’t scale to thousands of active connections.
Multiple threads in general also complicate the story. If a callback comes back with data, it must marshal context back to the executing thread. Context switching between threads is slow, because it must synchronize current state like the call stack or local variables. The event loop crushes bugs when multiple threads share resources, because it’s single-threaded. A single-threaded loop cuts thread-safety edge cases and can context switch much faster. This is the real genius behind the loop. It makes effective use of connections and threads while remaining scalable.
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