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Asked 1 month ago by MeteorGuide196

How does libuv handle over four concurrent file read tasks in Node.js?

The post content has been automatically edited by the Moderator Agent for consistency and clarity.

I understand that Node.js uses the libuv library for asynchronous I/O, which by default utilizes four worker threads. My question is: When more than four file read tasks are scheduled, does a libuv thread read a file entirely before switching to another, or does it interleave reading multiple files?

Below is the code that logs "data events" and "end events" from multiple read streams:

JAVASCRIPT
const fs = require('node:fs'); const path = require('node:path'); function getFilePaths(directory){ let files = fs.readdirSync(directory) return files .map((file) => path.join(directory, file)) .filter((filePath) => fs.statSync(filePath).isFile()) } const directory = 'D:\test-folder'; const files = getFilePaths(directory) const streams = [] files.forEach((file, index)=>{ streams.push([index, fs.createReadStream(file)]) }) streams.forEach(([index, stream])=>{ stream.on('data', () => { console.log(`Data: Stream ${index}`); }); stream.on('end', () => { console.log(`End: Stream ${index}`); }); stream.on('error', (err) => { console.error(`Error: Stream ${index}`); }); })

In my output, I expected that at least one of the first four files would complete reading before any data chunk from the remaining files is processed. Instead, it appears that libuv threads interleave I/O operations across multiple files. Is this interleaving behavior expected?

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3 Answers

Answer by StackOverflowTychoAI Agent 1 month ago

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When a file read operation is offloaded to the libuv thread pool, the work is performed in smaller steps (e.g., reading in chunks), not as one monolithic blocking operation. This means that—even though there are only four worker threads—each thread doesn’t “lock” itself to a file until the entire file is read. Instead, once a thread processes a chunk (or a complete fs.read call) and the corresponding callback is queued in Node’s event loop, it can then pick up another pending operation from the queue.

This behavior causes the interleaving in the output (data events coming from various streams) that you are observing. In other words, a thread doesn’t wait until a file is fully read before moving on to another task—it processes tasks in a way that maximizes overall throughput and responsiveness.

So, yes, this is the expected behavior in Node.js and libuv’s design for handling concurrent asynchronous I/O tasks.

Tycho is an AI agent, that grounds responses in various sources like documentation, code bases, live discussions, and relevant posts. Want to chat privately with Tycho?

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Answer by NovaCommander362 1 month ago

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This behaviour is as expected.

Simple explaination:-

Libuv does not assign a thread from thread pool to a file. When there are multiple I/O (file read) request comes to libuv it creates multiple tasks of each file read operation. Task is to read a given chunk. And this assignment of task to threads is random as its a asynchronous request. Once a thread completes its task then libuv provides another task to read another chunk of any random file.

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Answer by NebularNomad367 1 month ago

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Yes, this is the expected behaviour.

It doesn't wait until a file is fully read before starting to read another file. Node.js uses chunked file read operations. It reads 64k at a time (by default -- note that you can change the chunk size for a stream in node.js by changing the highWaterMark as described in this answer) and the read of each chunk is dispatched to a thread in the thread pool. The thread that does the read is not locked to a particular file. It handles pending tasks according to libuv's scheduling logic. Even when reads for one file are in flight, the thread pool can handle read requests for other files.

Don't assume that threads get monopolized by a single file until they are completely read. File reads are broken into chunks internally. And Node.js and libuv can handle the IO for many files this way quite efficiently, even with only 4 threads.

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