How to handle stream errors in Node.js
Łukasz Holeczek
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Handling stream errors properly in Node.js prevents application crashes and ensures robust data processing in production environments. As the creator of CoreUI with over 11 years of Node.js development experience, I’ve implemented comprehensive error handling in stream-based applications, file processing systems, and data pipelines. From my expertise, the most reliable approach is using error event listeners, pipeline error handling, and proper cleanup mechanisms for stream failures. This pattern ensures applications remain stable and provide meaningful error feedback when stream operations encounter problems.
Use error event listeners and pipeline error handling to manage stream failures and prevent application crashes.
const fs = require('fs')
const { pipeline } = require('stream')
const { Transform } = require('stream')
// Error handling with event listeners
const readStream = fs.createReadStream('input.txt')
const writeStream = fs.createWriteStream('output.txt')
readStream.on('error', (error) => {
console.error('Read stream error:', error.message)
writeStream.destroy()
})
writeStream.on('error', (error) => {
console.error('Write stream error:', error.message)
readStream.destroy()
})
// Better error handling with pipeline
const transform = new Transform({
transform(chunk, encoding, callback) {
try {
const processed = chunk.toString().toUpperCase()
callback(null, processed)
} catch (error) {
callback(error)
}
}
})
pipeline(
fs.createReadStream('input.txt'),
transform,
fs.createWriteStream('output.txt'),
(error) => {
if (error) {
console.error('Pipeline failed:', error.message)
} else {
console.log('Pipeline completed successfully')
}
}
)
Here individual streams use on('error', ...) event listeners to handle specific stream errors and properly clean up resources. The pipeline() function provides centralized error handling that automatically destroys all streams if any fail. Transform stream errors are handled in the callback function, and the pipeline callback receives any errors from the entire chain. This approach prevents memory leaks and ensures proper resource cleanup.
Best Practice Note:
This is the same approach we use in CoreUI backend services for robust file processing, data transformation pipelines, and real-time stream processing with proper error recovery. Always use pipeline() for production stream chains and implement retry logic for recoverable errors to build resilient data processing systems.
