How to handle streaming data in Node ? - GeeksforGeeks (2024)

Streaming data in NodeJS involves processing data in chunks as it becomes available, rather than waiting for the entire dataset to be loaded into memory. This approach is particularly useful for handling large files, network data, or real-time data sources. NodeJS provides a powerful set of streaming APIs that allow developers to efficiently handle streaming data. Here’s how you can handle streaming data in NodeJS:

Reading from Streams:

NodeJS provides various readable streams, such as fs.createReadStream() for reading data from files, http.IncomingMessage for reading data from HTTP requests, and process.stdin for reading data from standard input.

const fs = require('fs');
const readStream = fs.createReadStream('input.txt');

readStream.on('data', (chunk) => {
console.log('Received data chunk:', chunk.toString());
});

readStream.on('end', () => {
console.log('Finished reading data.');
});

Writing to Streams:

Writable streams in NodeJS, such as fs.createWriteStream() for writing data to files, http.ServerResponse for writing data to HTTP responses, and process.stdout for writing data to standard output, allow you to write data chunk by chunk.

const fs = require('fs');
const writeStream = fs.createWriteStream('output.txt');

writeStream.write('Hello, ');
writeStream.write('World!');
writeStream.end(); // Close the stream

Transforming Streams:

Transform streams enable you to modify or transform data as it passes through the stream. You can create custom transform streams by extending the Transform class from the stream module and implementing the _transform() method.

const { Transform } = require('stream');

class UpperCaseTransform extends Transform {
_transform(chunk, encoding, callback) {
this.push(chunk.toString().toUpperCase());
callback();
}
}

const upperCaseTransform = new UpperCaseTransform();
process.stdin.pipe(upperCaseTransform).pipe(process.stdout);

Piping Streams:

Piping streams together is a common pattern in NodeJS, allowing you to connect the output of one stream to the input of another stream, creating a data pipeline.

const fs = require('fs');
const readStream = fs.createReadStream('input.txt');
const writeStream = fs.createWriteStream('output.txt');

readStream.pipe(writeStream);

Conclusion:

NodeJS provides a versatile set of streaming APIs that enable efficient handling of streaming data. By using readable, writable, transform, and piping streams, developers can process large datasets, handle network communication, and perform real-time data processing tasks with ease. Leveraging streaming data processing capabilities is essential for building scalable, performant, and memory-efficient applications in NodeJS.



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How to handle streaming data in Node ? - GeeksforGeeks (2024)

FAQs

How do you handle streaming data? ›

How Streaming Data Works
  1. Aggregate all your data sources using a CDC streaming tool from relational databases or transactional systems which may be located on-premises or in the cloud. ...
  2. Build a stream processor using a tool such as Apache Kafka or Amazon Kinesis. ...
  3. Query or store the streaming data.

How to read stream data in nodejs? ›

To create a readable stream, first, import the 'stream' module and then create an instance of the readable stream by adding the following:
  1. const Stream = require('stream') const readableStream = new Stream. ...
  2. readableStream. ...
  3. > mkdir streams-example > cd streams-example > touch index.js > touch read.txt.
Mar 6, 2022

How does nodejs streaming work? ›

Streams in Node. js work on the principle of events and backpressure. Data is consumed or produced in chunks, and events like `data`, `end`, and `error` are emitted to notify the application about the stream's state.

What are the challenges of querying on a large data stream? ›

Data streaming comes with its own set of challenges:
  • High Volume and Velocity: Processing massive amounts of data continuously can strain resources and overwhelm traditional systems.
  • Scalability: Systems need to adapt to fluctuating data flow, requiring flexible and scalable architecture.
Feb 12, 2015

How do you handle late data in streaming? ›

To handle late and out-of-order data, one of the common techniques is to use windowing and watermarking. Windowing is a way of dividing the stream of data into fixed or dynamic intervals based on event time or processing time, and applying some aggregation or computation function to each window.

What is the basics of streaming data? ›

What is Streaming Data? Also known as event stream processing, streaming data is the continuous flow of data generated by various sources. By using stream processing technology, data streams can be processed, stored, analyzed, and acted upon as it's generated in real-time.

What are the four types of streams in node JS? ›

There are 4 types of streams in Node. js:
  • Writable: streams to which we can write data. For example, fs. ...
  • Readable: streams from which data can be read. For example: fs. ...
  • Duplex: streams that are both Readable and Writable. ...
  • Transform: streams that can modify or transform the data as it is written and read.
Nov 22, 2019

When to use streams in NodeJS? ›

Scalability for real-time processing: By handling data in chunks, Node. js with streams can efficiently handle large amounts of data with limited resources. This scalability makes streams ideal for applications that process high volumes of data in real time.

How to save file from stream in NodeJS? ›

The simplest way to use a Got stream and write the file to the file system looks like this: const got = require("got"); const { createWriteStream } = require("fs"); const url = "https://media0.giphy.com/media/4SS0kfzRqfBf2/giphy.gif"; got. stream(url). pipe(createWriteStream('image.

What is an example of streaming data? ›

For example, you can first process data in a streaming data platform such as Amazon Kinesis to extract real-time insights. Then, you can persist it into a store like Amazon Simple Storage Service (Amazon S3). There, it can be transformed and loaded for various batch processing use cases.

What are the different types of queries in data stream? ›

One-time queries (a class that includes traditional DBMS queries) are queries that are evaluated once over a point-in-time snapshot of the data set, with the answer returned to the user. Continuous queries, on the other hand, are evaluated continuously as data streams continue to arrive.

What is the problem in handling big data? ›

A Big Data Problem refers to challenges related to the speed, structure, volume, cost, value, security, privacy, and interoperability of large datasets that traditional IT methods struggle to handle efficiently.

How can I reduce my data usage while streaming? ›

6 tips to conserve your data while streaming
  1. Tip 1: Reduce Video Quality.
  2. Tip 2: Limit Streaming on Mobile Data.
  3. Tip 3: Use Data Saver Modes.
  4. Tip 4: Download Content for Offline Viewing.
  5. Tip 5: Monitor Data Usage.
  6. Tip 6: Use Wi-Fi Whenever Possible.
Apr 18, 2024

Does streaming use a lot of Internet data? ›

On average, streaming video data usage for SD quality is around 0.7 to 1 GB of data per hour, while HD streaming can use approximately 1.5 to 2.5 GB of data per hour. UHD or 4K streaming typically consumes even more data, with estimates ranging from 7 to 10 GB per hour.

How do I know if my Internet can handle streaming? ›

The best internet speed for streaming is about 100 Mbps or higher. This is usually great for streaming 4k videos and online gaming. The minimum upload speed for streaming usually falls between 1 Mbps and 1.5 Mbps. This speed can support SD 480p streams of lower quality.

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