The Node.js documentation makes the following comments about a Writable stream's _writev method.
The writable._writev() method may be implemented in addition or alternatively to writable._write() in stream implementations that are capable of processing multiple chunks of data at once. If implemented and if there is buffered data from previous writes, _writev() will be called instead of _write().
Emphasis mine. In what scenarios can a Node.js writable stream have buffered data from previous writes?
Is the _writev method only called after uncorking a corked stream that's had data written to it? Or are there other scenarios where a stream can have buffered date from previous writes? Bonus point if you can point to the place in the Node.js source code where it makes a decisions w/r/t to calling _write or _writev.
_writev() will be called whenever there is more than one piece of data buffered from the stream and the function has been defined. Using cork() could cause more data to be buffered, but so could slow processing.
The code that guards _writev is in lib/internal/streams/writable.js. There is a buffer decision and then the guard for the write.
Question:
In Node.js, if a Readable stream is piped to a Writable stream and both go out of scope, is the pair of streams liable to be garbage collected before the reader is complete? (because they are now inaccessible)
Background:
I am trying to understand the effects of pipes on stream object lifetimes. I am operating under the assumption that a pipe represents a bidirectional reference between the two streams, so that if one is accessible, neither will be garbage collected (until, of course, the reader ends and the pipe is closed).
So with that assumption: Is there anything under the hood in the runtime that holds streams in existence while a pipe is active, or while a 'data' listener on the Readable is doing the equivalent? (apart from the obvious, like references embedded in event listener functions and other objects)
A concrete example would be piping a file read stream to an http response object. If I "pipe-and-forget", and retain no reference to the file or response stream, is this process liable to be interrupted mid-stream?
Or alternatively, if something is holding off the GC for piped streams, would a bidirectional pipe between two sockets exist indefinitely, even if they were both inaccessible? (and be totally unclosable?)
The answer, as usual, is: it depends.
If nothing references the stream objects then they will be garbage collected. However, there might be references elsewhere than in your code.
Note that the writable stream is referenced by the readable stream via event handlers, so all we really need is a reference to the readable stream to keep both alive.
If the source is a stream that is capable of producing data all by itself (it reads from a file, the network, or something in memory) and the pipeline is flowing, then it will be referenced by a callback somewhere (an I/O continuation, event handler, or closure given to setTimeout() or process.nextTick()).
If the source is a stream that is waiting for you to push data into it or the pipeline is paused, then there are likely no references and both streams will eventually be garbage-collected.
I have a question about Node.js streams - specifically how they work conceptually.
There is no lack of documentation on how to use streams. But I've had difficulty finding how streams work at the data level.
My limited understanding of web communication, HTTP, is that full "packages" of data are sent back and forth. Similar to an individual ordering a company's catalogue, a client sends a GET (catalogue) request to the server, and the server responds with the catalogue. The browser doesn't receive a page of the catalogue, but the whole book.
Are node streams perhaps multipart messages?
I like the REST model - especially that it is stateless. Every single interaction between the browser and server is completely self contained and sufficient. Are node streams therefore not RESTful? One developer mentioned the similarity with socket pipes, which keep the connection open. Back to my catalogue ordering example, would this be like an infomercial with the line "But wait! There's more!" instead of the fully contained catalogue?
A large part of streams is the ability for the receiver 'down-stream' to send messages like 'pause' & 'continue' upstream. What do these messages consist of? Are they POST?
Finally, my limited visual understanding of how Node works includes this event loop. Functions can be placed on separate threads from the thread pool, and the event loop carries on. But shouldn't sending a stream of data keep the event loop occupied (i.e. stopped) until the stream is complete? How is it ALSO keeping watch for the 'pause' request from downstream?n Does the event loop place the stream on another thread from the pool and when it encounters a 'pause' request, retrieve the relevant thread and pause it?
I've read the node.js docs, completed the nodeschool tutorials, built a heroku app, purchased TWO books (real, self contained, books, kinda like the catalogues spoken before and likely not like node streams), asked several "node" instructors at code bootcamps - all speak about how to use streams but none speak about what's actually happening below.
Perhaps you have come across a good resource explaining how these work? Perhaps a good anthropomorphic analogy for a non CS mind?
The first thing to note is: node.js streams are not limited to HTTP requests. HTTP requests / Network resources are just one example of a stream in node.js.
Streams are useful for everything that can be processed in small chunks. They allow you to process potentially huge resources in smaller chunks that fit into your RAM more easily.
Say you have a file (several gigabytes in size) and want to convert all lowercase into uppercase characters and write the result to another file. The naive approach would read the whole file using fs.readFile (error handling omitted for brevity):
fs.readFile('my_huge_file', function (err, data) {
var convertedData = data.toString().toUpperCase();
fs.writeFile('my_converted_file', convertedData);
});
Unfortunately this approch will easily overwhelm your RAM as the whole file has to be stored before processing it. You would also waste precious time waiting for the file to be read. Wouldn't it make sense to process the file in smaller chunks? You could start processing as soon as you get the first bytes while waiting for the hard disk to provide the remaining data:
var readStream = fs.createReadStream('my_huge_file');
var writeStream = fs.createWriteStream('my_converted_file');
readStream.on('data', function (chunk) {
var convertedChunk = chunk.toString().toUpperCase();
writeStream.write(convertedChunk);
});
readStream.on('end', function () {
writeStream.end();
});
This approach is much better:
You will only deal with small parts of data that will easily fit into your RAM.
You start processing once the first byte arrived and don't waste time doing nothing, but waiting.
Once you open the stream node.js will open the file and start reading from it. Once the operating system passes some bytes to the thread that's reading the file it will be passed along to your application.
Coming back to the HTTP streams:
The first issue is valid here as well. It is possible that an attacker sends you large amounts of data to overwhelm your RAM and take down (DoS) your service.
However the second issue is even more important in this case:
The network may be very slow (think smartphones) and it may take a long time until everything is sent by the client. By using a stream you can start processing the request and cut response times.
On pausing the HTTP stream: This is not done at the HTTP level, but way lower. If you pause the stream node.js will simply stop reading from the underlying TCP socket.
What is happening then is up to the kernel. It may still buffer the incoming data, so it's ready for you once you finished your current work. It may also inform the sender at the TCP level that it should pause sending data. Applications don't need to deal with that. That is none of their business. In fact the sender application probably does not even realize that you are no longer actively reading!
So it's basically about being provided data as soon as it is available, but without overwhelming your resources. The underlying hard work is done either by the operating system (e.g. net, fs, http) or by the author of the stream you are using (e.g. zlib which is a Transform stream and usually bolted onto fs or net).
The below chart seems to be a pretty accurate 10.000 feet overview / diagram for the the node streams class.
It represents streams3, contributed by Chris Dickinson.
So first of all, what are streams?
Well, with streams we can process meaning read and write data piece by piece without completing the whole read or write operation. Therefore we don't have to keep all the data in memory to do these operations.
For example, when we read a file using streams, we read part of the data, do something with it, then free our memory, and repeat this until the entire file has been processed. Or think of YouTube or Netflix, which are both called streaming companies because they stream video using the same principle.
So instead of waiting until the entire video file loads, the processing is done piece by piece or in chunks so that you can start watching even before the entire file has been downloaded. So the principle here is not just about Node.JS. But universal to computer science in general.
So as you can see, this makes streams the perfect candidate for handing large volumes of data like for example, video or also data that we're receiving piece by piece from an external source. Also, streaming makes the data processing more efficient in terms of memory because there is no need to keep all the data in memory and also in terms of time because we can start processing the data as it arrives, rather than waiting until everything arrives.
How they are implemented in Node.JS:
So in Node, there are four fundamental types of streams:
readable streams, writable streams, duplex streams, and transform streams. But the readable and writeable ones are the most important ones, readable streams are the ones from which we can read and we can consume data. Streams are everywhere in the core Node modules, for example, the data that comes in when an http server gets a request is actually a readable stream. So all the data that is sent with the request comes in piece by piece and not in one large piece. Also, another example from the file system is that we can read a file piece by piece by using a read screen from the FS module, which can actually be quite useful for large text files.
Well, another important thing to note is that streams are actually instances of the EventEmitter class. Meaning that all streams can emit and listen to named events. In the case of readable streams, they can emit, and we can listen to many different events. But the most important two are the data and the end events. The data event is emitted when there is a new piece of data to consume, and the end event is emitted as soon as there is no more data to consume. And of course, we can then react to these events accordingly.
Finally, besides events, we also have important functions that we can use on streams. And in the case of readable streams, the most important ones are the pipe and the read functions. The super important pipe function, which basically allows us to plug streams together, passing data from one stream to another without having to worry much about events at all.
Next up, writeable streams are the ones to which we can write data. So basically, the opposite of readable streams. A great example is the http response that we can send back to the client and which is actually a writeable stream. So a stream that we can write data into. So when we want to send data, we have to write it somewhere, right? And that somewhere is a writeable stream, and that makes perfect sense, right?
For example, if we wanted to send a big video file to a client, we would just like Netflix or YouTube do. Now about events, the most important ones are the drain and the finish events. And the most important functions are the write and end functions.
About duplex streams. They're simply streams that are both readable and writeable at the same time. These are a bit less common. But anyway, a good example would be a web socket from the net module. And a web socket is basically just a communication channel between client and server that works in both directions and stays open once the connection has been established.
Finally, transform streams are duplex streams, so streams that are both readable and writeable, which at the same time can modify or transform the data as it is read or written. A good example of this one is the zlib core module to compress data which actually uses a transform stream.
*** Node implemented these http requests and responses as streams, and we can then consume, we can use them using the events and functions that are available for each type of stream. We could of course also implement our own streams and then consume them using these same events and functions.
Now let's try some example:
const fs = require('fs');
const server = require('http').createServer();
server.on('request', (req, res) =>{
fs.readFile('./txt/long_file.txt', (err, data)=>{
if(err) console.log(err);
res.end(data);
});
});
server.listen('8000','127.0.01', ()=>{
console.log(this);
});
Suppose long_file.txt file contain 1000000K lines and each line contain more thean 100 words, so this is a hug file with a big chunk of data, now in the above example problem is by using readFile() function node will load entire file into memory, because only after loading the whole file into memory node can transfar the data as a responce object.
When the file is big, and also when there are a ton of request hitting your server, by means of time node process will very quickly run out of resources and your app will quit working, everything will crash.
Let's try to find a solution by using stream:
const fs = require('fs');
const server = require('http').createServer();
server.on('request', (req, res) =>{
const readable = fs.createReadStream('./txt/long_file.txt');
readable.on('data', chunk=>{
res.write(chunk);
});
readable.on('end',()=>{
res.end();
})
readable.on('error', err=>{
console.log('err');
res.statusCode=500;
res.end('File not found');
});
});
server.listen('8000','127.0.01', ()=>{
console.log(this);
});
Well in the above example with the stream, we are effectively streaming the file, we are reading one piece of the file, and as soon as that's available, we send it right to the client, using the write method of the respond stream. Then when the next pice is available then that piece will be sent, and all the way until the entire file is read and streamed to the client.
So the stream is basically finished reading the data from the file, the end event will be emitted to signals that no more data will be written to this writable stream.
With the above practice, we solved previous problem, but still, there is a huge problem remain with the above example which is called backpressure.
The problem is that our readable stream, the one that we are using to read files from the disk, is much much faster than actually sending the result with the response writable stream over the network. And this will overwhelm the response stream, which cannot handle all this incoming data so fast and this problem is called backpressure.
The solution is using the pipe operator, it will handle the speed of data coming in and speed of data going out.
const fs = require('fs');
const server = require('http').createServer();
server.on('request', (req, res) =>{
const readable = fs.createReadStream('./txt/long_file.txt');
readable.pipe(res);
});
server.listen('8000','127.0.01', ()=>{
console.log(this);
});
I think you are overthinking how all this works and I like it.
What streams are good for
Streams are good for two things:
when an operation is slow and it can give you partials results as it gets them. For example read a file, it is slow because HDDs are slow and it can give you parts of the file as it reads it. With streams you can use these parts of the file and start to process them right away.
they are also good to connect programs together (read functions). Just as in the command line you can pipe different programs together to produce the desired output. Example: cat file | grep word.
How they work under the hood...
Most of these operations that take time to process and can give you partial results as it gets them are not done by Node.js they are done by the V8 JS Engine and it only hands those results to JS for you to work with them.
To understand your http example you need to understand how http works
There are different encodings a web page can be send as. In the beginning there was only one way. Where a whole page was sent when it was requested. Now it has more efficient encodings to do this. One of them is chunked where parts of the web page are sent until the whole page is sent. This is good because a web page can be processed as it is received. Imagine a web browser. It can start to render websites before the download is complete.
Your .pause and .continue questions
First, Node.js streams only work within the same Node.js program. Node.js streams can't interact with a stream in another server or even program.
That means that in the example below, Node.js can't talk to the webserver. It can't tell it to pause or resume.
Node.js <-> Network <-> Webserver
What really happens is that Node.js asks for a webpage and it starts to download it and there is no way to stop that download. Just dropping the socket.
So, what really happens when you make in Node.js .pause or .continue?
It starts to buffer the request until you are ready to start to consume it again. But the download never stopped.
Event Loop
I have a whole answer prepared to explain how the Event Loop works but I think it is better for you to watch this talk.
I have a ClearTextStream for a TLS connection and I want to check if "end" was already called. The actual problem is, that I'm trying to write something into the stream and I get an "write after end" error.
Now to avoid that, I just want to check if "end" was already called. I do have an "close" event, but it isn't fired in all cases.
I can't find it in the documentation and I couldn't find anything like that by googling.
I could check the error event (which is throwing "write after end" for me) and handle the situation there - but is there really no way to check this in the beginning?
Thanks!
If you get a write after end error, that means that you are trying to write data to a Writable stream that has been closed (ie. that can't accept anymore input data). When a writable stream closes, the finish event is emitted (see the documentation). On the other hand, the close event is emitted by a Readable stream, when the underlying resource is closed (for instance when the file descriptor you are reading is closed).
As a ClearTextStream is a Duplex stream, it can emit both close and finish events, but they don't mean the same thing. In your particular case, you should listen to the finish event and react appropriately.
Another solution would be to check the this.ended and this.finished booleans (see the source code), but I wouldn't recommend that as they are private variables and only reflect the implementation details, not the public API.
I've often heard of Streams2 and old-streams, but what is Streams3? It get mentioned in this talk by Thorsten Lorenz.
Where can I read about it, and what is the difference between Streams2 and Streams3.
Doing a search on Google, I also see it mentioned in the Changelog of Node 0.11.5,
stream: Simplify flowing, passive data listening (streams3) (isaacs)
I'm going to give this a shot, but I've probably got it wrong. Having never written Streams1 (old-streams) or Streams2, I'm probably not the right guy to self-answer this one, but here it goes. It seems as if there is Streams1 API that still persists to some degree. In Streams2, there are two modes of streams flowing (legacy), and non-flowing. In short, the shim that supported flowing mode is going away. This was the message that lead to the patch now called called Streams3,
Same API as streams2, but remove the confusing modality of flowing/old
mode switch.
Every time read() is called, and returns some data, a data event fires.
resume() will make it call read() repeatedly. Otherwise, no change.
pause() will make it stop calling read() repeatedly.
pipe(dest) and on('data', fn) will automatically call resume().
No switches into old-mode. There's only flowing, and paused. Streams start out paused.
Unfortunately, to understand any of description which defines Streams3 pretty well, you need to first understand Streams1, and the legacy streams
Backstory
First, let's take a look at what the Node v0.10.25 docs say about the two modes,
Readable streams have two "modes": a flowing mode and a non-flowing mode. When in flowing mode, data is read from the underlying system and provided to your program as fast as possible. In non-flowing mode, you must explicitly call stream.read() to get chunks of data out. — Node v0.10.25 Docs
Isaac Z. Schlueter said in November slides I dug up:
streams2
"suck streams"
Instead of 'data' events spewing, call read() to pull data from source
Solves all problems (that we know of)
So it seems as if in streams1, you'd create an object and call .on('data', cb) to that object. This would set the event to be trigger, and then you were at the mercy of the stream. In Streams2 internally streams have buffers and you request data from those streams explicitly (using `.read). Isaac goes on to specify how backwards compat works in Streams2 to keep Streams1 (old-stream) modules functioning
old-mode streams1 shim
New streams can switch into old-mode, where they spew 'data'
If you add a 'data' event handler, or call pause() or resume(), then switch
Making minimal changes to existing tests to keep us honest
So in Streams2, a call to .pause() or .resume() triggers the shim. And, it should, right? In Streams2 you have control over when to .read(), and you're not catching stuff being thrown at you. This triggered a legacy mode that acted independently of Streams2.
Let's take an example from Isaac's slide,
createServer(function(q,s) {
// ADVISORY only!
q.pause()
session(q, function(ses) {
q.on('data', handler)
q.resume()
})
})
In Streams1, q starts up right away reading and emitting (likely losing data), until the call to q.pause advises q to stop pulling in data but not from emitting events to clear what it already read.
In Streams2, q starts off paused until the call to .pause() which signifies to emulate the old mode.
In Streams3, q starts off as paused having never read from the file handle making the q.pause() a noop, and on the call to q.on('data', cb) will call q.resume until there is no more data in the buffer. And, then call again q.resume doing the same thing.
Seems like Streams3 was introduced in io.js, then in Node 0.11+
Streams 1 Supported data being pushed to a stream. There was no consumer control, data was thrown at the consumer whether it was ready or not.
Streams 2 allows data to be pushed to a stream as per Streams 1, or for a consumer to pull data from a stream as needed. The consumer could control the flow of data in pull mode (using stream.read() when notified of available data). The stream can not support both push and pull at the same time.
Streams 3 allows pull and push data on the same stream.
Great overview here:
https://strongloop.com/strongblog/whats-new-io-js-beta-streams3/
A cached version (accessed 8/2020) is here: https://hackerfall.com/story/whats-new-in-iojs-10-beta-streams-3
I suggest you read the documentation, more specifically the section "API for Stream Consumers", it's actually very understandable, besides I think the other answer is wrong: http://nodejs.org/api/stream.html#stream_readable_read_size