I have a syslog collector implemented in Node.js and want to save these syslogs to a MongoDB collection. The issue is that these syslogs arrive in chunks of dozens at a time.
What is the best way to handle writing that to the database? It seems like what I would like to do is write these several per connection to the database instead of opening and closing a database connection for each syslog message received.
Even better would be to keep a connection to the database open and write each syslog as it arrives.
Is a batch write the way to go here? Basically fill an array in memory that get's emptied every x seconds? In other words .insertMany every x seconds?
Or, is there a way to keep a connection open to Mongo for several .insertOne's?
I need to slightly modify the syslog text prior to inserting it into the database collection. Does this mean I should use a Readable and Writable stream, or does a Writable stream alone work ok? The syslogs are coming in over UDP.
After researching, the correct way to do this is to simply keep the database connection open for the lifetime of your service/app. Basically just insert as records come in. No need to implement a stream beyond what the UDP datagram service already did.
I have a big problem with socket.io which makes my real-time game unplayable.
I want my node.js server to send data every 20ms to every connected client (each socket)
But I notice that the client does not receive every 20ms, it receives several at a time every 100 - 200ms and more. which makes the game totally unplayable (very big lag)
Locally it works very well.
Can you help me please ?
Here is a piece of code of my function that sends data (server side):
function sendData()
{
playersList.forEach( (player) =>
{
let data = [];
// code which add data to "data" variable
socketsList[player.id].emit('refreshGame', JSON.stringify(data));
});
setTimeout(sendData, 20);
}
sendData();
This happens as there are some network bottlenecks. This happens because of:
Packets sent are very big.
Slow network.
To mitigate, try to optimize sending packets, IE only send data that is needed. For example, if I have a game with moving and non-moving components, only send the non-moving components once even though you might send the moving components multiple times.
The other option would be to diagnose the network, which is outside the scope of this stackoverflow question.
However, although these are the "facts", there are some un-conventional or small adjustments that seem to fix this issue based on my own experience.
Get rid of the JSON.stringify on the emit function. Socket.emit automatically does this for you.
Place the setTimeout at the beginning of the function, rather than the end.
Also, make sure that socketsList[player.id] is the player's actual socket. If you use socketsList.splice at some point, it would mess up the indexes totally making it send the packets to the wrong client.
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'm implementing a tcp protocol in Node.
Full source:
https://github.com/roelandmoors/ads.js/blob/master/ads.js
specs:
http://infosys.beckhoff.com/content/1033/tcadsamsspec/html/tcadsamsspec_amstcppackage.htm?id=17754
The problem is that I use this to send a package:
this.tcpClient.write(buf);
If I send multiple commands, then multiple commands are combined into a single tcp packet.
This doesn't work.
There are more questions about this on SO, but they recommend using a delimeter.
But since I can't change the protocol this isn't an option.
Isn't there a simple solution to flush the socket?
socket.setNoDelay() doesn't help.
Edit: I also tried to use the drain event to send the next write, but the event is never called?
Update:
This seems to solve the problem, but is very uggly and I don't now if it always works.
Instead of writing it directly I write to a buffer:
this.writeFILO.push(buf);
Every cycle(?) I'm writing a package to the socket stream:
var sendCycle = function(ads) {
if (ads.writeFILO.length > 0) {
ads.tcpClient.write(ads.writeFILO.shift());
}
setTimeout(function() {
sendCycle(ads);
}, 0);
}
I refer to the socket.write(data, [encoding], [callback]) API:
The optional callback parameter will be executed when the data is finally written out - this may not be immediately.
So, set up a queue (array is fine) which holds messages to be sent.
When the above callback is being called, check the queue and send if needed..
This however does not guarantee what you're looking for, you'll have to test. Unfortunately the docs don't explicitly state when there's an acknowledgement from the remote end point that it actually received that message...
In the end, as you concluded, TCP is a stream.
An interesting idea which just came up to me now, however, if you're FORCED TO use an existing protocol, then open two TCP connections.
When one connection acknowledges (whatever the higher-level protocol is) receiving that message, send the next through the other one... and so forth..
Anyway, nice challenge :)
I was wrong. TCP is a stream and the protocol works like a stream, but I didn't handle it like a stream.
PS: sending seperate messages seemed to work with setImmediate()
I know that this is an old question, and I'm not 100% sure I understand what you are looking for, but there is a way to flush a socket in node. First you need to implement a Transform class.
See here for example: https://nodejs.org/api/stream.html#stream_implementing_a_transform_stream.
Then you can take your stream and pipe it through your transform before piping it into your socket.
I do not own this node module but I have seen an example of this here: https://github.com/yongtang/clamav.js/blob/master/index.js#L8
I have lot's of data to insert (SET \ INCR) to redis DB, so I'm looking for pipeline \ mass insertion through node.js.
I couldn't find any good example/ API for doing so in node.js, so any help would be great!
Yes, I must agree that there is lack of examples for that but I managed to create the stream on which I sent several insert commands in batch.
You should install module for redis stream:
npm install redis-stream
And this is how you use the stream:
var redis = require('redis-stream'),
client = new redis(6379, '127.0.0.1');
// Open stream
var stream = client.stream();
// Example of setting 10000 records
for(var record = 0; record < 10000; record++) {
// Command is an array of arguments:
var command = ['set', 'key' + record, 'value'];
// Send command to stream, but parse it before
stream.redis.write( redis.parse(command) );
}
// Create event when stream is closed
stream.on('close', function () {
console.log('Completed!');
// Here you can create stream for reading results or similar
});
// Close the stream after batch insert
stream.end();
Also, you can create as many streams as you want and open/close them as you want at any time.
There are several examples of using redis stream in node.js on redis-stream node module
In node_redis there all commands are pipelined:
https://github.com/mranney/node_redis/issues/539#issuecomment-32203325
You might want to look at batch() too. The reason why it'd be slower with multi() is because it's transactional. If something failed, nothing would be executed. That may be what you want, but you do have a choice for speed here.
The redis-stream package doesn't seem to make use of Redis' mass insert functionality so it's also slower than the mass insert Redis' site goes on to talk about with redis-cli.
Another idea would be to use redis-cli and give it a file to stream from, which this NPM package does: https://github.com/almeida/redis-mass
Not keen on writing to a file on disk first? This repo: https://github.com/eugeneiiim/node-redis-pipe/blob/master/example.js
...also streams to Redis, but without writing to file. It streams to a spawned process and flushes the buffer every so often.
On Redis' site under mass insert (http://redis.io/topics/mass-insert) you can see a little Ruby example. The repo above basically ported that to Node.js and then streamed it directly to that redis-cli process that was spawned.
So in Node.js, we have:
var redisPipe = spawn('redis-cli', ['--pipe']);
spawn() returns a reference to a child process that you can pipe to with stdin. For example: redisPipe.stdin.write().
You can just keep writing to a buffer, streaming that to the child process, and then clearing it every so often. This then won't fill it up and will therefore be a bit better on memory than perhaps the node_redis package (that literally says in its docs that data is held in memory) though I haven't looked into it that deeply so I don't know what the memory footprint ends up being. It could be doing the same thing.
Of course keep in mind that if something goes wrong, it all fails. That's what tools like fluentd were created for (and that's yet another option: http://www.fluentd.org/plugins/all - it has several Redis plugins)...But again, it means you're backing data on disk somewhere to some degree. I've personally used Embulk to do this too (which required a file on disk), but it did not support mass inserts, so it was slow. It took nearly 2 hours for 30,000 records.
One benefit to a streaming approach (not backed by disk) is if you're doing a huge insert from another data source. Assuming that data source returns a lot of data and your server doesn't have the hard disk space to support all of it - you can stream it instead. Again, you risk failures.
I find myself in this position as I'm building a Docker image that will run on a server with not enough disk space to accommodate large data sets. Of course it's a lot easier if you can fit everything on the server's hard disk...But if you can't, streaming to redis-cli may be your only option.
If you are really pushing a lot of data around on a regular basis, I would probably recommend fluentd to be honest. It comes with many great features for ensuring your data makes it to where it's going and if something fails, it can resume.
One problem with all of these Node.js approaches is that if something fails, you either lose it all or have to insert it all over again.
By default, node_redis, the Node.js library sends commands in pipelines and automatically chooses how many commands will go into each pipeline [(https://github.com/NodeRedis/node-redis/issues/539#issuecomment-32203325)][1]. Therefore, you don't need to worry about this. However, other Redis clients may not use pipelines by default; you will need to check out the client documentation to see how to take advantage of pipelines.