Related
I want to know the performance gain from doing a HTTP batch request. is it only reducing the number of round trips to one instead of n times where n is the number of HTTP requests? if it's like that I guess you can keep http connection opened and send your http messages through and once finish you can close it to get performance gain.
The performance gain of doing batch requests depends on what you are doing with them. However just as an agnostic approach here you go:
If you can manage a keep-alive connection, yes this means you don't have to do the initial handshake for the connection. That reduces some overhead and certainly saves time spent handling subsequent packets along this connection. Because of this you can "pipeline" requests and decrease overall load latency (all else not considered). However, requests in HTTP1.1 are still bound to be FIFO so you can have hangups. This is where batching is useful. Since even with a keep-alive connection you can have this hangup (HTTP/2 will allow asynchronous handling) you can still have some significant latency between requests.
This can be mitigated further by batching. If possible you lump all the data needed for subsequent requests into one and this way everything is processed together and sent back as one response. Sure it may take a bit longer to handle a single packet as opposed to the sequential method, but your throughput is increased per time because roundtrip latency for request->response is not multiplied. Thus you get an even better performance gain in terms of requests handling speeds.
Naturally this approach depends on what you're doing with the requests for it to be effective. Sometimes batching can put too much stress on a server if you have a lot of users doing this with a lot of data so to increase overall concurrent throughput across all users you sometimes need to take the technically slower sequential approach to balance things out. However, the best approach will be known by you upon some simple monitoring and analysis.
And as always, don't optimize prematurely :)
Consider this typical scenario: the client has the identifier of a resource which resides in a database behind an HTTP server, of which resource they want to get an object representation.
The general flow to execute that goes like this:
The client code constructs an HTTP client.
The client builds an URI and sets the proper HTTP request fields.
Client issues the HTTP request.
Client OS initiates a TCP connection, which the server accepts.
Client sends the request to the server.
Server OS or webserver parses the request.
Server middleware parses the request components into a request for the server application.
Server application gets initialized, the relevant module is loaded and passed the request components.
The module obtains an SQL connection.
Module builds an SQL query.
The SQL server finds the record and returns that to the module.
Module parses the SQL response into an object.
Module selects the proper serializer through content negotiation, JSON in this case.
The JSON serializer serializes the object into a JSON string.
The response containing the JSON string is returned by the module.
Middleware returns this response to the HTTP server.
Server sends the response to the client.
Client fires up their version of the JSON serializer.
Client deserializes the JSON into an object.
And there you have it, one object obtained from a webserver.
Now each of those steps along the way is heavily optimized, because a typical server and client execute them so many times. However, even if one of those steps only take a millisecond, when you for example have fifty resources to obtain, those milliseconds add up fast.
So yes, HTTP keep-alive cuts away the time the TCP connection takes to build up and warm up, but each and every other step will still have to be executed fifty times. Yes, there's SQL connection pooling, but every query to the database adds overhead.
So instead of going through this flow fifty separate times, if you have an endpoint that can accept fifty identifiers at once, for example through a comma-separated query string or even a POST with a body, and return their JSON representation at once, that will always be way faster than individual requests.
Could someone please explain multiplexing in relation to HTTP/2 and how it works?
Put simply, multiplexing allows your Browser to fire off multiple requests at once on the same connection and receive the requests back in any order.
And now for the much more complicated answer...
When you load a web page, it downloads the HTML page, it sees it needs some CSS, some JavaScript, a load of images... etc.
Under HTTP/1.1 you can only download one of those at a time on your HTTP/1.1 connection. So your browser downloads the HTML, then it asks for the CSS file. When that's returned it asks for the JavaScript file. When that's returned it asks for the first image file... etc. HTTP/1.1 is basically synchronous - once you send a request you're stuck until you get a response. This means most of the time the browser is not doing very much, as it has fired off a request, is waiting for a response, then fires off another request, then is waiting for a response... etc. Of course complex sites with lots of JavaScript do require the Browser to do lots of processing, but that depends on the JavaScript being downloaded so, at least for the beginning, the delays inherit to HTTP/1.1 do cause problems. Typically the server isn't doing very much either (at least per request - of course they add up for busy sites), because it should respond almost instantly for static resources (like CSS, JavaScript, images, fonts... etc.) and hopefully not too much longer even for dynamic requests (that require a database call or the like).
So one of the main issues on the web today is the network latency in sending the requests between browser and server. It may only be tens or perhaps hundreds of millisecond, which might not seem much, but they add up and are often the slowest part of web browsing - especially as websites get more complex and require extra resources (as they are getting) and Internet access is increasingly via mobile (with slower latency than broadband).
As an example let's say there are 10 resources that your web page needs to load after the HTML is loaded itself (which is a very small site by today's standards as 100+ resources is common, but we'll keep it simple and go with this example). And let's say each request takes 100ms to travel across the Internet to web server and back and the processing time at either end is negligible (let's say 0 for this example for simplicity sake). As you have to send each resource and wait for a response one at a time, this will take 10 * 100ms = 1,000ms or 1 second to download the whole site.
To get around this, browsers usually open multiple connections to the web server (typically 6). This means a browser can fire off multiple requests at the same time, which is much better, but at the cost of the complexity of having to set-up and manage multiple connections (which impacts both browser and server). Let's continue the previous example and also say there are 4 connections and, for simplicity, let's say all requests are equal. In this case you can split the requests across all four connections, so two will have 3 resources to get, and two will have 2 resources to get totally the ten resources (3 + 3 + 2 + 2 = 10). In that case the worst case is 3 round times or 300ms = 0.3 seconds - a good improvement, but this simple example does not include the cost of setting up those multiple connections, nor the resource implications of managing them (which I've not gone into here as this answer is long enough already but setting up separate TCP connections does take time and other resources - to do the TCP connection, HTTPS handshake and then get up to full speed due to TCP slow start).
HTTP/2 allows you to send off multiple requests on the same connection - so you don't need to open multiple connections as per above. So your browser can say "Gimme this CSS file. Gimme that JavaScript file. Gimme image1.jpg. Gimme image2.jpg... Etc." to fully utilise the one single connection. This has the obvious performance benefit of not delaying sending of those requests waiting for a free connection. All these requests make their way through the Internet to the server in (almost) parallel. The server responds to each one, and then they start to make their way back. In fact it's even more powerful than that as the web server can respond to them in any order it feels like and send back files in different order, or even break each file requested into pieces and intermingle the files together. This has the secondary benefit of one heavy request not blocking all the other subsequent requests (known as the head of line blocking issue). The web browser then is tasked with putting all the pieces back together. In best case (assuming no bandwidth limits - see below), if all 10 requests are fired off pretty much at once in parallel, and are answered by the server immediately, this means you basically have one round trip or 100ms or 0.1 seconds, to download all 10 resources. And this has none of the downsides that multiple connections had for HTTP/1.1! This is also much more scalable as resources on each website grow (currently browsers open up to 6 parallel connections under HTTP/1.1 but should that grow as sites get more complex?).
This diagram shows the differences, and there is an animated version too.
Note: HTTP/1.1 does have the concept of pipelining which also allows multiple requests to be sent off at once. However they still had to be returned in order they were requested, in their entirety, so nowhere near as good as HTTP/2, even if conceptually it's similar. Not to mention the fact this is so poorly supported by both browsers and servers that it is rarely used.
One thing highlighted in below comments is how bandwidth impacts us here. Of course your Internet connection is limited by how much you can download and HTTP/2 does not address that. So if those 10 resources discussed in above examples are all massive print-quality images, then they will still be slow to download. However, for most web browser, bandwidth is less of a problem than latency. So if those ten resources are small items (particularly text resources like CSS and JavaScript which can be gzipped to be tiny), as is very common on websites, then bandwidth is not really an issue - it's the sheer volume of resources that is often the problem and HTTP/2 looks to address that. This is also why concatenation is used in HTTP/1.1 as another workaround, so for example all CSS is often joined together into one file: the amount of CSS downloaded is the same but by doing it as one resource there are huge performance benefits (though less so with HTTP/2 and in fact some say concatenation should be an anti-pattern under HTTP/2 - though there are arguments against doing away with it completely too).
To put it as a real world example: assume you have to order 10 items from a shop for home delivery:
HTTP/1.1 with one connection means you have to order them one at a time and you cannot order the next item until the last arrives. You can understand it would take weeks to get through everything.
HTTP/1.1 with multiple connections means you can have a (limited) number of independent orders on the go at the same time.
HTTP/1.1 with pipelining means you can ask for all 10 items one after the other without waiting, but then they all arrive in the specific order you asked for them. And if one item is out of stock then you have to wait for that before you get the items you ordered after that - even if those later items are actually in stock! This is a bit better but is still subject to delays, and let's say most shops don't support this way of ordering anyway.
HTTP/2 means you can order your items in any particular order - without any delays (similar to above). The shop will dispatch them as they are ready, so they may arrive in a different order than you asked for them, and they may even split items so some parts of that order arrive first (so better than above). Ultimately this should mean you 1) get everything quicker overall and 2) can start working on each item as it arrives ("oh that's not as nice as I thought it would be, so I might want to order something else as well or instead").
Of course you're still limited by the size of your postman's van (the bandwidth) so they might have to leave some packages back at the sorting office until the next day if they are full up for that day, but that's rarely a problem compared to the delay in actually sending the order across and back. Most of web browsing involves sending small letters back and forth, rather than bulky packages.
Since #Juanma Menendez answer is correct while his diagram is confusing, I decided to improve upon it, clarifying the difference between multiplexing and pipelining, the notions that are often conflated.
Pipelining (HTTP/1.1)
Multiple requests are sent over the same HTTP connection. Responses are received in the same order. If the first response takes a lot of time, other responses have to wait in line. Similar to CPU pipeling where an instruction is fetched while another one is being decoded. Multiple instructions are in flight at the same time, but their order is preserved.
Multiplexing (HTTP/2)
Multiple requests are sent over the same HTTP connection. Responses are received in the arbitrary order. No need to wait for a slow response that's blocking others. Similar to out-of-order instruction execution in modern CPUs.
Hopefully the improved image clarifies the difference:
Request multiplexing
HTTP/2 can send multiple requests for data in parallel over a single TCP connection. This is the most advanced feature of the HTTP/2 protocol because it allows you to download web files asynchronously from one server. Most modern browsers limit TCP connections to one server. This reduces the additional round trip time (RTT), making your website load faster without any optimization, and makes domain sharding unnecessary.
Multiplexing in HTTP 2.0 is the type of relationship between the browser and the server that use a single connection to deliver multiple requests and responses in parallel, creating many individual frames in this process.
Multiplexing breaks away from the strict request-response semantics and enables one-to-many or many-to-many relationships.
Simple Ans (Source) :
Multiplexing means your browser can send multiple requests and receive multiple responses "bundled" into a single TCP connection. So the workload associated with DNS lookups and handshakes is saved for files coming from the same server.
Complex/Detailed Ans:
Look out the answer provided by #BazzaDP.
I'm trying to find an architecture for the following scenario. I'm building a REST service that performs some computation that can be quickly batch computed. Let's say that computing 1 "item" takes 50ms, and computing 100 "items" takes 60ms.
However, the nature of the client is that only 1 item needs to be processed at a time. So if I have 100 simultaneous clients, and I write the typical request handler that sends one item and generates a response, I'll end up using 5000ms, but I know I could compute the same in 60ms.
I'm trying to find an architecture that works well in this scenario. I.e., I would like to have something that merges data from many independent requests, processes that batch, and generates the equivalent responses for each individual client.
If you're curious, the service in question is python+django+DRF based, but I'm curious about what kind of architectural solutions/patterns apply here and if anything solving this is already available.
At first you could think of a reverse proxy detecting all pattern-specific queries, collecting all theses queries and sending it to your application in an HTTP 1.1 pipeline (pipelining is a way to send a big number of queries one after another and receiving all HTTP responses in the same order at the end, without waiting for a response after each query).
But:
Pipelining is very hard to do well
you would have to code the reverse proxy as I do not know a way to do it
one slow response in the pipeline block all the other responses
you need an http server able to give several queries to your application language, something which never happens if the http server is not directly coded in your application, because usually http is made to work on only one query (like you never receive 2 queries in a PHP env, you receive the 1st one, send the response, and then receive the next one, even if the connection contain 2 queries).
So the good idea would be to do that on the application side. You could identify matching queries, and wait for a small amount of time (10ms?) to see if some other queries are also incoming. You will need a way to communicate between several parallel workers here (like you have 50 application workers and 10 of them have received queries that could be treated in the same batch). This way of communication could be a database (a very fast one) or some shared memory, depends on the technology used.
Then when too much time waiting has been spend (10ms?) or when a big amount of queries are received, one of the worker could collect all queries, run the batch, and tell every other workers that a result is there (here again you need a central point of communication, like LISTEN/NOTIFY in PostgreSQL, a shared memory thing, a message queue service, etc.).
Finally every worker is responsible for sending the right HTTP response.
The key here is having a system where the time you loose in trying to share requests treatment is less important than the time saved in batching several queries together, and in case of low traffic this time should stay reasonnable (as here you will always loose time waiting for nothing). And of course you are also adding some complexity on the system, harder to maintain, etc.
I just read that some browsers would prevent HTTP polling (I guess by limiting the rate of requests)...
From https://github.com/sstrigler/JSJaC:
Note: As security restrictions of most modern browsers prevent HTTP
Polling from being usable anymore this module is disabled by default
now. If you want to compile it in use 'make polling'.
This could explain some misbehavior of some of my JavaScripts (sometimes requests are just not sent or retried, even if they were actually successful). But I couldn't find further information on details..
Questions
if it's "max. number of requests n per x seconds", what are the usual/default settings for x and n?
Is there any way good resource for this?
Any way to detect if a request has been "delayed" or "rejected" because of a rate limit?
Thanks for your help...
Stefan
Yes, as far as I am aware there is a default pool limit of 10 and a default request timeout of 30 seconds per request, however the timeout and poll limits can be controlled and different browsers implement different limitations!
Check out this Google implementation.
and this is an awesome implementation of catching a timeout error!
You can find the Firefox specifics HERE!
Internet Explorer specifics are controlled from inside the Windows registry.
Also have a look at this question.
Basically, the way you control is not by changing the browser limitations, but by abiding them. So you apply a technique called throttle-ing.
Think of it as creating a FIFO/priority queue of functions. A queue struct that takes xhr requests as members and enforces delay between them is an Xhr Poll. For instance, I am using
Jsonp to get data from a node.js server located on another domain and I am polling of course due to browser limitations. Otherwise, I get zero response back from the server and that is only because of browser limitations.
I am actually doing a console log for every request that's supposed to be sent, but not all of them are being logged. So the browser limits them.
I'll be even more specific with helping you out. I have a page on my website which is supposed to render a view for tens or even hundreds of articles. You go through them using a cool horizontal slider.
The current value of the slider matches the currrent 'page'. Since I am only displaying 5 articles per page and I can't exactly load thousands of articles 'onload' without severe performance implications, I load the articles for the current page. I get them from a MongoDB by sending a cross-domain request to a Python script.
The script is supposed to return an array of five objects with all the details I need to build the DOM elements for a 'page'. However, there are a couple of issues.
First, the slider works extremely fast, as it's more or less a value change. Even if there is drag drop functionality, key down events etc, the actual change takes miliseconds. However, the code of the slider looks something like this:
goog.events.listen(slider, goog.events.EventType.CHANGE, function() {
myProject.Articles.page(slider.getValue());
}
The slider.getValue() method returns an int with the current page number, so basically I have to load from:
currentPage * articlesPerPage to (currentPage * articlesPerPage + 1) - 1
But in order to load, i do something like this:
I have a storage engine(think of it as an array):
I check if the content is not already there
If it is, there is no point to make another request, so go forward with getting the DOM elements from the array with the already created DOM elements in place.
If it isn't, then I need to get it so I need to send that request I was mentioning, which would look something like(without accounting for browser limitations):
JSONP.send({'action':'getMeSomeArticles','start':start,'length': itemsPerPage, function(callback){
// now I just parse the callback quickly to make sure it is consistent
// create DOM elements, and populate the client side storage
// and update the view for the user.
}}
The problem comes from the speed with which you can change that slider. Since every change supposedly triggers a request(same would happen for normal Xhr requests), then you are basically crossing the limitations of all browsers, so without throttle-ing, there would be no 'callback' for most of the requests. 'callback' is the JS code returned by the JSONP request(which is more of a remote script inclusion than anything else).
So what I do is push a request to a priority queue, not POLL, as now I don't need to send multiple simultaneous requests. If the queue is empty, the recently added member is executed and everyone is happy. If it's not, then all non-completed requests in progress are cancelled and only the last one is executed.
Now in my particular case, I do a binary search(0(log n)) to see if the storage engine doesn't have data for the previous requests yet, which tells me if the previous request has been completed or not. If it has, then it's removed from the queue and the current one is processed, otherwise the new one fires. So an and so forth.
Again, for speed consideration and shit browser wanna-bes such as Internet Explorer, I do the above described procedure about 3-4 steps ahead. So I pre-load 20 pages ahead till everything is the client side storage engine. This way, every limitation is successfully dealt with.
The cooldown time is covered by the minimum time it would take to slide through 20 pages and the throttle-ing makes sure there are no more than 1 active requests at any given time(with backwards compatibility going as far as Internet Explorer 5).
The reason why I wrote all this is to give you an example trying to say that you cannot always enforce delay directly from the FIFO structure, as your calls may need to turn into what a user sees, and you don't exactly want to make a user wait 10-15 seconds for a single page to render.
Also, always minimize the polling and the need to poll(simultaneously fired Ajax events, as not all browsers actually do good things with them). For instance, instead of doing something like sending one request to get content and sending another for that content to be tracked as viewed in your app metrics, do as many tasks at server level as you possibly can!
Of course, you probably want to track your errors properly, so your Xhr object from your library of choice implement error handling for ajax and because you are an awesome developer you want to make use of them.
so say you have a try - catch block in place
The scenario is this:
An Ajax call has finished and it's supposed to return a JSON, but the call somehow failed. However, you try to parse the JSON and do whatever you need to do with it.
so
function onAjaxSuccess (ajaxResponse) {
try {
var yourObj = JSON.parse(ajaxRespose);
} catch (err) {
// Now I've actually seen this on a number of occasions, to log that an error occur
// a lot of developers will attempt to send yet another ajax request to log the
// failure of the previous one.
// for these reasons, workers exist.
myProject.worker.message('preferrably a pre-determined error code should go here');
// Then only the worker should again throttle and poll the ajax requests that log the
//specific error.
};
};
While I have seen various implementations that try to fire as many Xhr requests at the same time as they possible can until they encounter browser limitations, then do quite a good job at stalling the ones that haven't fired in wait for the browser 'cooldown', what I can advise you is to think about the following:
How important is speed for your app?
Just how scalable and how intensive the I/O will be?
If the answer to the first one is 'very' and to the latter 'OMFG modern technology', then try to optimize your code and architecture as much as you can so that you never need to send 10 simultaneous Xhr requests. Also, for large scale apps, multi-thread your processes. The JavaScript way to accomplish that is by using workers. Or you could call the ECMA board, tell them to make this a default, and then post it here so that the rest of us JS devs can enjoy native multi-threading in JS:)(how dafuq did they not think about this?!?!)
Stefan, quick answers below:
-if it's "max. number of requests n per x seconds", what are the usual/default settings for x and n?
This sounds more like a server restriction. The browser ones usually sound like:
-"the maximum requests for the same hostname is x"
-"the maximum connections for ANY hostname is y"
-Is there any way good resource for this?
http://www.browserscope.org/?category=network (also hover over table headers to see what is measured)
http://www.stevesouders.com/blog/2008/03/20/roundup-on-parallel-connections
-Any way to detect if a request has been "delayed" or "rejected" because of a rate limit?
You could look at the http headers for "Connection: close" to detect server restrictions but I am not aware of being able in JavaScript to read settings from so many browsers in a consistent, browser-independent way. (For Firefox, you could read this http://support.mozilla.org/en-US/questions/746848)
Hope this quick answer helps?
No, browser does not in any way affect polling. I think what was meant on that page is the same origin policy - you can only access the same host and port as your original page.
Only known limitation to connections themselves is that you usually can only have from two to four simultaneous connections to the same host.
I've written some apps with long poll, some with C++ backend with my own webserver, and one with PHP backend with Apache2.
My long poll timeout is 4..10 s. When something occurs, or 4..10 s passes, my server returns an empty response. Then the client immediatelly starts another AJAX request. I found that some browsers hangs up when I start AJAX call from previous AJAX handler, so I am using setTimeout() with a small value to start the next AJAX request.
When something happens on the client side, which should be sent to server, I use another AJAX request for it, but it's a one-way thing: the server does not send any response, and the client does not process anything. The result of the operation (if any) will be received on the long poll. It requires max. 2 connection to the server, which all browsers supports.
Keep in mind, that if there's 500 client, it means 500 server-side webserver thread, which will move together, occurring load peaks, because when something happens, the server have to report it at the same time for each clients, the clients will process it near same time long, they will start the next long request in the same time, and from then, the timeout will expire also at the same time, and furthcoming ones too. You can trick with rnd timeout, say 4 rnd(0..4), but it's worthless, if anything happens, they will "sync" again, all the request have to be served at the same time, when something reportable happens.
I've tested it thru a router, and it works. I assume, routers respects 4..10 lag, it's around the speed of a slow webapge (far, far away), which no router think, that it should be canceled.
My PHP work is a collaborative spreadsheet, it looks amazing when you hit enter and the stuff is updating simultaneously in several browsers. Have fun!
No limit for no of ajax requests. However it will be on same host & port.
Server can limit no of request from a machine based on its setting.
For example. A server can set so that if there are more than few request from same machine within specified time it will reject request.
After small mistake in javascript code, neverending loop was made witch each step calling 2 ajax requests. In firebug i could see more and more requests until firefox started to slow down, dont response and finally crash.
So, yes, there is a "limit" ;)
Will it be smart and queue later requests for submission after earlier requests complete, or will it do something stupid like discard later requests which push it over its maximum number.
Is the answer the same across browsers, or does it vary?
Are you referring to the fact that browsers typically limit the number of simultaneous connections to a particular host (2 is recommended by the HTTP spec)? If so, then yes, all requests will be queued. It's really no different then loading a web page that has a lot of images in it -- the initial load will result in a bunch of new requests, but they may have to wait based on the connection limit. But all of your images do load.
I'm not aware of an ajax-specific request limit.