Per the title, is there a maximum number of Get requests?
I need to make a couple hundred get requests to a rest API in order to dynamically load data into webpage, but I find that if I make a Promise.All array and output the promise result in the .then, eventually I get undefined due to request time outs.
Is this due to a limit on the number of connections? Is there a best practice for making large number of simultaneous requests?
Thanks for your insight!
A receiving server has a particular capability for how many simultaneous requests it can handle. It could be a small number or a very large number depending upon a whole bunch of things including the server configuration, the server software architecture, the types of request being sent, etc...
If you're getting timeouts from the server, then you are probably sending enough requests that the server can't process all of them before whatever request timeout is configured (on either client or server) and thus you get a timeout error.
The usual way of handling this on the client is to control how many simultaneous requests you will send at once and then when one finishes, you can send the next and so on. You will have to test to find out what the capabilities are of the receiving server and then you should back off a bit from that to allow other load from other sources some room to execute while your requests are running.
Assuming your requests are not unusually heavy-weight things to do on the server, I would typically test 5 or 10 requests at a time and see how the receiving server handles that.
There's a discussion of a lot of options for controlling this here:
Promise.all consumes all my RAM
Make several requests to an API that can only handle 20 request a minute
Concurrency control is also part of Promise.map() in the Bluebird promise library.
Is there a maximum number of Get requests?
Servers are limited on how many requests they can handle at once for a whole variety of reasons. Every server setup will likely be different and it also depends upon the types of requests you're sending too (and what they have to do). Some servers may be able to handle hundreds of thousands of requests (probably because there's a cluster behind them and they're configured for big load). Smaller configurations may only handle dozens at a time.
Is this due to a limit on the number of connections?
Any receiving server will have a limit on how many incoming connections it will allow to queue. What that is will depend upon many factors and there is no way for you (from the outside) to know exactly what that limit is. Timeout errors usually don't mean you're hitting this limit.
Related
I have an array with a length of one million. Each element is a string. I have a cloud function that takes a string and processes it. What is the fastest way to POST all million strings in my array to the cloud function? I don't care for the response of the cloud function. Ideally, it would POST, not wait for a response, then move on and POST the next one, iterating through the entire list as fast as possible. The issue is apparently with HTTP you cannot not wait for a response. You must wait for the response. Each cloud function takes about 10 seconds to execute. So if I need to wait for each response before moving to the next one, this would take 10 million seconds. Whereas if I could post each and not wait, I could probably run through the entire array in a few seconds.
A lot of this has been covered before in prior questions/answers, but none that I found is a pure duplicate of what you're asking so I'll reference some that have come before and add some explanation. First the ones that have come before:
How to make millions of parallel http requests from nodejs app
How to fire off 1,000,000 requests
Is there a limit to how many promises can or should run concurrently when making requests
In Node js. How many simultaneous requests can I send with the "request" package
What is the limit of sending concurrent ajax requests with node.js?
How to loop many http requests with axios in node.js
Handling large number of outbound HTTP requests
Promise.all consumes all my RAM
Properly batch nested promises in Node
How can I handle a file of 30,000 urls without memory leaks?
First off, you can send a lot of parallel outbound requests. You do not have to wait for a prior response before sending the next one.
Second, you have resource limits on both client and server and ultimately, you will have to explore with testing your local configuration and your target server to find out where those resource limits are and then write your code to stay within those limits. There is no way to reliably send a request and then immediately kill the socket because you don't care about the response. If your socket gets queued by the target server (because you've already overwhelmed it), then killing the socket may drop it from the target server's queue before it gets processed by the target server.
Your local configuration will be limited by how many simultaneous sockets you can have open and how much memory you have (as each outbound request takes some amount of memory to keep track of).
The target server will be limited by its own resources. It may have protections built-in to limit how many posts/sec it can received from one particular source (rate limiting). It may have overall server protections against how many incoming requests at once it can handle. Typically servers protect themselves from overload by configuring things so that once an incoming request queue gets to a certain level, they just immediately hang up on new requests. The idea is to provide some level of protection of service and just deflect new requests when they come in too fast.
If this isn't your target server and there isn't any documentation about what its limits are supposed to be, then you will just have to test how many simutaneous requests you can have "in-flight" at the same time. If they implement rate limiting from a given source, then it's not uncommon that this might be a fairly low number such as 5. If no rate limiting, then you're really just trying to figure out what their http server can handle without causing it to drop connections in defense of service.
Once you figure out (with testing) how many simultaneous requests in flight the target server can comfortably handle, you will have to structure your code to deliver that. Usually, you would take an approach like is show in this mapConcurrent() function where you code things so that only N requests are in flight at the same time where N is a number you figured out experimentally by testing the target server.
Relevant pieces of helper code:
mapConcurrent(array, maxConcurrent, fn)
rateLimitMap(array, requestsPerSec, maxInFlight, fn)
runN(fn, limit, cnt, options)
pMap(array, fn, limit)
And, if you want a pre-made library, the async library contains a bunch of control flow helpers like these.
I'm implementing a networking system in JavaScript (frontend) that will push the requests in a custom queue when there is no internet. The requests will be done, in the exact order, once the computer is re-connected.
The issue I'm having is that if I do the requests one by one, it might take very long to complete them all, and a browser can easily handle multiple requests at the same time.
My question is how can I push as many network request I can without overloading the browser with too many requests? Is there a common JS property that can be used, or something I can use to optimize the number of requests I can simultaneously do without overloading the browser?
I know that different browsers have different amounts of concurrent connections they can handle to the same hostname, but what exactly happens to a new request when that limit is hit?
Does it automatically wait and retry again later or is there something I need to do to help this process along?
Specifically, if this is a XMLHttpRequest executed via JavaScript and not just some assets being loaded by the browser from markup, could that automatically try again?
I have a client side library that makes multiple API requests and occasionally it tries to send too many too quickly. When this happens, I can see server side API errors, but this doesn't make sense. If the concurrency limit stops requests, then they would have never hit the server, would they?
Update: Thanks to #joshstrike and some more testing, I've discovered that my actual problem was not related to concurrent HTTP request limits in the browser. I am not sure these even apply to JavaScript API calls. I have a race condition in the specific API calls I'm making, which gave an error that I initially misunderstood.
The browser will not retry any request on its own if that request times out on the server (for whatever reason - including if you exceed the API's limits). It's necessary to check the status of each request and handle retrying them in some way that's graceful to the application and the user. For failed requests you can check the status code. However for requests which simply hang for a long time it may be necessary to attach a counter to your request, and "cancel" it after a delay... Then if a result comes back bearing the number of one that has already been canceled, ignore that result if a newer one has already returned. This is what typically happens in a long-polling application that is hitting a server constantly and not knowing whether some pings will return later or never return at all.
When the limit on the Chrome is reached it pauses anymore requests. Once one request has been responded to, the browser sends the next request. On Chrome that limit is six for me.
I am creating a question answering application using Node.js + Express for my back-end. Front-end sends the question data to the back-end, which in turn makes requests to multiple third-party APIs to get the answer data.
Problem is, some of those third-party APIs take too long to respond, since they have to do some intense processing and calculations. For that reason, i have already implemented a caching system that saves answer data for each different question. Nevertheless, that first request each time might take up to 5 minutes.
Since my back-end server waits and does not respond back to the front-end until data arrives (the connections are being kept open), it can only serve 6 requests concurrently (that's what I have found). This is unacceptable in terms of performance.
What would be a workaround to this problem? Is there a way to not "clog" the server, so it can serve more than 6 users?
Is there a design pattern, in which the servers gives an initial response, and then serves the full data?
Perhaps, something that sets the request to "sleep" and opens up space for new connections?
Your server can serve many thousands of simultaneous requests if things are coded properly and it's not CPU intensive, just waiting for network responses. This is something that node.js is particularly good at.
A single browser, however, will only send a few requests at a time (it varies by browser) to the same endpoint (queuing the others until the earlier ones finish). So, my guess is that you're trying to test this from a single browser. That's not going to test what you really want to test because the browser itself is limiting the number of simultaneous requests. node.js is particularly good at having lots of request in flight at the same time. It can easily do thousands.
But, if you really have an operation that takes up to 5 minutes, that probably won't even work for an http request from a browser because the browser will probably time out an inactive connection still waiting for a result.
I can think of a couple possible solutions:
First, you could make the first http request be to just start the process and have it return immediately with an ID. Then, the client can check every 30 seconds of so after that sending the ID in an http request and your server can respond whether it has the result yet or not for that ID. This would be a client-polling solution.
Second, you could establish a webSocket or socket.io connection from client to server. Then, send a message over that socket to start the request. Then, whenever the server finishes its work, it can just send the result directly to the client over the webSocket or socket.io connection. After receiving the response, the client can either keep the webSocket/socket.io connection open for use again in the future or it can close it.
I'm developing a single-page application, which sends multiple AJAX request to the server.
The system works with polling, because some data-request can take about 10-20minutes to calculate.
client asks server for data
server hands out a job-id
client asks server every few seconds for the result
The polling algorithm lowers the polling frequency over time, stopping at intervals of 10seconds.
But when a client sends different data requests in a short time, he ends up with about 10-20 job-ids and starts polling for all of them.
Is it better to simply do it this way and let the browser handle those requests in parallel or should I schedule every request and serialize them all?
Would it bring performance benefits to serialize them?
If each initial request returns a unique id and each page has a unique user id then you can poll on what information for each request.
In the JSON I would return the results for any completed request, and the current status of those that haven't completed, such as whether it has started being processed, and perhaps a percentage of completion, or how many requests are ahead of that request.
This will simplify the work as you won't be making several polling calls, but just one, getting back a complex result to give feedback to the user the status of each request.
I find it useful to give some information on status for long-running queries otherwise the user may think the request was lost.
Some months ago, I faced performance issues due to multiple ajax calls, but I haven't investigated deeper this topic since then : High latencies loading stores in an ExtJS 4.1 MVC application.