So I'd like to know what is the general algorithm to implementing an instant search that is not load intensive. Not specifically on the web but even in a desktop/winforms application.
Correct me if Im wrong but one cannot send async calls on every key stroke right? (Not sure how google instant manages this) It would create an insane load on the database/store etc.
Ive been thinking of something like this:
Fire timer every xxx milliseconds
On fire, Disable input, Disable timer, and send an async call to search.
When the call returns, display results, enable input, enable timer
Is this how it it generally handled, or is there a better way?
Search queries are generally quite small, so the increased load on the server may not be as significant as you think. Sending a query on every keystroke should be fine as long as you keep a limit on the length of queries.
Anyway, it's the server that knows how loaded it is, so the place to put the load management is on the server side. For example, you could follow a strategy something like this:
On the client:
When the search text changes, send it to the server.
When the server sends some results, update the page.
On the server, when a query is received from a client:
If I am already handling a query from that client, cancel the old query.
If I have a queued query from that client, discard it.
Add the new query to a queue of pending search queries, unless the queue is full.
Related
I have an asp.net core Web Api application.
In my application I have Web Api method which I want to prevent multi request from the same user to enter simultaneously. I don't mind request from different users to perform simultaneously.
I am not sure how to create the lock and where to put it. I thought about creating some kind of a dictionary which will contains the user id and perform the lock on the item but I don't think i'm getting it right. Also, what will happen if there is more than one server and there is a load balancer?
Example:
Let assume each registered user can do 10 long task each month. I need to check for each user if he exceeded his monthly limit. If the user will send many simultaneously requests to the server, he might be allowed to perform more than 10 operations. I understand that I need to put a lock on the method but I do want to allow other users to perform this action simultaneously.
What you're asking for is fundamentally not how the Internet works. The HTTP and underlying IP protocols are stateless, meaning each request is supposed to run independent of any knowledge of what has occurred previously (or concurrently, as the case may be). If you're worried about excessive load, your best bet is to implement rate limiting/throttling tied to authentication. That way, once a user burns through their allotted requests, they're cut off. This will then have a natural side-effect of making the developers programming against your API more cautious about sending excessive requests.
Just to be a bit more thorough, here, the chief problem with the approach you're suggesting is that I know of no way it can be practically implemented. You can use something like SemaphoreSlim to create a lock, but that needs to be static so that the same instance is used for each request. Being static is going to limit your ability to use a dictionary of them, which is what you'll need for this. It can technically be done, I suppose, but you'd have to use a ConcurrentDictionary and even then, there's no guarantee of single-thread additions. So, concurrent requests for the same user could load concurrent semphaphores into it, which defeats the entire point. I suppose you could front-load the dictionary with a semphaphore for each user from the start, but that could become a huge waste of resources, depending on your user-base. Long and short, it's one of those things where when you're finding a solution this darn difficult, it's a good sign you're likely trying to do something you shouldn't be doing.
EDIT
After reading your example, I think this really just boils down to an issue of trying to handle the work within the request pipeline. When there's some long-running task to be completed or just some heavy work to be done, the first step should always be to pass it off to a background service. This allows you to return a response quickly. Web servers have a limited amount of threads to handle requests with, and you want to service the request and return a response as quickly as possible to keep from exhausting your threadpool.
You can use a library like Hangfire to handle your background work or you can implement an IHostedService as described here to queue work on. Once you have your background service ready, you would then just immediately hand off to that any time your get a request to this endpoint, and return a 202 Accepted response with a URL the client can hit to check the status. That solves your immediate issue of not wanting to allow a ton of requests to this long-running job to bring your API down. It's now essentially doing nothing more that just telling something else to do it and then returning immediately.
For the actual background work you'd be queuing, there, you can check the user's allowance and if they have exceeded 10 requests (your rate limit), you fail the job immediately, without doing anything. If not, then you can actually start the work.
If you like, you can also enable webhook support to notify the client when the job completes. You simply allow the client to set a callback URL that you should notify on completion, and then when you've finish the work in the background task, you hit that callback. It's on the client to handle things on their end to decide what happens when the callback is it. They might for instance decide to use SignalR to send out a message to their own users/clients.
EDIT #2
I actually got a little intrigued by this. While I still think it's better for your to offload the work to a background process, I was able to create a solution using SemaphoreSlim. Essentially you just gate every request through the semaphore, where you'll check the current user's remaining requests. This does mean that other users must wait for this check to complete, but then your can release the semaphore and actually do the work. That way, at least, you're not blocking other users during the actual long-running job.
First, add a field to whatever class you're doing this in:
private static readonly SemaphoreSlim _semaphore = new SemaphoreSlim(1, 1);
Then, in the method that's actually being called:
await _semaphore.WaitAsync();
// get remaining requests for user
if (remaining > 0)
{
// decrement remaining requests for user (this must be done before this next line)
_semaphore.Release();
// now do the work
}
else
{
_semaphore.Release();
// handle user out of requests (return error, etc.)
}
This is essentially a bottle-neck. To do the appropriate check and decrementing, only one thread can go through the semaphore at a time. That means if your API gets slammed, requests will queue up and may take a while to complete. However, since this is probably just going to be something like a SELECT query followed by an UPDATE query, it shouldn't take that long for the semaphore to release. You should definitely do some load testing and watch it, though, if you're going to go this route.
I am serving my users with data fetched from an external API. Now, I don't know when this API will have new data, how would be the best approach to do that using Node, for example?
I have tried setInterval's and node-schedule to do that and got it working, but isn't it expensive for the CPU? For example, over a day I would hit this endpoint to check for new data every minute, but it could have new data every five minutes or more.
The thing is, this external API isn't ran by me. Would the only way to check for updates hitting it every minute? Is there any module that can do that in Node or any approach that fits better?
Use case 1 : Call a weather API for every city of the country and just save data to my db when it is going to rain in a given city.
Use case 2 : Send notification to the user when a given Philips Hue lamp is turned on at the time it is turned on without having to hit the endpoint to check if it is on or not.
I appreciate the time to discuss this.
If this external API has no means of notifying you when there's new data, then the only thing you can do is to "poll" it to check for new data.
You will have to decide what an "efficient design" for polling is in your specific application and given the type of data and the needs of the client (what is an acceptable latency for new data).
You also need to be sure that your service is not violating any terms of service with your polling scheme or running afoul of rate limiting that may deny you access to the server if you use it "too much".
Would the only way to check for updates hitting it every minute?
Unless the API offers some notification feature, there is no other scheme other than polling at some interval. Polling every minute is fairly quick. Do your clients really need information that is less than a minute old? Or would it really make no difference if the information was as much as 5 minutes old.
For example, in your example of weather, a client wouldn't really need temperature updates more often than probably every 10-15 minutes.
Is there any module that can do that in Node or any approach that fits better?
No. Not really. You'll probably just use some sort of timer (either repeated setTimeout() or setInterval() in a node.js app to repeatedly carry out your API operations.
Use case: Call a weather API for every city of the country and just save data to my db when it is going to rain in a given city.
Trying to pre-save every possible piece of data from an external API is probably a losing proposition. You're essentially trying to "scrape" all the data from the external API. That is likely against the terms of service and will likely also run afoul of rate limits. And, it's just not very practical.
Instead, you will probably want to fetch data upon demand (when a client requests data for Phoenix, then, and only then, do you start collecting data for Phoenix) and then once a demand for a certain type of data (temperatures in a particular city) is established, then you might want to pre-cache that data more regularly so you can notify clients of changes. If, after awhile, no clients are asking for data from Phoenix, you stop requesting updates for Phoenix any more until a client establishes demand again.
I have tried setInterval's and node-schedule to do that and got it working, but isn't it expensive for the CPU? For example, over a day I would hit this endpoint to check for new data every minute, but it could have new data every five minutes or more.
Making a remote network request is not a CPU intensive operation, even if you're doing it every minute. node.js uses non-blocking networking so most of the time during a network request, node.js isn't doing anything and isn't using the CPU at all. The only time the CPU would be briefly used is when you first send the API request and then when you receive back the result from the API call and need to process it.
Whether you really need to "poll" every minute depends upon the data and the needs of the client. I'd ask yourself if your app will work just fine if you check for new data every 5 minutes.
The method I would use to update would be contained outside of the code in a scheduled batch/powershell/bash file. In windows you can schedule tasks based upon time of day or duration since last run, so what you could do is run a simple command that will kill your application for five minutes, run npm update, and then restart your application before closing the shell.
That way you're staying out of your API and keeping code to a minimum, and if your code is inside that Node package in the update, it'll be there and ready once you make serious application changes or you need to take the server down for maintenance and updates to the low-level code.
This is a light-weight solution for you and it's a method I've used once or twice at my workplace. There are lots of options out there, and if this isn't what you're looking for I can keep looking out for you.
I'm building a website that some users will enter and after a specific amount of time an algorithm has to run in order to take the input of the users that is stored in the database and create some results for them storing the results also in the database. The problem is that in nodejs i cant figure out where and how should i implement this algorithm in order to run after a specific amount of time and only once(every few minutes or seconds).
The app is builded in nodejs-expressjs.
For example lets say that i start the application and after 3 minutes the algorithm should run and take some data from the database and after the algorithm has created some output stores it in database again.
What are the typical solutions for that (at least one is enough). thank you!
Let say you have a user request that saves url to crawl and get listed products
So one of the simplest ways would be to:
On user requests create in DB "tasks" table
userId | urlToCrawl | dateAdded | isProcessing | ....
Then in node main site you have some setInterval(findAndProcessNewTasks, 60000)
so it will get all tasks that are not currently in work (where isProcessing is false)
every 1 min or whatever interval you need
findAndProcessNewTasks
will query db and run your algorithm for every record that is not processed yet
also it will set isProcessing to true
eventually once algorithm is finished it will remove the record from tasks (or mark some another field like "finished" as true)
Depending on load and number of tasks it may make sense to process your algorithm in another node app
Typically you would have a message bus (Kafka, rabbitmq etc.) with main app just sending events and worker node.js apps doing actual job and inserting products into db
this would make main app lightweight and allow scaling worker apps
From your question it's not clear whether you want to run the algorithm on the web server (perhaps processing input from multiple users) or on the client (processing the input from a particular user).
If the former, then use setTimeout(), or something similar, in your main javascript file that creates the web server listener. Your server can then be handling inputs from users (via the app listener) and in parallel running algorithms that look at the database.
If the latter, then use setTimeout(), or something similar, in the javascript code that is being loaded into the user's browser.
You may actually need some combination of the above: code running on the server to periodically do some processing on a central database, and code running in each user's browser to periodically refresh the user's display with new data pulled down from the server.
You might also want to implement a websocket and json rpc interface between the client and the server. Then, rather than having the client "poll" the server for the results of your algorithm, you can have the client listen for events arriving on the websocket.
Hope that helps!
If I understand you correctly - I would just send the data to the client-side while rendering the page and store it into some hidden tag (like input type="hidden"). Then I would run a script on the server-side with setTimeout to display the data to the client.
I have an application where users are running a geospatial query against a mongo database. The query can return many thousands of results (~50k). These results are then streamed to the client over a websocket. However, users can abort a request mid result set and execute a new query. Users will frequently start, abort, and re-start requests on the order of several times per minute. Sometimes they even cancel/restart every couple of seconds.
The question is, when a user aborts a request, how do I cancel the query on the server so it doesn't continue to tie up resources streaming back thousands of unneeded results? I'm currently calling destroy() on the cursor, but it's not clear that this is actually stopping the query from executing on the server.
What's the best practice in this case?
Have you tried this?
db.currentOp()
db.killOp(IDRETURNEDHE)
This is a good example.
The answer is it depends upon a lot of your implementation details.
If your server is in the middle of streaming results (e.g. still hasn't sent or queued everything) when the server receives some sort of other message that the previous results should be cancelled, then it is possible for you to communicate with that other stream and tell it to stop sending. How exactly you would do that depends entirely upon your code and you would have to show us your code for us to know.
Chances are the db query is long since complete and what is going on is the server is in the process of streaming results to the client. So, if that's the case, then it isn't the db you're looking for, it's the code that streams the response to the client. Since node.js JS is single threaded, the only time another request would actually get run on the server would be while the streaming code was in some async write operation, waiting for that to finish. You would probably have to set some flag that was uniquely associated with a particular user and then your stream code would have to check for that flag before each chunk of data was sent. If it saw the cancel flag, it could abandon sending the rest of the results.
You could make things more cancellable by explicitly chunking your results (say 500 at a time) and checking for a cancel flag between the sending of each chunk.
If, on the other hand, all the data has already been buffered up by the TCP layer on the server, then the only way to stop that from being sent is to tear down the webSocket and force the client to reconnect.
I have, as part of a meteor application, a server side that gets POST messages of information to feed to the web client via inserts/updates to a Collection. So far so good. However, sometimes these updates can be rather large (50K records a go, every 5 seconds). I was having a hard time keeping up to this until I started using batch-insert package and then low-level batch.find.update() and batch.execute() from Mongo.
However, there is still a good amount of processing going on even with 50K records (it does some calculations, analytics, etc). I would LOVE to be able to "thread" that logic so the main event loop can continue along. However, I am not sure there is a real easy way to create "real" threads for this within Meteor. So baring that, I would like to know the best / proper way of at least "batching" the work so that every N (say 1K or so) records I can release the event loop back to process other events (like some client side DDP messages and the like). Then do another 1K records, etc. until however many records as I need are done.
I am THINKING the solution lies within using Fibers/Futures -- which appear to be the Meteor way -- but I am not positive that is correct or the low level ideas like "setTimeout()" and/or "setImmediate()" are more appropriate.
TIA!
Meteor is not a one size fits all tool. I think you should decouple your meteor application from your batch processing. Set up a separate meteor instance, or better yet set up a pure node.js server to handle these requests and batch processes. It would look like this:
Create a node.js instance that connects to the same mongo database using the mongodb plugin (https://www.npmjs.com/package/mongodb).
Use express if you're using node.js to handle the post requests (https://www.npmjs.com/package/express).
Do the batch processing/inserts/updates in this instance.
The updates in mongo will be reflected in meteor very quickly. I had a similar situation and used a node server to do some batch data collection and then pass it into a cassandra database. I then used pig latin to run some batch operations on that data, and then inserted it into mongo. My meteor application would reactively display the new data pretty much instantaneously.
You can call this.unblock() inside a server method to allow the code to run in the background, and immediately return from the method. See example below.
Meteor.methods({
longMethod: function() {
this.unblock();
Meteor._sleepForMs(1000 * 60 * 60);
}
});