Consider a POST/PUT REST API (using DRF).
If the server receives request1 and within a couple of ms request2 with identical everything to request1 (duplicate request), is there a way to avoid the request2 to be executed using some Django way? Or Should I deal with it manually by some state?
Any inputs would be much appreciated.
There isn't anything out of the box so you would need to write something your self potentially a piece of custom middleware (https://docs.djangoproject.com/en/3.0/topics/http/middleware/) would be best as then it would run over all of the requests. You would need to capture and exam the requests so you'd need a fast storage of some sort such as a memory store.
You could also look into the python asynco library - https://docs.python.org/3/library/asyncio-sync.html
Another possible solution would be using a FIFO message queue which is configured to support de-duplication based on content. This would turn the request into an deferred process though so it may not be suitable for your needs.
Related
I am wondering if there is a standard way to reject requests with the same body sent within a few seconds at the API gateway itself.
Forex: Reddit rejects if I try to post the same content within few seconds in a different group. Similarly, if I make a credit card payment for the second time, it automatically rejects it.
I am wondering if there is a way to have the same behavior in the AWS API gateway itself so that we are not handling it in lambda functions with dynamoDB and stuff.
Looking forward to efficient ways of doing it.
The API Gateway currently doesn't offer a feature like that, you'd have to implement this yourself.
If I was to implement this, I'd probably use an in-memory cache like ElastiCache for Redis or Memcached as the storage backend for deduplications.
For each incoming request I'd determine what makes it unique and create a hash from that.
Then I check if that hash value is in the cache already. If that's the case it 's a duplicate and I reject the request. If it isn't already in the cache, I'd add it with a time to live of n seconds (The time interval in which I wish to deduplicate).
My django rest app accepts request to scrape multiple pages for prices & compare them (which takes time ~5 seconds) then returns a list of the prices from each page as a json object.
I want to update the user with the current operation, for example if I scrape 3 pages I want to update the interface like this :
Searching 1/3
Searching 2/3
Searching 3/3
How can I do this?
I am using Angular 2 for my front end but this shouldn't make a big difference as it's a backend issue.
This isn't the only way, but this is how I do this in Django.
Things you'll need
Asynchronous worker procecess
This allows you to do work outside the context of the request-response cycle. The most common are either django-rq or Celery. I'd recommend django-rq for its simplicity, especially if all you're implementing is a progress indicator.
Caching layer (optional)
While you can use the database for persistence in this case, temporary cache key-value stores make more sense here as the progress information is ephemeral. The Memcached backend is built into Django, however I'd recommend switching to Redis as it's more fully featured, super fast, and since it's behind Django's caching abstraction, does not add complexity. (It's also a requirement for using the django-rq worker processes above)
Implementation
Overview
Basically, we're going to send a request to the server to start the async worker, and poll a different progress-indicator endpoint which gives the current status of that worker's progress until it's finished (or failed).
Server side
Refactor the function you'd like to track the progress of into an async task function (using the #job decorator in the case of django-rq)
The initial POST endpoint should first generate a random unique ID to identify the request (possibly with uuid). Then, pass the POST data along with this unique ID to the async function (in django-rq this would look something like function_name.delay(payload, unique_id)). Since this is an async call, the interpreter does not wait for the task to finish and moves on immediately. Return a HttpResponse with a JSON payload that includes the unique ID.
Back in the async function, we need to set the progress using cache. At the very top of the function, we should add a cache.set(unique_id, 0) to show that there is zero progress so far. Using your own math implementation, as the progress approaches 100% completion, change this value to be closer to 1. If for some reason the operation fails, you can set this to -1.
Create a new endpoint to be polled by the browser to check the progress. This looks for a unique_id query parameter and uses this to look up the progress with cache.get(unique_id). Return a JSON object back with the progress amount.
Client side
After sending the POST request for the action and receiving a response, that response should include the unique_id. Immediately start polling the progress endpoint at a regular interval, setting the unique_id as a query parameter. The interval could be something like 1 second using setInterval(), with logic to prevent sending a new request if there is still a pending request.
When the progress received equals to 1 (or -1 for failures), you know the process is finished and you can stop polling
That's it! It's a bit of work just to get progress indicators, but once you've done it once it's much easier to re-use the pattern in other projects.
Another way to do this which I have not explored is via Webhooks / Channels. In this way, polling is not required, and the server simply sends the messages to the client directly.
I have an Apache Camel (version 2.15.3) route that is configured as follows (using a mix of XML and Java DSL):
Read a file from one of several folders on an FTP site.
Set a header to indicate which folder it was read from.
Do some processing and auditing.
Synchronously POST to an external REST service (jax-rs 1.1, Glassfish, Java EE 6).
The REST service takes a long time to do its job, 20+ minutes.
Receive the reply.
Do some more processing and auditing.
Write the response to one of several folders on an FTP site.
Use the header set at the start to know which folder to write to.
This is all configured in a single path of chained routes.
The problem is that the connection to the external REST service will timeout while the service is still processing. The infrastructure is a bit complex (edge servers, load balancers, Glassfish), and regardless I don't think increasing the timeout is the right solution.
How can I implement this route such that I avoid timeouts while still meeting all my requirements to (1) write the response to the appropriate FTP folder, (2) audit the transaction, and (3) meet other transaction/context-specific requirements?
I'm relatively new to Camel and REST, so maybe this is easy, but I don't know what Camel and REST tools and techniques to use.
(Questions and suggestions for improvement are welcome.)
Isn't it possible to break the two main steps a part and have two asynchronous operations?
I would do as follows.
Read a file from one of several folders on an FTP site.
Set a header to indicate which folder it was read from.
Save the header and file name and other relevant information in a cache. There is a camel component called camel-cache that is relatively easy to setup and you can store key-value or any other objects.
Do some processing and auditing. Asynchronously POST to an external REST service (jax-rs 1.1, Glassfish, Java EE 6). Note that we are posting asynchronously here.
Step 2.
Receive the reply.
Lookup the reply identifiers i.e. filename or some other identifier in cache to match the reply and then fetch the header.
Do some more processing and auditing.
Write the response to one of several folders on an FTP site.
This way, you don't need to wait and processing can take 20 min or longer. You just set your cache values to not expire for say 24h.
This is a typical asynchronous use case. Can the rest service give you a token id or some unique id immediately after you hit them ?
So that you can have a batch job or some other camel route which will pick up this id from a database/cache and hit the rest service again after 20 minutes.
This is the ideal solution I can think of, if the rest service can provision this.
You are right, waiting for 20 minutes on a synchronous call is a crazy idea. Also what is the estimated size of the file/payload which you are planning to post to the rest service ?
I am working on a mobile app that will broadcast a push message to hundreds of thousands of devices at a time. When each user opens their app from the push message, the app will hit our API for data. The API resource will be identical for each user of this push.
Now let's assume that all 500,000 users open their app at the same time. API Gateway will get 500,000 identical calls.
Because all 500,000 nearly concurrent requests are asking for the same data, I want to cache it. But keep in mind that it takes about 2 seconds to compute the requested value.
What I want to happen
I want API Gateway to see that the data is not in the cache, let the first call through to my backend service while the other requests are held in queue, populate the cache from the first call, and then respond to the other 499,999 requests using the cached data.
What is (seems to be) happening
API Gateway, seeing that there is no cached value, is sending every one of the 500,000 requests to the backend service! So I will be recomputing the value with some complex db query way more times than resources will allow. This happens because the last call comes into API Gateway before the first call has populated the cache.
Is there any way I can get this behavior?
I know that based on my example that perhaps I could prime the cache by invoking the API call myself just before broadcasting the bulk push job, but the actual use-case is slightly more complicated than my simplified example. But rest assured, solving this simplified use-case will solve what I am trying to do.
If you anticipate that kind of burst concurrency, priming the cache yourself is certainly the best option. Have you also considered adding throttling to the stage/method to protect your backend from a large surge in traffic? Clients could be instructed to retry on throttles and they would eventually get a response.
I'll bring your feedback and proposed solution to the team and put it on our backlog.
I have a requirement to count the jetty transactions and measure the time it took to process the request and get back the response using JMX for our monitoring system.
I am using Jetty 8.1.7 and I can’t seem to find a proper way to do this. I basically need to identify when request is sent (due to Jetty Async approach this is triggered from thread A) and when the response is complete (as the oncompleteResponse is done in another thread).
I usually use ThreadLocal for such state in other areas I need similar functionality, but obviously this won’t work here.
Any ideas how to overcome?
To use jetty's async requests you basically have to subclass ContentExchange and override its methods. So you can add an extra field to it which would contain a timestamp of when the request was sent, and use it later in your onResponseComplete() method to measure the processing time. If you need to know the time when your request was actually sent to the server instead of when it was created you can override the onRequestCommitted() and onRequestComplete() methods.