From a lot of articles and commercial API I saw, most people make their APIs idempotent by asking the client to provide a requestId or idempotent-key (e.g. https://www.masteringmodernpayments.com/blog/idempotent-stripe-requests) and basically store the requestId <-> response map in the storage. So if there's a request coming in which already is in this map, the application would just return the stored response.
This is all good to me but my problem is how do I handle the case where the second call coming in while the first call is still in progress?
So here is my questions
I guess the ideal behaviour would be the second call keep waiting until the first call finishes and returns the first call's response? Is this how people doing it?
if yes, how long should the second call wait for the first call to be finished?
if the second call has a wait time limit and the first call still hasn't finished, what should it tell the client? Should it just not return any responses so the client will timeout and retry again?
For wunderlist we use database constraints to make sure that no request id (which is a column in every one of our tables) is ever used twice. Since our database technology (postgres) guarantees that it would be impossible for two records to be inserted that violate this constraint, we only need to react to the potential insertion error properly. Basically, we outsource this detail to our datastore.
I would recommend, no matter how you go about this, to try not to need to coordinate in your application. If you try to know if two things are happening at once then there is a high likelihood that there would be bugs. Instead, there might be a system you already use which can make the guarantees you need.
Now, to specifically address your three questions:
- For us, since we use database constraints, the database handles making things queue up and wait. This is why I personally prefer the old SQL databases - not for the SQL or relations, but because they are really good at locking and queuing. We use SQL databases as dumb disconnected tables.
- This depends a lot on your system. We try to tune all of our timeouts to around 1s in each system and subsystem. We'd rather fail fast than queue up. You can measure and then look at your 99th percentile for timings and just set that as your timeout if you don't know ahead of time.
- We would return a 504 http status (and appropriate response body) to the client. The reason for having a idempotent-key is so the client can retry a request - so we are never worried about timing out and letting them do just that. Again, we'd rather timeout fast and fix the problems than to let things queue up. If things queue up then even after something is fixed one has to wait a while for things to get better.
It's a bit hard to understand if the second call is from the same client with the same request token, or a different client.
Normally in the case of concurrent requests from different clients operating on the same resource, you would also want to implementing a versioning strategy alongside a request token for idempotency.
A typical version strategy in a relational database might be a version column with a trigger that auto increments the number each time a record is updated.
With this in place, all clients must specify their request token as well as the version they are updating (typical the IfMatch header is used for this and the version number is used as the value of the ETag).
On the server side, when it comes time to update the state of the resource, you first check that the version number in the database matches the supplied version in the ETag. If they do, you write the changes and the version increments. Assuming the second request was operating on the same version number as the first, it would then fail with a 412 (or 409 depending on how you interpret HTTP specifications) and the client should not retry.
If you really want to stop the second request immediately while the first request is in progress, you are going down the route of pessimistic locking, which doesn't suit REST API's that well.
In the case where you are actually talking about the client retrying with the same request token because it received a transient network error, it's almost the same case.
Both requests will be running at the same time, the second request will start because the first request still has not finished and has not recorded the request token to the database yet, but whichever one ends up finishing first will succeed and record the request token.
For the other request, it will receive a version conflict (since the first request has incremented the version) at which point it should recheck the request token database table, find it's own token in there and assume that it was a concurrent request that finished before it did and return 200.
It's seems like a lot, but if you want to cover all the weird and wonderful failure modes when your dealing with REST, idempotency and concurrency this is way to deal with it.
