[zzzeek]

> if you schedule them in an async fashion you can begin operating on the first one that's ready and not the first one you defined.

This type of operation is a given in any production quality webserver, whether it runs with multiple threads and blocking IO or using a non-blocking approach with greenlets. For a web application, this is an implementation detail that should not be explicit within the request handling code (a request handled in the context of a web container after all is a package of data in, a package of data out. no network reading/writing is usually exposed to the web application unless it's trying to expose IO handles to the app, which is unusual). Easy enough with something like Gunicorn.

[icebraining]

I think you're talking about different things; the idea is not that you can multiplex the requests coming in, but also the requests going out to the database and etc for each web request handling function.

[zzzeek]

So on that topic, a request typically has a single transaction going out to the database so within the scope of the request, has to perform its steps in serial in any case. If it needs to make several requests to web services that aren't dependent on each other, that's an area where you can get into stacking them with some kind of concurrency construct (I'd pass it into a greenlet oriented worker pool). but this is already going to be a heavy web request with multiple web service calls.

[kazagistar]

> a request typically has a single transaction going out to the database

Its typical because people are still in a "single thread single transaction ORM crud" model of thinking. "Its linear because thats how it is"?

[zzzeek]

if you're using an ACID kind of database then yes, that's how it is :)

[makmanalp]

> this is already going to be a heavy web request with multiple web service calls

Sure, but it can now be a less heavy web request! ¯\_(ツ)_/¯

> a request typically has a single transaction going out to the database

The fact of the matter is, as applications develop, become richer, and grow larger, it becomes less and less uncommon to have more than one query per page. Especially in the context of larger organizations, it's very common to have everything wrapped behind a service call with an entire armada of infrastructure hidden behind it, and having to make many service calls to put together one web API result or page.

---

sigh Slight tangent. Look at where we are now and how we came here.

Back in the non-ajax days we used to do them all on the server side, then render the whole page all in one go. This would have come in handy back then! Imagine doing 5x 50ms queries asynchronously, dropping a 250ms response delay down to 50ms! But this stuff was hard back then, and we mostly left it alone.

This is also along the times when we figured out that since we can have pages that take a long time to load and block the interpreter, perhaps it's not such a great idea to serve many requests with a single interpreter, so people started using stuff like nginx to run multiple python interpreters in parallel (not even getting into threads here), which was easier to reason about since each python process is a separate universe that can block entirely, but overall we can still serve a new request with a new interpreter, so for the most part things are good.

Then the twisted people thought that this was silly, and why should we block in the first place, and they decided that the way to fix this was to change the way we program entirely, and re-create or wrap an entire ecosystem of software. It sort of worked, except there wasn't a good twisted package for your thing. But all in all it worked.

Then the greenlets (or one of its other 20 names) people came and wanted to instead use fine-grained implicit concurrency, and said "no no, we can get something with nicer abstraction packaging while mostly not changing the code we have", and that was even nicer, except when something didn't get monkey patched correctly for some reason. We got stuff like gunicorn, which was impressive.

Then as we moved more stuff to the client to create more responsive (in the original meaning of the word) applications, so we pushed the burden of requesting and fetching data to the browser side, which means that as a page loads, it might call REST APIs one by one (hopefully asynchronously!), each of which might make a single (finer-grained) database or service call behind the scenes.

So how different is this now from the gunicorn model? In the latter, you get fine threads of control, each working asynchronously to fetch their own thing, which gets put together in the server side, and then sent back to the client. In the former, you get similarly fine threads of control, but the fine threads perhaps live in their own universes, and it doesn't get all put back together until it travels over the internet to the browser.

So it's a little bit different, but overall what's happening is similar. It feels like we just keep moving concerns and procedures up and down the stack.

Surely there's reasons for all this. Times and technologies change, and we find ways to adapt. I like the "async" stuff because it makes things explicit. It's the middle-ground result of the culmination of our learnings that hiding async behavior makes libraries hard to design and can result in frustrating and unpredictable behavior, whilst changing the entire programming model isn't great either. So we get asyncio. I'm mostly happy with this result. Admittedly this article isn't doing any of this justice.

[zzzeek]

> it becomes less and less uncommon to have more than one query per page.

I said transaction, not query. A database transaction is on a single connection at a time and queries are performed via the transaction serially.

[coldtea]

>I said transaction, not query. A database transaction is on a single connection at a time and queries are performed via the transaction serially.

Unless you're doing e-commerce or banking sites, that's far less common that non-transaction requests.

[zzzeek]

unless you're using MyISAM or something like that, all your queries are in transactions.

edit: also, I'd challenge you to prove that for a web request that needs to make ten read queries to a relational database, from Python, that you can get better performance by opening up ten separate database connections (or from a pool) and running one query in each, bundled into the async construct of your choice and then merging them all back into your response, vs. just running ten queries on a single connection in serial. Assume these are not slow reporting-style transactions, just the usual "load the users full name, load the current status, load the user's current items", etc., small queries common in a web request that is looking for a very fast response with ten SQL queries.

Note that at the very least, it means your web application needs to use ten times as many database connections for a given set of load. In database-land that's more or less crazy.

[merb]

not everything is transaction centric. and also before I make a transaction I mostly fetch various stuff before and sometimes after.

and also my count example, it just makes no sense to have the count and the list data called inside a transaction (ok there are cases, but these are way more rare, because mostly It's not to bad to give users a wrong count, you don't need strict Serializability)

[zzzeek]

see my edit at https://news.ycombinator.com/item?id=14218862 where I propose a challenge to show that it's more efficient to use ten relational database connections for a request that needs to run ten small queries, vs running ten queries on a single DB connection.

[dagw]

In many non trivial cases I tend to find that I have to query several different databases to render a single page.

[zzzeek]

depending on the latency of those database connections I've argued in the past that the overhead of adding asyncio context switching and boilerplate is more expensive than just hitting the two or three databases in serial (and if your web request is having to hit dozens of DB sources to serve one request, I think you've already lost the performance game :) ). When your one web request is contending with many other concurrent web requests in any case, doing the DB calls in serial just lets the CPU attend to other requests.