I'm not trying to be snarky here, but that would advocate for no improvements anywhere else. Why did Ruby 1.9 bother with a new VM? Why try to improve GC? Why bother with invokedynamic? Why speed up JSON parsing? Why bother with speeding up YAML? Yet there's obviously value in improving all these areas and they speed up almost every Ruby app.
It's overly simplistic to say the only option is to cache everything. Or that your DB is going to be your ultimate bottleneck, so the other N - 1 items are worth investigating.
And even in the link you supplied, the illustrative example is getting a 20 hour process down to 1 hour without speeding up the single task that takes 1 hour. It suggests there's an upper limit, not that because there is an upper limit you can't possibly do better than the status quo.
" that would advocate for no improvements anywhere else"
Amdahl's law advocates starting from the part that takes the most time. In a database application, it can be interpreted as either A) improving the connector or B) reducing the application's demand for database resources.
"Why did Ruby 1.9 bother with a new VM? Why try to improve GC? Why bother with invokedynamic? Why speed up JSON parsing? Why bother with speeding up YAML? Yet there's obviously value in improving all these areas and they speed up almost every Ruby app."
JSON parsing improves those applications that use JSON parsing, and in many applications JSON parsing is the main operation. There are many other applications for which garbage collection is the limiting factor. You are taking my comment, which was addressing the parent comment's remark that "This fallacy about DB access and not needing to optimize really needs to go away though.", way out of context. It's not a fallacy -- you need to know what is dominating execution time and how to improve that aspect.
Take it to the logical extreme -- you could just write in x86 assembly directly. The program would be faster than ruby, but the development time would not make assembly a worthwhile target.
"And even in the link you supplied"
What link did I supply? I recommend the Hennessy and Patterson "Computer Architecture" book :)
Sorry about the link comment. I'm so used to Wikipedia links being passed around I must have instinctively looked there.
In any event, we probably agree on more than we disagree. I never disagreed with working on the DB if that's truly the bulk of your cost. But, you do actually need to measure that. It seems quite common nowadays to say "if you use a DB, that's where your cost is". And I routinely see this as an argument to justify practices that are almost certainly going to cause performance issues.
Put another way, I routinely see the argument put forth that the DB access is going to be the slowest part, so there's little need to reduce the other hotspots because you're just going to hit that wall anyway. And then the next logical argument is all you need is caching. The number of Rubyists I've encountered that know how to profile an app or have ever done so is alarmingly small. Which is fine, but you can't really argue about performance otherwise.
It's overly simplistic to say the only option is to cache everything. Or that your DB is going to be your ultimate bottleneck, so the other N - 1 items are worth investigating.
And even in the link you supplied, the illustrative example is getting a 20 hour process down to 1 hour without speeding up the single task that takes 1 hour. It suggests there's an upper limit, not that because there is an upper limit you can't possibly do better than the status quo.