gnuoytr@xxxxxxx writes:
> Time for my pet meme to wiggle out of its hole (next to Phil's, and a
> day later). For PG to prosper in the future, it has to embrace the
> multi-core/processor/SSD machine at the query level. It has to. And
> it has to because the Big Boys already do so, to some extent, and
> they've realized that the BCNF schema on such machines is supremely
> efficient. PG/MySql/OSEngineOfChoice will get left behind simply
> because the efficiency offered will be worth the price.
>
> I know this is far from trivial, and my C skills are such that I can
> offer no help. These machines have been the obvious "current" machine
> in waiting for at least 5 years, and those applications which benefit
> from parallelism (servers of all kinds, in particular) will filter out
> the winners and losers based on exploiting this parallelism.
>
> Much as it pains me to say it, but the MicroSoft approach to software:
> write to the next generation processor and force users to upgrade,
> will be the winning strategy for database engines. There's just way
> too much to gain.
I'm not sure how true that is, really. (e.g. - "too much to gain.")
I know that Jan Wieck and I have been bouncing thoughts on valid use of
threading off each other for *years*, now, and it tends to be
interesting but difficult to the point of impracticality.
But how things play out are quite fundamentally different for different
usage models.
It's useful to cross items off the list, so we're left with the tough
ones that are actually a problem.
1. For instance, OLTP applications, that generate a lot of concurrent
connections, already do perfectly well in scaling on multi-core systems.
Each connection is a separate process, and that already harnesses
multi-core systems perfectly well. Things have improved a lot over the
last 10 years, and there may yet be further improvements to be found,
but it seems pretty reasonable to me to say that the OLTP scenario can
be treated as "solved" in this context.
The scenario where I can squint and see value in trying to multithread
is the contrast to that, of OLAP. The case where we only use a single
core, today, is where there's only a single connection, and a single
query, running.
But that can reasonably be further constrained; not every
single-connection query could be improved by trying to spread work
across cores. We need to add some further assumptions:
2. The query needs to NOT be I/O-bound. If it's I/O bound, then your
system is waiting for the data to come off disk, rather than to do
processing of that data.
That condition can be somewhat further strengthened... It further needs
to be a query where multi-processing would not increase the I/O burden.
Between those two assumptions, that cuts the scope of usefulness to a
very considerable degree.
And if we *are* multiprocessing, we introduce several new problems, each
of which is quite troublesome:
- How do we decompose the query so that the pieces are processed in
ways that improve processing time?
In effect, how to generate a parallel query plan?
It would be more than stupid to consider this to be "obvious." We've
got 15-ish years worth of query optimization efforts that have gone
into Postgres, and many of those changes were not "obvious" until
after they got thought through carefully. This multiplies the
complexity, and opportunity for error.
- Coordinating processing
Becomes quite a bit more complex. Multiple threads/processes are
accessing parts of the same data concurrently, so a "parallelized
query" that harnesses 8 CPUs might generate 8x as many locks and
analogous coordination points.
- Platform specificity
Threading is a problem in that each OS platform has its own
implementation, and even when they claim to conform to common
standards, they still have somewhat different interpretations. This
tends to go in one of the following directions:
a) You have to pick one platform to do threading on.
Oops. There's now PostgreSQL-Linux, that is the only platform
where our multiprocessing thing works. It could be worse than
that; it might work on a particular version of a particular OS...
b) You follow some apparently portable threading standard
And find that things are hugely buggy because the platforms
follow the standard a bit differently. And perhaps this means
that, analogous to a), you've got a set of platforms where this
"works" (for some value of "works"), and others where it can't.
That's almost as evil as a).
c) You follow some apparently portable threading standard
And need to wrap things in a pretty thick safety blanket to make
sure it is compatible with all the bugs in interpretation and
implementation. Complexity++, and performance probably suffers.
None of these are particularly palatable, which is why threading
proposals get a lot of pushback.
At the end of the day, if this is only providing value for a subset of
use cases, involving peculiar-ish conditions, well, it's quite likely
wiser for most would-be implementors to spend their time on improvements
likely to help a larger set of users that might, in fact, include those
that imagine that this parallelization would be helpful.
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