2016-12-08 16:11 GMT+09:00 Craig Ringer <cr...@2ndquadrant.com>:
> On 8 December 2016 at 12:01, Kohei KaiGai <kai...@kaigai.gr.jp> wrote:
>>> At a higher level, I don't understand exactly where such giant
>>> ExpandedObjects would come from. (As you point out, there's certainly
>>> no easy way for a client to ship over the data for one.) So this feels
>>> like a very small part of a useful solution, if indeed it's part of a
>>> useful solution at all, which is not obvious.
>> I expect an aggregate function that consumes millions of rows as source
>> of a large matrix larger than 1GB. Once it is formed to a variable, it is
>> easy to deliver as an argument of PL functions.
> You might be interested in how Java has historically dealt with similar
> For a long time the JVM had quite low limits on the maximum amount of
> RAM it could manage, in the single gigabytes for a long time. Even for
> the 64-bit JVM. Once those limitations were lifted, the garbage
> collector algorithm placed a low practical limit on how much RAM it
> could cope with effectively.
> If you were doing scientific computing with Java, lots of big
> image/video work, using GPGPUs, doing large scale caching, etc, this
> rapidly became a major pain point. So people introduced external
> memory mappings to Java, where objects could reference and manage
> memory outside the main JVM heap. The most well known is probably
> BigMemory (https://www.terracotta.org/products/bigmemory), but there
> are many others. They exposed this via small opaque handle objects
> that you used to interact with the external memory store via library
> It might make a lot of sense to apply the same principle to
> PostgreSQL, since it's much less intrusive than true 64-bit VARLENA.
> Rather than extending all of PostgreSQL to handle special-case
> split-up VARLENA extended objects, have your interim representation be
> a simple opaque value that points to externally mapped memory. Your
> operators for the type, etc, know how to work with it. You probably
> don't need a full suite of normal operators, you'll be interacting
> with the data in a limited set of ways.
> The main issue would presumably be one of resource management, since
> we currently assume we can just copy a Datum around without telling
> anybody about it or doing any special management. You'd need to know
> when to clobber your external segment, when to copy(!) it if
> necessary, etc. This probably makes sense for working with GPGPUs
> anyway, since they like dealing with big contiguous chunks of memory
> (or used to, may have improved?).
> It sounds like only code specifically intended to work with the
> oversized type should be doing much with it except passing it around
> as an opaque handle, right?
Thanks for your proposition. Its characteristics looks like a largeobject
but volatile (because of no backing storage).
As you mentioned, I also think its resource management is the core of issues.
We have no reference count mechanism, so it is uncertain when we should
release the orphan memory chunk, or we have to accept this memory consumption
until clean-up of the relevant memory context.
Moreever, we have to pay attention to the scenario when this opaque identifier
is delivered to the background worker, thus, it needs to be valid on other
process's context. (Or, prohibit to exchange it on the planner stage?)
> Do you need to serialize this type to/from disk at all? Or just
> exchange it in chunks with a client? If you do need to, can you
> possibly do TOAST-like or pg_largeobject-like storage where you split
> it up for on disk storage then reassemble for use?
Even though I don't expect this big chunk is entirely exported to/imported
from the client at once, it makes sense to save/load this big chunk to/from
the disk, because construction of a big memory structure consumes much CPU
cycles than simple memory copy from buffers.
So, in other words, it does not need valid typinput/typoutput handlers, but
serialization/deserialization on disk i/o is helpful.
KaiGai Kohei <kai...@kaigai.gr.jp>
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