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From Chris Nuernberger <ch...@techascent.com>
Subject Re: Plasma store implementation status across client libraries
Date Mon, 04 Jan 2021 16:58:23 GMT
Yes that makes sense.  I guess you also need something to broker shared
memory filenames/ids.  The database isn't in-memory, however, although I
know what you mean.  One huge advantage of mmap is you can have much larger
than memory storage act like in-memory storage; so the plasma store can be
roughly the size of your disk and larger your ram but your program, unless
it attempts to verbatim copy a column wouldn't know any better.

Numerical larger-than-memory-but-in-memory redis indeed; that is an
interesting way to think of it.

On Mon, Jan 4, 2021 at 9:45 AM Thomas Browne <thomas@crvm.io> wrote:

> Interesting and agreed. I guess this a big advantage of the "on the wire"
> unserialised format - just read it in and it's already native. I'll go this
> way possibly.
>
> However I also note the beginnings of more advanced functionality in the
> Plasma store, for example, notification API on buffer seal (ie when
> something changes, all clients can be notified).
>
>
> https://arrow.apache.org/docs/python/generated/pyarrow.plasma.PlasmaClient.html#pyarrow.plasma.PlasmaClient.subscribe
>
> I'm assuming the plasma store will add functionality over time, and if
> this is the case, having all client libraries implement it means I can
> almost have a redis-like column-store specialising in numerical computation
> (which would be awesome), and for which i don't need to write my own
> functionality for each client library.
>
> A numerical in-memory database, if you will.
> On 04/01/2021 15:55, Chris Nuernberger wrote:
>
> Julia, Python, and R all have some support for mmap operations.
>
> On Mon, Jan 4, 2021 at 8:55 AM Chris Nuernberger <chris@techascent.com>
> wrote:
>
>> Could simply saving the arrow file in streaming mode to shared memory and
>> then mmap-ing the result in each language solve your problem ?  Plasma
>> seems to me to be a layer on top of basic mmap operations; as long as you
>> have shared memory and mmap then you can have multiple processes talking to
>> the same logical block of memory.
>>
>> On Mon, Jan 4, 2021 at 8:27 AM Thomas Browne <thomas@crvm.io> wrote:
>>
>>> I am hoping to use the Apache Arrow project for cross-language numerical
>>> computation, and for that the shared-memory idea is very powerful. Am I
>>> correct that the Plasma Store is the enabling technology for this,
>>> especially for soft real-time computation (ie not moving to parquet or
>>> any file-based sharing system)?
>>>
>>> Is that the case? And if so, then I'm wondering which client libraries,
>>> other than Python (and I assume C[++]), implement the Plasma Store. This
>>> table doesn't feature a row for Plasma:
>>>
>>> https://arrow.apache.org/docs/status.html
>>>
>>> and I can't seem to find any reference to the Plasma store in the Julia,
>>> R, or Javascript libraries.
>>>
>>> https://arrow.apache.org/docs/r/
>>>
>>> https://arrow.apache.org/docs/js/
>>>
>>> https://arrow.juliadata.org/stable/
>>>
>>>
>>> Thank you,
>>>
>>> Thomas
>>>
>>>
>>>

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