On 5/30/16 9:05 PM, Kouhei Kaigai wrote:
Due to performance reason, location of each element must be deterministic
without walking on the data structure. This approach guarantees we can
reach individual element with 2 steps.


Agreed.

On various other points...

Yes, please keep the discussion here, even when it relates only to PL/R. Whatever is being done for R needs to be done for plpython as well. I've looked at ways to improve analytics in plpython related to this, and it looks like I need to take a look at the fast-path function stuff. One of the things I've pondered for storing ndarrays in Postgres is how to reduce or eliminate the need to copy data from one memory region to another. It would be nice if there was a way to take memory that was allocated by one manager (ie: python's) and transfer ownership of that memory directly to Postgres without having to copy everything. Obviously you'd want to go the other way as well. IIRC cython's memory manager is the same as palloc in regard to very large allocations basically being ignored completely, so this should be possible in that case.

One thing I don't understand is why this type needs to be limited to 1 or 2 dimensions? Isn't the important thing how many individual elements you can fit into GPU? So if you can fit a 1024x1024, you could also fit a 100x100x100, a 32x32x32x32, etc. At low enough values maybe that stops making sense, but I don't see why there needs to be an artificial limit. I think what's important for something like kNN is that the storage is optimized for this, which I think means treating the highest dimension as if it was a list. I don't know if it then matters whither the lower dimensions are C style vs FORTRAN style. Other algorithms might want different storage.

Something else to consider is the 1G toast limit. I'm pretty sure that's why MADlib stores matricies as a table of vectors. I know for certain it's a problem they run into, because they've discussed it on their mailing list.

BTW, take a look at MADlib svec[1]... ISTM that's just a special case of what you're describing with entire grids being zero (or vice-versa). There might be some commonality there.

[1] https://madlib.incubator.apache.org/docs/v1.8/group__grp__svec.html
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Jim Nasby, Data Architect, Blue Treble Consulting, Austin TX
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