26.10.2017 18:40, Ger van Diepen пишет:
A choice consideration might be that the number of attributes has a limit.
Hmm, do I understand correctly that this limit is different for a group
and (an empty) dataset?
Best wishes,
Andrey Paramonov
I think HDF5 should support empty N-dim datasets. Being empty also
conveys information.
Note that in any language it would be strange if you could not have an
empty sequence.
Ger
Gerd Heber <[email protected]> 10/26/17 2:27 PM >>>
Andrey, the experts should chime in on the storage trade-offs.
(I imagine the null dataset is stored with compact layout, but in
newer versions of the file format an empty group is very "compact"
as well.) At the conceptual level, the two are very different and
that might tip the balance in either direction.
A group leaves the door open for other descendants.
A dataset is a terminal node and, despite being empty, is nevertheless
typed. (A null dataset has an element type!) Of course, you could
"type" a group with additional attributes, but it would be a very
different kind of variable.
This might be a case where there're no right or wrong choices
as far as HDF5 is concerned, and users will have to decide what
makes it right for them.
Best, G.
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Hi Gerd!
26.10.2017 14:31, Gerd Heber пишет:
> Rafal, this might be a bug. However, if you don't intend to store data
> there's a cheaper and maybe less contorted option: You can create a
> dataset with a dataspace of class H5S_NULL.
> Think of that as a dataset whose dataspace is an empty set.
> (Likewise you'd use H5S_SCALAR for a singleton.)
A common desire is to store non-uniform sparse data in HDF5 (consider
XML attributes as example). I tend to use empty groups which only serve
as container of attributes. What do you think: would empty datasets
(H5S_NULL) with attributes be more efficient (introduce less overhead)?
Best wishes,
Andrey Paramonov
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