The good old iterator approach always gets us there ... eventually :)
Thanks for the suggestion. We'll start with that and if it turns out
to be too slow we can rethink our data structure.
No chance of defining a "view" of a table (like you can in a
relational database)?
Brad
On Fri, Aug 13, 2010 at 1:34 PM, Francesc Alted <fal...@pytables.org> wrote:
> 2010/8/13, Brad Buran <bbu...@cns.nyu.edu>:
>> We structure our data collection in such a way that information is
>> stored in several HDF5 files (one for each set of experiments).
>> Within each HDF5 file, we store data from multiple, related
>> experiments. Each experiment has its own node in the HDF5 file, with
>> each node containing a table of data (along with several arrays,
>> attributes, etc.). The table under each experiment node is identical
>> in structure. Is there a simple way to construct a query that
>> traverses across the table in each node (and each file)?
>
> You mean something similar to:
>
> results = []
> for table in h5file.walkNodes("/", "Table"):
> results.append([row['col'] for row in table.where('ID=%d' % your_ID)
>
> ? (this for all tables in a file; generalizing to multiple files is
> left as an exercise to the reader ;-)
>
> Tell us if this is not what you are after.
>
> --
> Francesc Alted
>
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