>
> Well, I think that the HDF5 case is similar than the NetCDF for this
> scenario: if you need to efficiently retrieve measurements that are
> near in time, the best would be to save them in that order. However, in
> order to take advantage of this (disk-sorted) arrangement, you will
> need to build a map {table_indices} <--> {time_range} so as not having
> to walk the entire table in order to get the interesting time slice.
>
> A way to avoid having to build such a map by yourself is to use the
> indexing capabilities of PyTables Pro (in fact, this is what an index
> provides, a map between sorted values and indices for those values).
Great thanks - I had noticed benefits of PTP/indexing and will likely go this
direction if we end up using the API. It's a useful middle-ground feature in
the gap between a NetCDF archive and an online RDBMS/OLTP. Each having their
own uses of course.
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