On 9/10/2012 3:14 PM, Ellyn Montgomery wrote:
Aggregation gurus-
Please help with how to aggregate files that may contain an
inconsistent list of variables. The files I want to use all contain
temperature and salinity time series, but some also have conductivity,
attenuation or other data. I'd like to include all the possible
variables in a single aggregation. Seems like if one file of 50 is
missing attenuation, that I have to exclude attenuation from the
aggregation, and just operate on the variables that are present in all
50.
Have any of you found a way to also include the other "possibly
present variables", or whether it's better to just make 1 joinExisting
time aggregation per variable. I heard that in FMRC aggregations
there was a way to specify a "protoDataset" (maybe not the right term)
and it fills in appropriately for any files with variables missing
from the prototype. I couldn't find a reference to this in the
documentation, but if it's possible, would this approach be
appropriate for the inconsistently present variables I'm trying to
aggregate?
Or maybe someone has a good reason to supply several files (one file
per variable aggregated) instead of one file with all the possible
variables aggregated.
I'm interested in the pros and cons of each approach. Thanks for your
help!
Ellyn
Ellyn,
What is the format of the data files you are trying to aggregate? Grib
versus NetCDF will make a difference, particularly if you have
transitioned to TDS4.3. In the meantime, here is a link to
documentation about protoDatasets and the aggregation of non-homogeneous
files:
http://www.unidata.ucar.edu/projects/THREDDS/tech/tds4.2/reference/collections/FeatureCollections.html
or, in 4.3:
http://www.unidata.ucar.edu/projects/THREDDS/tech/tds4.3/reference/collections/FeatureCollections.html
Regards,
Lansing
