1 / 8

NcML Aggregation vs Feature Collections

NcML Aggregation vs Feature Collections. NcML functionality. Modify the objects found in CDM files Especially Attributes Don’t have to rewrite the files, esp on the server Make modest changes “by hand” Alternative to ncgen , ncdump CDL in XML Aggregations

gwen
Download Presentation

NcML Aggregation vs Feature Collections

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. NcML Aggregation vsFeature Collections

  2. NcML functionality • Modify the objects found in CDM files • Especially Attributes • Don’t have to rewrite the files, esp on the server • Make modest changes “by hand” • Alternative to ncgen, ncdump • CDL in XML • Aggregations • Creating logical datasets out of file collections

  3. NcML Aggregations • union • Logical union of objects inside multiple files • joinNew • Each file contains one slice – add new dimension • joinExisting • Concat existing multidim arrays together • tiled (never released) • Stitch horizontal tiles together • FMRC (deprecated as of 4.2)

  4. NcML Aggregations • Syntactic aggregation • Manipulating multidimensional arrays • Doesn’t know what the data means • High homogeneity requirements • Files must be identical, except for certain things • Difficult for Users to understand or to track • Assemble at runtime • Inefficient for large collections • Caching strategies cause trouble for dynamic datasets

  5. Feature Collections • Feature Types • Coverage: grid, swath, FMRC, ugrid*, image* • Discrete: point, station, profile, etc • Radial • Understands more of the dataset semantics • Mostly about the coordinate systems • Can “do the right thing” without user • Handle more inhomogeneity in the files * Coming soon

  6. Application Scientific Feature Types Datatype Adapter NetCDF-Java/ CDM architecture NetcdfDataset CoordSystem Builder NetcdfFile THREDDS I/O service provider Catalog.xml OPeNDAP NetCDF-3 NIDS NetCDF-4 GRIB NcML HDF5 GINI Nexrad DMSP

  7. What do you need to know? • NcML aggregation works and is stable code • Must know how your collection of files varies • Use it for simple cases • Feature Collections are still work in progress • Much easier to work with • All future development is here • You have our attention • Details tommorrow • If you have GRIB files • You want to use GRIB feature collections (4.3)

  8. Good Luck!

More Related