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On Apr 25, 2011, at 3:42 PM, John Caron wrote: > On 4/25/2011 1:37 PM, Roy Mendelssohn wrote: >> yes, internal compression. All the files were made from netcdf3 files using >> NCO with the options: >> >> ncks -4 -L 1 >> >> The results so far show a decrease in file size from 40% of original to >> 1/100 th of the original file size. If the internally compressed data >> requests are cached differently than request to netcdf3 files, we want to >> take that into account when we do the tests, so that we do not just see the >> affect of differential cacheing. >> >> When we have done tests on just local files, the reads where about 8 times >> slower from a compressed file. But Rich Signell has found that the >> combination of serialization/bandwidth is the bottleneck, and you hardly >> notice the difference in a remote access situation. That is what we want to >> find out, because we run on very little money and with compression as >> mentioned above our RAIDS would go a lot farther, as long the hit to the >> access time is not too great. >> >> Thanks, >> >> -Roy > > in netcdf4/hdf5, compression is tied to the chunking. Each chunk is > individually compressed, and must be completely decompressed to retrieve even > one value from that chunk. So the trick is to make your chunks correspond to > your "common cases" of data access. If thats possible, you should find that > compressed access is faster than non-compressed access, because IO is > smaller. but it will be highly dependent on that. John, is there a loss of efficiency when compressing chunks compared to compressing the entire file? I vaguely recall that for some compression algorithms, compression efficiency is a function of the volume of data compressed. Peter > >> >> >> >> On Apr 25, 2011, at 12:28 PM, John Caron wrote: >> >>> On 4/25/2011 11:30 AM, Roy Mendelssohn wrote: >>>> Hi All: >>>> >>>> We just converted one or our larger datasets (larger in terms of the >>>> number of files that are aggregated) into compressed netCDF4. There is a >>>> substantial savings in storage, but we wanted to do a series of tests to >>>> see what hit in access time we would take, if any, wsince many of our >>>> users will make requests involving a lot of time periods. >>>> >>>> In order to design these tests properly, we need to get a better >>>> understanding of how the TDS handles netcdf4 datasets that have >>>> compression. Are the decompressed data cached, or more accurately cached >>>> any differently from data read from an uncompressed series of netcdf3 >>>> files, or since the decompression is handled automatically on the read, is >>>> everything handled the same after that? >>>> >>>> We would also be interested other peoples experience with compressed >>>> netcdf4 files in TDS, in particular when the extracts are not synoptic, >>>> but cover a lot of time periods in a region, or make a lot of very small >>>> calls to a large number of time periods - such as we need to do for >>>> tagging data. >>>> >>>> Thanks for any info, >>>> >>>> -Roy >>> Hi Roy: >>> >>> I assume you mean internally compressed, not externally (like zipping up a >>> file) ? >>> >>> _______________________________________________ >>> thredds mailing list >>> thredds@xxxxxxxxxxxxxxxx >>> For list information or to unsubscribe, visit: >>> http://www.unidata.ucar.edu/mailing_lists/ >> ********************** >> "The contents of this message do not reflect any position of the U.S. >> Government or NOAA." >> ********************** >> Roy Mendelssohn >> Supervisory Operations Research Analyst >> NOAA/NMFS >> Environmental Research Division >> Southwest Fisheries Science Center >> 1352 Lighthouse Avenue >> Pacific Grove, CA 93950-2097 >> >> e-mail: Roy.Mendelssohn@xxxxxxxx (Note new e-mail address) >> voice: (831)-648-9029 >> fax: (831)-648-8440 >> www: http://www.pfeg.noaa.gov/ >> >> "Old age and treachery will overcome youth and skill." >> "From those who have been given much, much will be expected" > > _______________________________________________ > thredds mailing list > thredds@xxxxxxxxxxxxxxxx > For list information or to unsubscribe, visit: > http://www.unidata.ucar.edu/mailing_lists/ -- Peter Cornillon 215 South Ferry Road Telephone: (401) 874-6283 Graduate School of Oceanography Fax: (401) 874-6283 University of Rhode Island Internet: pcornillon@xxxxxxxxxxx Narragansett, RI 02882 USA
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