Changes between Version 66 and Version 67 of udg/ecoms/RPackage/examples


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Timestamp:
May 15, 2015 2:13:29 PM (7 years ago)
Author:
juaco
Comment:

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  • udg/ecoms/RPackage/examples

    v66 v67  
    771. '''Object size''': Requesting too large objects may deplete the available memory. Currently R runs on 32- and 64-bit operating systems, and most 64-bit OSes (including Linux, Solaris, Windows and OS X) can run either 32- or 64-bit builds of R. The memory limits depends mainly on the build, but for a 32-bit build of R on Windows they also depend on the underlying OS version. For more details, type in the R console `help("Memory-limits")`
    882. '''Loading time''': The time spent in a request does not depend exclusively on the size of the object to be loaded, but also largely depends on the characteristics of the internet connection and the ECOMS-UDG traffic load at the moment of accessing the data. Thus, if the data request takes too long, we strongly advice to simplify the requested dataset and try to divide the job into smaller queries. Also note that the first request after logging-in into ECOMS runs slower. This is due to some information that is stored in the cache memory after the first data request, notably improving the performance subsequently.
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     11In the particular case of global domain selections (`lonLim` and `latLim` arguments set to `NULL`) for forecast data, it is recommended that only single-member, single-year selections are performed, due to the large size of this type of requests. Note that this is just an approximate recommendation. Object sizes also depend on the spatial resolution (CFS has approximately 1º horizontal res., while System4 is 0.75º and WFDEI 0.5º). Similarly, while GCM data will normally return data for the whole Earth (including oceans) for most variables, many observational datasets (like WFDEI) provide only data for land areas. In addition, It is always advisable to temporally aggregate to the maximum level possible. To this aim, it is possible to aggregate monthly using the argument `aggr.m` to specify a monthly aggregation function (see [./bias EXAMPLE 3]), which dramatically reduces the size of the data, allowing for large global domain data requests. Type `help("loadECOMS")` for details on time aggregation options.
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    1014== Basic loading examples
     
    1923}}}
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    21 In the particular case of global domain selections (`lonLim` and `latLim` arguments set to `NULL`) for forecast data, it is recommended that only single-member, single-year selections are performed, due to the large size of this type of requests. Note that this is just an approximate recommendation. Object sizes also depend on the spatial resolution (CFS has approximately 1º horizontal res., while System4 is 0.75º and WFDEI 0.5º). Similarly, while GCM data will normally return data for the whole Earth (including oceans) for most variables, many observational datasets (like WFDEI) provide only data for land areas. In addition, It is always advisable to temporally aggregate to the maximum level possible. To this aim, it is possible to aggregate monthly using the argument `time = "MM"`, which dramatically reduces the size of the data, allowing for large global domain data requests (type help("loadECOMS") for details).
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    2426== Additional examples