snowfall-package(snowfall)
snowfall-package()所属R语言包：snowfall
Toplevel useability wrapper for snow to make parallel programming even more easy and comfortable. All functions are able to run without cluster in sequential mode. Also snowfall works as connector to the cluster management program sfCluster, but can also run without it.
雪使并行编程更容易和舒适的顶层使用性包装。无聚类在连续模式下，所有的功能都能够运行。降雪作品作为连接到聚类管理程序sfCluster的，但没有它也可以运行。
译者：生物统计家园网 机器人LoveR
描述----------Description----------
snowfall is designed to make setup and usage of snow more easier. It also is made ready to work together with sfCluster, a ressource management and runtime observation tool for R-cluster usage.
snowfall的目的是使snow更容易的设置和使用。这也是由愿共同努力与sfCluster，一个资源中管理和运行时观察R-聚类使用的工具。
Details
详细信息----------Details----------
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初始化----------Initialisation----------
Initalisation via sfInit must be called before the usage of any of the snowfall internal functions. sfStop stopps the current cluster. Some additional functions give access to build-in functions (like sfParallel, sfCpus etc.).
Initalisation通过sfInit之前，必须调用任何的snowfall内部功能的使用。 sfStop stopps当前的聚类。一些额外的功能，访问内置的函数（如sfParallel，sfCpus等）。
计算----------Calculations----------
The are plenty of function to execute parallel calculations via snowfall. Most of them are wrappers to the according snow functions, but there are additional functions as well. Most likely the parallel versions of the R-buildin applies are interesting: sfLapply, sfSapply and sfApply. For better cluster take a look at the load balanced sfClusterApplyLB and the function with restore possibilities: sfClusterApplySR.
有大量函数来执行并行计算通过snowfall。他们大多是根据snow功能的包装，但有附加功能。最有可能的并行版本的R-buildin适用的有趣：sfLapply，sfSapply和sfApply。为了更好地聚类的负载平衡来看看sfClusterApplyLB和功能恢复的可能性：sfClusterApplySR。
工具----------Tools----------
Various tools allow an easier access to parallel computing: sfLibrary and sfSource for loading code on the cluster, sfExport, sfExportAll, sfRemoveAll and sfRemoveAll for variable sperading on the cluster. And some more.
各种工具可以更容易地获得并行计算：sfLibrary和sfSource代码加载在聚类上，sfExport，sfExportAll，sfRemoveAll和sfRemoveAll 变量sperading聚类上的。更多一些。
sfCluster----------sfCluster----------
snowfall is also the R-connector to the cluster management program sfCluster. Mostly all of the communication to this tool is done implicit and directly affecting the initialisation via sfInit. Using sfCluster makes the parallel programming with snowfall even more practicable in real life environments.
snowfall是R-连接到聚类管理程序“sfCluster。大多是所有的通信这个工具是隐式和直接影响的初始化通过sfInit。使用sfCluster snowfall在现实生活环境中更可行的并行编程。
For futher informations about the usage of sfCluster look at its documentation.
如需进一步信息，sfCluster看看它的文档的使用。
（作者）----------Author(s)----------
Jochen Knaus
Maintainer:
Jochen Knaus <jo@imbi.uni-freiburg.de>,
参考文献----------References----------
<code>snow</code> (Simple Network of Workstations):<br> http://cran.r-project.org/src/contrib/Descriptions/snow.html<br><br>
<code>sfCluster</code> (Unix management tool for <code>snowfall</code> clusters):<br> http://www.imbi.uni-freiburg.de/parallel<br>
参见----------See Also----------
Snowfall Initialisation: snowfall-init<br> Snowfall Calculation: snowfall-calculation<br> Snowfall Tools: snowfall-tools<br>
降雪初始化：snowfall-init的<BR>降雪量的计算：snowfall-calculation的<BR>降雪工具：snowfall-tools参考
Optional links to other man pages, e.g. snow-cluster
可选链接到其他人的网页，例如snow-cluster
实例----------Examples----------
## Not run: [＃不运行：]
# Init Snowfall with settings from sfCluster[初始化降雪设置sfCluster]
##sfInit()[＃sfInit（）]
# Init Snowfall with explicit settings.[初始化降雪量有明确的设置。]
sfInit( parallel=TRUE, cpus=2 )
if( sfParallel() )
cat( "Running in parallel mode on", sfCpus(), "nodes.\n" )
else
cat( "Running in sequential mode.\n" )
# Define some global objects.[定义一些全局对象。]
globalVar1 <- c( "a", "b", "c" )
globalVar2 <- c( "d", "e" )
globalVar3 <- c( 1:10 )
globalNoExport <- "dummy"
# Define stupid little function.[定义愚蠢的小函数。]
calculate <- function( x ) {
cat( x )
return( 2 ^ x )
}
# Export all global objects except globalNoExport[导出所有全球除了globalNoExport对象]
# List of exported objects is listed.[被列为出口对象名单。]
# Work both parallel and sequential.[工作并行和顺序。]
sfExportAll( except=c( "globalNoExport" ) )
# List objects on each node.[每个节点列表对象。]
sfClusterEvalQ( ls() )
# Calc something with parallel sfLappy[钙与平行sfLappy的东西]
cat( unlist( sfLapply( globalVar3, calculate ) ) )
# Remove all variables from object.[从对象中删除所有的变量。]
sfRemoveAll( except=c( "calculate" ) )
## End(Not run)[＃（不执行）]
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注：
注1：为了方便大家学习，本文档为生物统计家园网机器人LoveR翻译而成，仅供个人R语言学习参考使用，生物统计家园保留版权。
注2：由于是机器人自动翻译，难免有不准确之处，使用时仔细对照中、英文内容进行反复理解，可以帮助R语言的学习。
注3：如遇到不准确之处，请在本贴的后面进行回帖，我们会逐渐进行修订。
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发表于 2012-9-30 11:05:39
