snow

I'm using the doSNOW package and more specifically the parLapply function to perform reclassification (and subsequently other operations) on a list of big raster datasets (OS: Windows x64). The code looks a little like this minimalistic example: library(raster) library(doSNOW) #create list containing test rasters x <- raster(ncol=10980,nrow=10980) x <- setValues(x,1:ncell(x)) list.x <- replicate( 9 , x ) #setting up cluster NumberOfCluster <- 8 cl <- makeCluster(NumberOfCluster) registerDoSNOW(cl) junk <- clusterEvalQ(cl,library(raster)) #perform calculations on each raster list.x <- parLapply

I'm using the snow package in R to execute a function on a SOCK cluster with multiple machines(3) running on Linux OS. I tried to run the code with both parLapply and clusterApply . In case of any error at the worker level, the results of the worker nodes are not returned properly to master making it very hard to debug. I'm currently logging every heartbeat of the worker nodes independently using futile.logger . It seems as if the results are properly computed. But when I tried to print the result at the master node (After receiving the output from workers) I get an error which says, Error in

The makeCluster function for the SNOW package has the different cluster types of " SOCK ", " PVM ", " MPI ", and " NWS " but I'm not very clear on the differences among them, and more specifically which would be best for my program. Currently I have a queue of tasks of different length going into a load balancing cluster with clusterApplyLB and am using a 64bit 32-core Windows machine. I am looking for a brief description of the differences among the four cluster types, which would be best for my use and why. Welcome to parallel programming. You may want to peruse the vignette of the excellent

Fairly new to Parallel R. Quick question. I have an algorithm that is computationally intensive. Fortunately it can easily be broken up into pieces to make use of multicore or snow . What I would like to know is if it is considered fine in practice to use multicore in conjunction with snow ? What I would like to do is split up my load to run on multiple machines in a cluster and for each machine. I would like to utilize all cores on the machine. For this type of processing, is it reasonable to mix snow with multicore ? I have used the approach suggested above by lockedoff, that is use the

可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 问题: I've written a function in Rcpp and compiled it with inline . Now, I want to run it in parallel on different cores, but I'm getting a strange error. Here's a minimal example, where the function funCPP1 can be compiled and runs well by itself, but cannot be called by snow 's clusterCall function. The function runs well as a single process, but gives the following error when ran in parallel: Error in checkForRemoteErrors(lapply(cl, recvResult)) : 2 nodes produced errors; first error: NULL value passed as symbol address And here is some code: #

可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 问题: I use Spark-shell to do the below operations Recently loaded a table with an array column in spark-sql . Here is the ddl for the same: create table test_emp_arr{ dept_id string, dept_nm string, emp_details Array } the data looks something like this +-------+-------+-------------------------------+ |dept_id|dept_nm| emp_details| +-------+-------+-------------------------------+ | 10|Finance|[Jon, Snow, Castle, Black, Ned]| | 20| IT| [Ned, is, no, more]| +-------+-------+-------------------------------+ i can query the emp_details column

Run git software asume that we need to delete the folder “snow/”, input the following codes git rm -r --cached snow/ git commit -m “snow” git push origin master then the folder “snow/” is deleted 来源：51CTO 作者： graceful snow 链接：https://blog.csdn.net/graceful_snow/article/details/100157061

swap 大小改变 假设当前系统swap大小为4GB，想增加swap大小为5GB。 步骤如下： 查看当前swap大小 free -h 增加1GBswap大小，假设文件路径及名称：/snow/swapfile， 执行下面命令 dd if=/dev/zero of=/snow/swapfile bs=1M count=1024 创建swap，创建成功后，该文件大小为1GB mkswap /snow/swapfile 激活swap /usr/sbin/swapon /snow/swapfile 设置swap安全权限为 600 chmod 600 /snow/swapfile 用free -h 命令去查看现在swap的大小已经更新成功 free -h 假设想改变回原来swap大小，执行下面命令 /usr/sbin/swapoff /snow/swapfile 再次用free-h去查看，发现swap的值已经变回原来的4GB swap 优化 文件 /proc/sys/vm/swappiness ， 里面的值代表和物理内存的比例。如果为20，表示物理内存用了 80%的时候才用SWAP空间 临时调整值的大小 - 假设调整该值为10执行下面命令 sysctl vm.swappiness=10 或者 echo 10 > /proc/sys/vm/swappiness 永久调整： vim /etc