search for: parrappli

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2017 Sep 14
1
Print All Warnings that Occurr in All Parallel Nodes
Dear R Users, I have developed the following code for importing a series of zipped CSV by parallel computing. My problems are that: A) Some ZIP Files (Which contain CSVs inside) are corrupted, and cannot be opened. B) After executing parRapply I can only see the last.warning variable error, for knowing which CSV have failed in each node, but I cannot see all warnings, only 1 at a time. So: *
2020 May 18
1
parRapply and parCapply return a list in corner cases
According to ?parCapply: parRapply and parCapply always return a vector. This appears not to be the case in the following minimal reproducible example: > library(parallel) > nslaves <- 2 > cl <- makeCluster(nslaves) > X <- matrix(2,nrow=3,ncol=4) > X <- rbind(c(1,1,0,1),X) > tv <- parCapply(cl,X,FUN=function(x){ +
2012 Oct 23
0
Typos/omissions/inconsistencies in man page for clusterApply
Hi, Here are the issues I found: Typos ----- (a) Found: It a parallel version of ?evalq?, "is" missing. (b) Found: 'parLapplyLB', 'parSapplyLB' are load-balancing versions, intended for use when applying ?FUN? to 'parLapplyLB' has no 'FUN' arg (more on this below). (c) Found: 'clusterApply' calls 'fun' on the first
2016 Apr 10
2
what is the faster way to search for a pattern in a few million entries data frame ?
Hi there, I have a data frame DF with 40 millions strings and their frequency. I am searching for strings with a given pattern and I am trying to speed up this part of my code. I try many options but so far I am not satisfied. I tried: - grepl and subset are equivalent in term of processing time grepl(paste0("^",pattern),df$Strings) subset(df,
2016 Apr 09
0
fast way to search for a pattern in a few million entries data frame
Hi there, I have a data frame DF with 40 millions strings and their frequency. I am searching for strings with a given pattern and I am trying to speed up this part of my code. I try many options but so far I am not satisfied. I tried: - grepl and subset are equivalent in term of processing time grepl(paste0("^",pattern),df$Strings) subset(df,
2016 Apr 10
0
what is the faster way to search for a pattern in a few million entries data frame ?
On 10/04/2016 2:03 PM, Fabien Tarrade wrote: > Hi there, > > I have a data frame DF with 40 millions strings and their frequency. I > am searching for strings with a given pattern and I am trying to speed > up this part of my code. I try many options but so far I am not > satisfied. I tried: > - grepl and subset are equivalent in term of processing time >