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 grepl(paste0("^",pattern),df$Strings) subset(df, grepl(paste0("^",pattern), df$Strings)) - lookup(pattern,df) is not what I am looking for since it is doing an exact matching - I tried to convert my data frame in a data table but it didn't improve things (probably read/write of this DT will be much faster) - the only way I found was to remove 1/3 of the data frame with the strings of lowest frequency which speed up the process by a factor x10 ! - didn't try yet parRapply and with a machine with multicore I can get another factor. I did use parLapply for some other code but I had many issue with memory (crashing my Mac). I had to sub-divide the dataset to have it working correctly but I didn't manage to fully understand the issue. I am sure their is some other smart way to do that. Any good article/blogs or suggestion that can give me some guidance ?
Didn't you post the same question yesterday? Perhaps nobody answered because your question is unanswerable. You need to describe what the strings are like and what the patterns are like if you want advice on speeding things up.
Duncan Murdoch ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
