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$Strings)
    subset(df, grepl(paste0("^",pattern), df$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 ?

Thanks a lot
Cheers
Fabien

Dr Fabien Tarrade

Quantitative Analyst/Developer - Data Scientist

Senior data analyst specialised in the modelling, processing and 
statistical treatment of data.
PhD in Physics, 10 years of experience as researcher at the forefront of 
international scientific research.
Fascinated by finance and data modelling.

Geneva, Switzerland

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