Tricks to manage the available memory in an R session

Question

What tricks do people use to manage the available memory of an interactive R session? I use the functions below [based on postings by Petr Pikal and David Hinds to the r-he

Answer 1

I use the data.table package. With its := operator you can :

• Add columns by reference
• Modify subsets of existing columns by reference, and by group by reference
• Delete columns by reference

None of these operations copy the (potentially large) data.table at all, not even once.

• Aggregation is also particularly fast because data.table uses much less working memory.

Related links :

• News from data.table, London R presentation, 2012
• When should I use the := operator in data.table?