Brandon,
note that the post was about RDS which is more efficient than all the options 
you list (in particular when not compressed). General advice is to avoid 
strings. Numeric vectors are several orders of magnitude faster than strings to 
load/save.
Cheers,
Simon


> On May 5, 2016, at 6:49 PM, Brandon Hurr <bhiv...@gmail.com> wrote:
> 
> You might be interested in the speed wars that are happening in the
> file reading/writing space currently.
> 
> Matt Dowle/Arun Srinivasan's data.table and Hadley Wickham/Wes
> McKinney's Feather have made huge speed advances in reading/writing
> large datasets from disks (mostly csv).
> 
> Data Table fread()/fwrite():
> https://github.com/Rdatatable/data.table
> https://stackoverflow.com/questions/35763574/fastest-way-to-read-in-100-000-dat-gz-files
> http://blog.h2o.ai/2016/04/fast-csv-writing-for-r/
> 
> 
> Feather read_feather()/write_feather()
> https://github.com/wesm/feather
> 
> I don't often have big datasets (10s of MBs) so I don't see the
> benefits of these much, but you might.
> 
> HTH,
> B
> 
> On Thu, May 5, 2016 at 3:16 PM, Charles DiMaggio
> <charles.dimag...@gmail.com> wrote:
>> Been a while, but wanted to close the page on a previous post describing R 
>> hanging on readRDS() and load() for largish (say 500MB or larger) files. 
>> Tried again with recent release (3.3.0).  Am able to read in large files 
>> under El Cap.  While the file is reading in, I get a disconcerting spinning 
>> pinwheel of death and a check under Force Quit reports R is not responding.  
>> But if I wait it out, it eventually reads in.  Odd.  But I can live with it.
>> 
>> Cheers
>> 
>> Charles
>> 
>> 
>> 
>> 
>> 
>> 
>> Charles DiMaggio, PhD, MPH
>> Professor of Surgery and Population Health
>> Director of Injury Research
>> Department of Surgery
>> New York University School of Medicine
>> 462 First Avenue, NBV 15
>> New York, NY 10016-9196
>> charles.dimag...@nyumc.org
>> Office: 212.263.3202
>> Mobile: 516.308.6426
>> 
>> 
>> 
>> 
>> 
>> 
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>> 
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