Viewing profile — arun_sriniv

No worries :-). And glad to hear you're working on it! Let me know if I can be of any help.

ajinkyakale, "harder to learn" doesn't expose the fact that data.table provides so many features that, for example, dplyr just doesn't. And in addition, it is fast and memory effic…

Unfortunately the datasets in that benchmark less than 3MB each in size - it fits entirely in cache. It doesn't give a good indication of how well the function/implementation scale…

@ajinkyakale, thanks. What'd be also interesting is to benchmark memory usage in addition to runtime.

data.table's `DT[i, j, by]` is quite consistent actually and is comparable to SQL's - i = where, j = select | update and by = group by. This form is always intact. For example: req…

Here's a benchmark Matt recently did comparing data.table, dplyr and pandas on 50GB and 100GB: https://github.com/Rdatatable/data.table/wiki/Benchmarks-%3A...

We're in the process of adding more detailed vignettes illustrating more clearly the philosophy behind data.table's `i, j, by`. Should make things lot easier for beginners - https:…