Others may know more than I do, but roughly:
(1) SQL provides access to relational database management systems
that are much more robust and handle large-scale data;
(2) methods based on SQL will often handle data that are too large to
fit in memory
R complements SQL by providing a much larger set of statistical
tools. The typical workflow would be that you would use SQL queries to
do the extraction, subsetting, and simple manipulation of data to reduce
the data to a manageable size for analysis on a single machine, then use
R to analyze it.
See also various packages (arrow, dbplyr) that provide alternative
big-data workflows.
cheers
Ben Bolker
On 12/11/24 08:16, akshay kulkarni wrote:
dear Members,
I have recently started studying SQL and MySQL. My
question is, what exactly is SQL used for? That is, whatever can be done by
SQL, like subsetting and filtering of data sets, can also be done by R. What's,
then, the advantage of SQL? It is OK if you tag this question as offtopic, but
I could'nt find any info on the web. Can you please refer me to some online
resources that shed some light on this? Finally, how does SQL complement R? Are
both dependent?
THanking you,
Yours sincerely,
AKSHAY M KULKARNI
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