Dear JC,
THanks .....
THanking you,
Yours sincerely,
AKSHAY M KULKARNI
________________________________
From: R-help <r-help-boun...@r-project.org> on behalf of J C Nash
<profjcn...@gmail.com>
Sent: Wednesday, December 11, 2024 10:27 PM
To: r-help@r-project.org <r-help@r-project.org>
Subject: Re: [R] SQL and R - tangential
My late friend Morven Gentleman, not long after he stepped down from being chair
of Computer Science at Waterloo, said that it seemed computer scientists had to
create
a new computer language for every new problem they encountered.
If we could use least squares to measure this approximation, we'd likely be
suspicious
of a terribly small error measure or overly high R^2.
JN
On 2024-12-11 11:11, avi.e.gr...@gmail.com wrote:
> Akshay,
>
> Your question has way too many answers.
>
> SQL has a long history and early versions came long before R arrived on the
> scene. There is a huge embedded base of hardware and software dedicated to
> managing databases. It has some features that most R programs do not even
> dream of doing. Besides easily handling massive amounts of data or sometimes
> tweaking queries to possibly run more efficiently, there are all kinds of
> issue of how to manage multiple people accessing and changing the data at
> about the same time, or rolling the data back to an earlier checkpoint.
>
> R came along later and, as Ben pointed out, adds all kinds of things SQL
> does not have and likely does not need, or alternate ways to do things.
>
> For many people now, the workload is to use a programming language, and R is
> not the only one used, which has enhanced with packages or modules that
> allow access in a fairly general way to one or many databases running
> various versions of SQL. The programmer uses this API in many ways.
>
> In some ways, it is just a way to tell the database what to do without much
> other processing. You can ask to open a connection to the server, do a query
> that gets translated to SQL (or you can provide the actual SQL) and let the
> remote (or local) machine do much of the work. For example, imagine a
> database with terabytes of data and all you want is a few rows/columns that
> meet your query. In R, you might have to open a collection of huge CSV files
> and fill more memory than you have and do the query somehow. If the data is
> remote, we are talking about a huge receiving of data. Using SQL divides the
> work so you do parts here and parts there.
>
> Why use a local MYSQL? Part of the answer is that you have a fairly
> optimized and debugged system that does it well and lets the programmer
> focus on the parts they need to add within R like complex analyses. Part is
> portability, as you can later move the data outside your machine and with
> minor changes, your program should still work. And, there are many other
> scenarios such as wanting to gather data from different sources such as
> connecting to multiple remote databases and getting filtered data and doing
> an analysis across that data and perhaps updating them.
>
> R used in ways like this provides lots of flexibility. But part of the
> question is like asking why there are a hundred programming languages still
> in use out there. Why do we need so many? In short, we don't necessarily
> need all or even most of them but they are there because various people
> developed them and used them and it is not trivial to get people to switch
> and maybe abandon all the older software or try to rewrite it.
>
> Having said that, I think a large fraction of R users have never had any
> particular reason to learn SQL. Many have never used it directly or even
> indirectly. I know someone who I have programmed for who calls some expert
> to do a SQL query and save the results in CSV files and then works directly
> in R on those files. I have pointed out to them that their life could be
> even easier if they got a more focused dump of the SQL data with some of the
> added processing done in SQL and then a smaller amount of data coming into
> the R side.
>
> I also note that languages like R and python can have parts that run fairly
> slowly. Arguably, most versions of SQL have been tuned over decades ...
>
>
> -----Original Message-----
> From: R-help <r-help-boun...@r-project.org> On Behalf Of akshay kulkarni
> Sent: Wednesday, December 11, 2024 8:17 AM
> To: R help Mailing list <r-help@r-project.org>
> Subject: [R] SQL and R
>
> 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
SQL
> complement R? Are both dependent?
>
> THanking you,
> Yours sincerely,
> AKSHAY M KULKARNI
>
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