SQL Queries from Multiple Servers

I use RODBC as my conduit from R to SQL. It works well when the tables are
stored on one channel, e.g.,

channel <- odbcConnect("data_base_01", uid="....", dsn="....")

However, I often need to match tables across multiple databases, e.g.,
"data_base_01" and "data_base_02". However, odbcConnect() appears limited
insofar as you may only query from tables within a single channel, e.g.,
database. I do not have access to write and create new tables on the SQL
servers, which is a possible solution (e.g., copy all tables into a single
database).

Is there any way, in RODBC or another R-friendly SQL package, to perform SQL
operations across multiple databases?

Sounds like you want... a SQL database engine.  Some engines provide
features to work with external tables... but it is not standardized and
it is not usually very efficient. You usually have to have some level of
admin privilege to do this.

Alternatively, you can create a new database using an engine of your
choice, move the data to that common working database, and do your
cross-queries to your heart's content. Depending on your working
environment, SQLite, MySQL, MS Jet, or MSDE could be options. Or, if your
joins are fairly small you can use R's merge function and doBy.
It seems a bit much to me to expect a database access library to
do double duty as a SQL database engine, though.

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I use RODBC as my conduit from R to SQL. It works well when the tables are
stored on one channel, e.g.,

channel <- odbcConnect("data_base_01", uid="....", dsn="....")

However, I often need to match tables across multiple databases, e.g.,
"data_base_01" and "data_base_02". However, odbcConnect() appears limited
insofar as you may only query from tables within a single channel, e.g.,
database. I do not have access to write and create new tables on the SQL
servers, which is a possible solution (e.g., copy all tables into a single
database).

Is there any way, in RODBC or another R-friendly SQL package, to perform SQL
operations across multiple databases?
  

I'm not sure if this can be done with odbc, but with MySQL it is 
possible to do joins across multiple databases, and creating temporary 
tables may be possible even without the write access you would need for 
a permanent table. I'm not sure if you can pass this kind of statement 
from R, because the connection usually specifies the database. However, 
I have constructed temporary tables with a simple mysql client and then 
queried them from R. They stay around as long as you don't quit the 
simple client.  I am not really sure this is suppose to work.  Another 
option is two connections and do some of the comparison in R, or write 
the results to an SQLite connection, on which you usually have write 
access. This might be slow  and you may have to deal with chunks if you 
have big tables.  Joins across databases are also possible with 
PostgreSQL, I'm told, but they are more difficult.

Paul

Warm regards.

  

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Hi.

Depending on your requirements, one option would be to do the join in
R using merge()

If you wish to run SQL joins across multiple databases, then it is not
an R problem but a database problem. For a quick solution, I would
write scripts that bring all your data together into one database
(could be written in any scripting language, and of course R) and then
process from there.

Bw

Mark

2009/5/13 Tom Schenk Jr <tomschenkjr at gmail.com>:

I use RODBC as my conduit from R to SQL. It works well when the tables are
stored on one channel, e.g.,

channel <- odbcConnect("data_base_01", uid="....", dsn="....")

However, I often need to match tables across multiple databases, e.g.,
"data_base_01" and "data_base_02". However, odbcConnect() appears limited
insofar as you may only query from tables within a single channel, e.g.,
database. I do not have access to write and create new tables on the SQL
servers, which is a possible solution (e.g., copy all tables into a single
database).

Is there any way, in RODBC or another R-friendly SQL package, to perform SQL
operations across multiple databases?

Warm regards.

--
Tom Schenk Jr.
tomschenkjr at gmail.com

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