R: Painfully slow read performance using RODBC & SQL Server
I am new to R but am interested in using Shiny to create dynamic charts using data stored in a SQL Server database. To enable interactivity, I want to bring in the raw data from the database and perform calculations within R rather than have the database summarize the data.
I am able to connect to the database using RODBC, execute a query, and receive results in a data.frame. However, the read time in R is about 12x longer than than the same query executed in SQL Server Management Studio (SSMS). SSMS takes ~600 ms, whereas R takes about 7.6 seconds. My question is whether I am doing something wrong, or is R just really slow with database access? And if so, are there faster alternatives (e.g. writing the database output to a file and reading the file)?
Some information about the query that may help: The query retrieves about 250K rows with 4 columns. The first column is a date and the other three are numeric values. The machine running R and SSMS is a high-end Win 7 workstation with 32GB of memory. The R command that I am running is:
system.time(df <- sqlQuery(cn, query))
which returns:
user system elapsed
7.17 0.01 7.58
Interestingly, it appears that the data transfer from SQL to my machine is fast, but that R is busy doing things internally for several seconds before returning the data.frame. I see this because network utilization spikes in the first second and almost immediately returns to near 0. Then several seconds later, the R data.frame returns.
Answer
I would try RJDBC http://cran.r-project.org/web/packages/RJDBC/RJDBC.pdf
with these drivers https://msdn.microsoft.com/en-us/sqlserver/aa937724.aspx
library(RJDBC)
drv <- JDBC("com.microsoft.sqlserver.jdbc.SQLServerDriver","/sqljdbc4.jar")
con <- dbConnect(drv, "jdbc:sqlserver://server.location", "username", "password")
dbGetQuery(con, "select column_name from table")