Attempting to use multiple ODBC connections across parallelized worker threads may fail as in the following example:
loaddata <- function(cn){result <- sqlQuery(cn,'select * from boston')return(head(result))}library(RODBC)cn1 <- odbcConnect("RevoTestDB", uid='RevoTester', pwd='RevoTester')cn2 <- odbcConnect("RevoTestDB", uid='RevoTester', pwd='RevoTester')cn3 <- odbcConnect("RevoTestDB", uid='RevoTester', pwd='RevoTester')cn4 <- odbcConnect("RevoTestDB", uid='RevoTester', pwd='RevoTester')rxSetComputeContext('localpar')system.time ({z <- rxExec(loaddata, rxElemArg(list(cn1,cn2,cn3,cn4)), packagesToLoad='RODBC')})Error in do.call(.rxDoParFUN, as.list(args)) :task 1 failed - "first argument is not an open RODBC channel"The problem is the worker processes receive the ODBC connections as closed.The issue here is that connections are process-specific, so unless the workers are sharing the parent process (as in multicore workers created via forking), the parent's connections can't be shared by the workers. To distribute ODBC computations on non-forked workers, establish the connections on each worker as part of the distributed task.Example:
loaddata <- function(){library(RODBC)cn <- odbcConnect("RevoTestDB", uid='RevoTester', pwd='RevoTester')result <- sqlQuery(cn,'select * from boston')return(head(result))}z <- system.time({z <- rxExec(loaddata,packagesToLoad='RODBC')})
