Memory Issue

I am running into a memory issue with drandomForest. I receive this message which we have all seen before: Error in drandomForest.default(m, y, ..., ntree = ntree, nExecutor = nExecutor, :
cannot allocate vector of size 7.9 Gb

function call:
tree.result <- drandomForest( Target~., data=as.data.frame(signalDF), mtry=predictors, nExecutor = 4)

Executing on a 64-bit machine with 32 Gb memory. # predictors = 64, and the the dataset contains ~ 4 million rows. The size of the data is slightly over 2GB. We are using the function in classification mode ( y is set as a factor). Predictors are a combination of numeric vars and factors.

Please advise. Thanks!

[afard]

I wonder why you have "mtry=predictors" in your function call. The default value of mtry in classification mode is floor(sqrt(ncol(x))) which would be 8 in your example.
Moreover, the default value of ntree is 500. I wonder if it makes sense for your use case to decrease the number of trees which should reduce the memory consumption.

mtry=predictors for a Bagging tree model.