skus<-Matrix(as.matrix(data.frame(
orderNum=sample(1000,10000,TRUE),
sku=sample(1000,10000,TRUE),
amount=runif(10000))),sparse=TRUE)
a<-aggregate.Matrix(skus[,'amount'],skus[,'sku',drop=FALSE])
m<-rsparsematrix(1000000,100,.001)
labels<-as.factor(sample(1e4,1e6,TRUE))
b<-aggregate.Matrix(m,labels)
## Not run:
# orders<-data.frame(orderNum=as.factor(sample(1e6, 1e7, TRUE)),
# sku=as.factor(sample(1e3, 1e7, TRUE)),
# customer=as.factor(sample(1e4,1e7,TRUE)),
# state = sample(letters, 1e7, TRUE), amount=runif(1e7))
# system.time(d<-aggregate.Matrix(orders[,'amount',drop=FALSE],orders$orderNum))
# system.time(e<-aggregate.Matrix(orders[,'amount',drop=FALSE],orders[,c('customer','state')]))
# ## End(Not run)
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