Azure ML Batch Run - Single Output

Question

I create an forecasting experiment using R engine. My data source is pivoted, hence I need to pass row by row. The output works great with single row prediction. But when I try to populate multiple lines, it still gives single row output - for the first record only.

I'm trying to loop my result as follows :

# Map 1-based optional input ports to variables
dataset1 <- maml.mapInputPort(1) # class: data.frame

library(forecast)
library(reshape)
library(dplyr)
library(zoo)
#exclude non required columns
my.ds <- dataset1[, -c(4,5,6)]
# set the CIs we want to use here, so we can reuse this vector
cis <- c(80, 95)

for (i in 1:nrow(my.ds)) {
my.start <- my.ds[i,c(3)]
my.product <- my.ds[i, "Product"]
my.location <- my.ds[i, "Location"]
my.result <- melt(my.ds[i,], id = c("Product","Location"))
my.ts <- ts(my.result$value, frequency=52, start=c(my.start,1))
# generate the forecast using those ci levels
f <- forecast(na.interp(my.ts), h=52, level=cis)
# make a data frame containing the forecast information, including the index
z <- as.data.frame(cbind(seq(1:52),
                       f$mean,
                       Reduce(cbind, lapply(seq_along(cis), function(i) cbind(f$lower[,i], f$upper[,i])))))
# give the columns better names
names(z) <- c("index", "mean", paste(rep(c("lower", "upper"), times = length(cis)), rep(cis, each = 2), sep = "."))
# manipulate the results as you describe
zw <- z %>%
# keep only the variable you want and its index
mutate(sssf = upper.95 - mean) %>%
select(index, mean, sssf) %>%
# add product and location info
mutate(product = my.product,
       location = my.location) %>%
# rearrange columns so it's easier to read
select(product, location, index, mean, sssf)
zw <- melt(zw, id.vars = c("product", "location", "index"), measure.vars = c("mean","sssf"))
data.set <- cast(zw, product + location ~ index + variable, value = "value")
# Select data.frame to be sent to the output Dataset port
maml.mapOutputPort("data.set");
}

This is design of my experiment :

And this is how sample input looks like :

I'm testing using the Excel test workbook downloaded from experiment site.

Answer 1

I figured out the problem :

{
...
ds <- cast(zw, product + location ~ index + variable, value = "value")
data.set <- rbind(data.set, ds)
}
# Select data.frame to be sent to the output Dataset port
maml.mapOutputPort("data.set");

I should be merging the rows and then output outside of the loop.