Not sure if you all will be able to help me without reproducible example data, but I have a problem with running the code below. I am attempting to use the multidplyr package, but it doesn't seem to find my columns. I am running the code below:
cl <- detectCores()
cl
models_prep <-
bookings_prep %>%
inner_join(pipeline_prep_, by = c("booking_type", "group")) %>%
crossing(biz_day) %>%
left_join(closed_pipeline, by = c("booking_type", "group")) %>%
select(-opportunity_forecast_category)
group1 <- rep(1:cl, length.out = nrow(models_prep))
models_prep1 <- bind_cols(tibble(group1), models_prep)
cluster <- new_cluster(cl)
cluster %>%
cluster_library("tidyr")
cluster %>%
cluster_library("purrr")
cluster %>%
cluster_library("plyr")
cluster %>%
cluster_library("dplyr")
cluster_copy(cluster, "rmf")
cluster_copy(cluster, "fc_xreg")
#cluster_assign(cluster, "rmf")
#cluster_copy(cluster,c("rmf","fc_xreg"))
by_group <- models_prep %>%
group_by(group) %>%
partition(cluster)
by_group1 <- models_prep1 %>%
group_by(group1) %>%
partition(cluster)
models <- by_group %>%
mutate(
xreg_arima = pmap(list(data = pipeline, h = 1,name = group, bookings = bookings, type = booking_type,
biz_day = biz_day, no_bookings = no_bookings,
sparse_pipeline = sparse_pipeline,
closed_forecast_cat = pipeline_amount, FUN = "fc_xreg"), rmf))
Everything runs up to models <- correctly, but it fails there saying it cannot find the object group. Here is what the by_group data frame looks like.
Sometimes arguments just need to be quoted, particularly in dplyr-ish situations.