I have several R visuals (R script visuals and custom R developer visuals) that throw an execution timeout error in Power BI Service. I am aware of the known limitations with R visuals (eg. 150,000 rows, 2MB, etc), but I don't think I am bumping into those limits. My scripts use the gstat package to interpolate data using ordinary kriging and I use either leaflet (custom R developer visual) or ggplot2 (R script visual) to display the results of the kriging spatially. When my input dataset increases from 179 rows to 289 rows, I get the execution timeout error. I should note that the visuals render in Power BI Desktop, but not in Service.
library(ggplot2)
library(sf)
library(dplyr)
library(gstat)
library(raster)
library(ggrepel)
library(sp)
crs <- "+init=epsg:2277"
dat <- dataset
# Rename coordinates to lat and lng for leaflet
dat <- dat %>%
rename(lat = x_coord,
lng = y_coord)
# Make spatial dataframe
coordinates(dat) <- ~lat+lng
proj4string(dat) <- CRS(crs)
dat <- dat[-sp::zerodist(dat)[,1],]
# Get extent of data
xb <- min(dat@coords[,1])
xe <- max(dat@coords[,1])
yb <- min(dat@coords[,2])
ye <- max(dat@coords[,2])
xn <- 10 # (xe - xb)/100
yn <- 10 # (ye - yb)/100
# Get number of points
n <- length(dat@coords[,1])
# Create grid and make spatial object
grid2D <- expand.grid(lat = seq(xb, xe, xn),
lng = seq(yb, ye, yn))
gridded(grid2D) <- ~lat+lng
sp::proj4string(grid2D) = CRS(crs)
# Create variogram using linear model
v <- variogram(midland_pcl_format ~ 1, dat)
v.fit <- vgm(1, 'Lin', 0)
# Krig the data
base <- gstat::krige(midland_pcl_format ~ 1, dat, grid2D, model = v.fit)
# Convert SpatialPixelsDataFrame to Raster
rpred <- raster(base)
limit1 <- 0.8
rpred[rpred <= limit1] <- NA
rppred <- projectRaster(rpred, crs = "+init=epsg:4326")
rpred_df <- as.data.frame(rppred, xy = TRUE)
ggplot () +
geom_raster(data = rpred_df, aes(x = x, y = y, fill = var1.pred)) +
scale_fill_continuous(na.value = "transparent") +
geom_point(
data = dat@Anonymous,
aes(x = longitude, y = latitude, color = as.factor(midland_pcl_format)),
size = 3
) +
scale_color_manual(values = c("0" = "#009292", "1" = "#fe6db6"))+
geom_text_repel(
data = dat@Anonymous,
aes(x = longitude, y = latitude, label = sys_loc_code),
family = "sans",
alpha = 0.7,
size = 3,
label.padding = 0.5
) +
ylab("")+
xlab("")+
theme(legend.position = "none") +
coord_quickmap()
