read_sf_dataset: Read an Arrow multi-file dataset and create 'sf' object
In sfarrow: Read/Write Simple Feature Objects ('sf') with 'Apache' 'Arrow'

Description Usage Arguments Details Value See Also Examples

Read an Arrow multi-file dataset and create sf object

1	read_sf_dataset(dataset, find_geom = FALSE)

`dataset`	a `Dataset` object created by `arrow::open_dataset` or an `arrow_dplyr_query`
`find_geom`	logical. Only needed when returning a subset of columns. Should all available geometry columns be selected and added to to the dataset query without being named? Default is `FALSE` to require geometry column(s) to be selected specifically.

This function is primarily for use after opening a dataset with arrow::open_dataset. Users can then query the arrow Dataset using dplyr methods such as filter or select. Passing the resulting query to this function will parse the datasets and create an sf object. The function expects consistent geographic metadata to be stored with the dataset in order to create sf objects.

object of class sf

open_dataset, st_read, st_read_parquet

# read spatial object
nc <- sf::st_read(system.file("shape/nc.shp", package="sf"), quiet = TRUE)

# create random grouping
nc$group <- sample(1:3, nrow(nc), replace = TRUE)

# use dplyr to group the dataset. %>% also allowed
nc_g <- dplyr::group_by(nc, group)

# write out to parquet datasets
tf <- tempfile()  # create temporary location
on.exit(unlink(tf))
# partitioning determined by dplyr 'group_vars'
write_sf_dataset(nc_g, path = tf)

list.files(tf, recursive = TRUE)

# open parquet files from dataset
ds <- arrow::open_dataset(tf)

# create a query. %>% also allowed
q <- dplyr::filter(ds, group == 1)

# read the dataset (piping syntax also works)
nc_d <- read_sf_dataset(dataset = q)

nc_d
plot(sf::st_geometry(nc_d))