Filters geometries based on a spatial relationship with another geometry, such as intersection, containment, or proximity.
Usage
ddbs_filter(
x,
y,
predicate = "intersects",
conn = NULL,
conn_x = NULL,
conn_y = NULL,
name = NULL,
crs = NULL,
crs_column = "crs_duckspatial",
distance = NULL,
mode = NULL,
overwrite = FALSE,
quiet = FALSE
)Arguments
- x
Input spatial data. Can be:
A
duckspatial_dfobject (lazy spatial data frame via dbplyr)An
sfobjectA
tbl_lazyfrom dbplyrA character string naming a table/view in
conn
Data is returned from this object.
- y
Input spatial data. Can be:
A
duckspatial_dfobject (lazy spatial data frame via dbplyr)An
sfobjectA
tbl_lazyfrom dbplyrA character string naming a table/view in
conn
- predicate
A geometry predicate function. Defaults to
intersects, a wrapper ofST_Intersects. See details for other options.- conn
A connection object to a DuckDB database. If
NULL, the function runs on a temporary DuckDB database.- conn_x
A
DBIConnectionobject to a DuckDB database for the inputx. IfNULL(default), it is resolved fromconnor extracted fromx.- conn_y
A
DBIConnectionobject to a DuckDB database for the inputy. IfNULL(default), it is resolved fromconnor extracted fromy.- name
A character string of length one specifying the name of the table, or a character string of length two specifying the schema and table names. If
NULL(the default), the function returns the result as ansfobject- crs
Deprecated The coordinates reference system of the data. Specify if the data doesn't have a
crs_column, and you know the CRS.- crs_column
Deprecated a character string of length one specifying the column storing the CRS (created automatically by
ddbs_write_vector). Set toNULLif absent.- distance
a numeric value specifying the distance for ST_DWithin. Units correspond to the coordinate system of the geometry (e.g. degrees or meters)
- mode
Character. Controls the return type. Options:
"duckspatial"(default): Lazy spatial data frame backed by dbplyr/DuckDB"sf": Eagerly collected sf object (uses memory)
Can be set globally via
ddbs_options(mode = "...")or per-function via this argument. Per-function overrides global setting.- overwrite
Boolean. whether to overwrite the existing table if it exists. Defaults to
FALSE. This argument is ignored whennameisNULL.- quiet
A logical value. If
TRUE, suppresses any informational messages. Defaults toFALSE.
Value
Depends on the mode argument (or global preference set by ddbs_options):
duckspatial(default): Aduckspatial_df(lazy spatial data frame) backed by dbplyr/DuckDB.sf: An eagerly collected object in R memory, that will return the same data type as thesfequivalent (e.g.sforunitsvector).
When name is provided, the result is also written as a table or view in DuckDB and the function returns TRUE (invisibly).
Details
Spatial Join Predicates:
A spatial predicate is really just a function that evaluates some spatial relation between two geometries and returns true or false, e.g., “does a contain b” or “is a within distance x of b”. Here is a quick overview of the most commonly used ones, taking two geometries a and b:
"ST_Intersects": Whether a intersects b"ST_Contains": Whether a contains b"ST_ContainsProperly": Whether a contains b without b touching a's boundary"ST_Within": Whether a is within b"ST_Overlaps": Whether a overlaps b"ST_Touches": Whether a touches b"ST_Equals": Whether a is equal to b"ST_Crosses": Whether a crosses b"ST_Covers": Whether a covers b"ST_CoveredBy": Whether a is covered by b"ST_DWithin": x) Whether a is within distance x of b
Examples
if (FALSE) { # \dontrun{
# RECOMMENDED: Efficient lazy workflow using ddbs_open_dataset
library(duckspatial)
# Load data directly as lazy spatial data frames (CRS auto-detected)
countries <- ddbs_open_dataset(
system.file("spatial/countries.geojson", package = "duckspatial")
)
argentina <- ddbs_open_dataset(
system.file("spatial/argentina.geojson", package = "duckspatial")
)
# Lazy filter - computation stays in DuckDB
neighbors <- ddbs_filter(countries, argentina, predicate = "touches")
# Collect to sf when needed
neighbors_sf <- dplyr::collect(neighbors) |> sf::st_as_sf()
# Alternative: using sf objects directly (legacy compatibility)
library(sf)
countries_sf <- st_read(system.file("spatial/countries.geojson", package = "duckspatial"))
argentina_sf <- st_read(system.file("spatial/argentina.geojson", package = "duckspatial"))
result <- ddbs_filter(countries_sf, argentina_sf, predicate = "touches")
# Alternative: using table names in a duckdb connection
conn <- ddbs_create_conn(dbdir = "memory")
ddbs_write_table(conn, countries_sf, "countries")
ddbs_write_table(conn, argentina_sf, "argentina")
ddbs_filter(conn = conn, "countries", "argentina", predicate = "touches")
} # }
