spark_read_shapefile {apache.sedona} | R Documentation |
Read geospatial data into a Spark DataFrame.
Description
Functions to read geospatial data from a variety of formats into Spark DataFrames.
-
spark_read_shapefile
: from a shapefile -
spark_read_geojson
: from a geojson file -
spark_read_geoparquet
: from a geoparquet file
Usage
spark_read_shapefile(sc, name = NULL, path = name, options = list(), ...)
spark_read_geojson(
sc,
name = NULL,
path = name,
options = list(),
repartition = 0,
memory = TRUE,
overwrite = TRUE
)
spark_read_geoparquet(
sc,
name = NULL,
path = name,
options = list(),
repartition = 0,
memory = TRUE,
overwrite = TRUE
)
Arguments
sc |
A |
name |
The name to assign to the newly generated table. |
path |
The path to the file. Needs to be accessible from the cluster. Supports the ‘"hdfs://"’, ‘"s3a://"’ and ‘"file://"’ protocols. |
options |
A list of strings with additional options. See https://spark.apache.org/docs/latest/sql-programming-guide.html. |
... |
Optional arguments; currently unused. |
repartition |
The number of partitions used to distribute the generated table. Use 0 (the default) to avoid partitioning. |
memory |
Boolean; should the data be loaded eagerly into memory? (That is, should the table be cached?) |
overwrite |
Boolean; overwrite the table with the given name if it already exists? |
Value
A tbl
See Also
Other Sedona DF data interface functions:
spark_write_geojson()
Examples
library(sparklyr)
library(apache.sedona)
sc <- spark_connect(master = "spark://HOST:PORT")
if (!inherits(sc, "test_connection")) {
input_location <- "/dev/null" # replace it with the path to your input file
rdd <- spark_read_shapefile(sc, location = input_location)
}