knitr::opts_chunk$set( collapse = TRUE, comment = "#>" )
An important part of sparklyr.sedona
is its collection of R interfaces to Sedona visualization routines.
For example, the following
is essentially the R equivalent of this example in Scala.
library(sparklyr) library(sparklyr.sedona) sc <- spark_connect(master = "local") resolution_x <- 1000 resolution_y <- 600 boundary <- c(-126.790180, -64.630926, 24.863836, 50.000) pt_rdd <- sedona_read_dsv_to_typed_rdd( sc, location = "arealm.csv", type = "point" ) polygon_rdd <- sedona_read_dsv_to_typed_rdd( sc, location = "primaryroads-polygon.csv", type = "polygon" ) pair_rdd <- sedona_spatial_join_count_by_key( pt_rdd, polygon_rdd, join_type = "intersect" ) overlay <- sedona_render_scatter_plot( polygon_rdd, resolution_x, resolution_y, output_location = tempfile("scatter-plot-"), boundary = boundary, base_color = c(255, 0, 0), browse = FALSE ) sedona_render_choropleth_map( pair_rdd, resolution_x, resolution_y, output_location = "/tmp/choropleth-map", boundary = boundary, overlay = overlay, # vary the green color channel according to relative magnitudes of data points so # that the resulting map will show light blue, light purple, and light gray pixels color_of_variation = "green", base_color = c(225, 225, 255) )
It will create a scatter plot, and then overlay it on top of a choropleth map, as shown below:
See ?sparklyr.sedona::sedona_render_scatter_plot
, ?sparklyr.sedona::sedona_render_heatmap
,
and ?sparklyr.sedona::sedona_render_choropleth_map
for more details on visualization-related
R interfaces currently implemented by sparklyr.sedona
.
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