sedona_knn_query: Query the k nearest spatial objects.
In r-spark/sparklyr.sedona: Sparklyr Extension for Apache Sedona

Description Usage Arguments See Also Examples

Given a spatial RDD, a query object x, and an integer k, find the k nearest spatial objects within the RDD from x (distance between x and another geometrical object will be measured by the minimum possible length of any line segment connecting those 2 objects).

sedona_knn_query(
  rdd,
  x,
  k,
  index_type = c("quadtree", "rtree"),
  result_type = c("rdd", "sdf", "raw")
)

`rdd`	A Sedona spatial RDD.
`x`	The query object.
`k`	Number of nearest spatail objects to return.
`index_type`	Index to use to facilitate the KNN query. If NULL, then do not build any additional spatial index on top of `x`. Supported index types are "quadtree" and "rtree".
`result_type`	Type of result to return. If "rdd" (default), then the k nearest objects will be returned in a Sedona spatial RDD. If "sdf", then a Spark dataframe containing the k nearest objects will be returned. If "raw", then a list of k nearest objects will be returned. Each element within this list will be a JVM object of type `org.locationtech.jts.geom.Geometry`.

Other Sedona spatial query: sedona_range_query()

library(sparklyr)
library(sparklyr.sedona)

sc <- spark_connect(master = "spark://HOST:PORT")

if (!inherits(sc, "test_connection")) {
  knn_query_pt_x <- -84.01
  knn_query_pt_y <- 34.01
  knn_query_pt_tbl <- DBI::dbGetQuery(
    sc,
    sprintf(
      "SELECT ST_GeomFromText(\"POINT(%f %f)\") AS `pt`",
      knn_query_pt_x,
      knn_query_pt_y
    )
  )
  knn_query_pt <- knn_query_pt_tbl$pt[[1]]
  input_location <- system.file(
    file.path("extdata", "polygon.json"), package = "sparklyr.sedona"
  )
  rdd <- sedona_read_geojson_to_typed_rdd(
    sc,
    location = input_location,
    type = "polygon"
  )
  knn_result_sdf <- sedona_knn_query(
    rdd, x = knn_query_pt, k = 3, index_type = "rtree", result_type = "sdf"
  )
}