私はこのチュートリアルを行ってきました: https://databricks.com/notebooks/geomesa-h3-notebook.html
ポリゴン関数 (polygonToH3) は完全に機能しますが、マルチ ポリゴン関数では奇妙な結果が得られます。数百万の H3 インデックスを期待していましたが、少なくとも 10,000 km2 の領域に対して数百のインデックスしか生成しませんでした
val multiPolygonToH3 = udf{ (geometry: Geometry, resolution: Int) =>
var points: List[GeoCoord] = List()
var holes: List[java.util.List[GeoCoord]] = List()
if (geometry.getGeometryType == "MultiPolygon") {
val numGeometries = geometry.getNumGeometries()
if (numGeometries > 0) {
points = List(
geometry
.getGeometryN(0)
.getCoordinates()
.toList
.map(coord => new GeoCoord(coord.y, coord.x)): _* )
}
if (numGeometries > 1) {
holes = (1 to (numGeometries - 1)).toList.map(n => {
List(
geometry
.getGeometryN(n)
.getCoordinates()
.toList
.map(coord => new GeoCoord(coord.y, coord.x)): _*).asJava
})
}
}
H3.instance.polyfill(points, holes.asJava, resolution).toList
}
This is the code that calls the above function:
def ConvertMultiPolyH3(iLGA:Int) : Boolean = {
var batch_start = System.currentTimeMillis()
val res = 12
var sSQL = s"""SELECT * from tca_test_dl.lga
WHERE lga_wkt is not null and lga_id = $iLGA and GeometryType = 'MultiPolygon'""".stripMargin
val dfLGA = sparkSession.sql(sSQL)
val wktdfLGA = dfLGA.withColumn("lga_geom", st_geomFromWKT(col("lga_wkt")))
.withColumn("lga_id", col("lga_id").cast(LongType))
.withColumn("state_id", col("state_id").cast(LongType)).cache
val dfLGA_H3 = wktdfLGA.withColumn("h3_index", multiPolygonToH3(col("lga_geom"),lit(res))).withColumn("h3_index", explode($"h3_index"))
dfLGA_H3.printSchema()
val dfLGA_New = dfLGA_H3.drop("lga_wkt", "lga_geom")
//dfLGA_New.write.mode("append").format("delta").partitionBy("lga_id").save("/mnt/cont-tca-test/delta_lake/lga_h3")
println(dfLGA_New.count())
var batch_time = (System.currentTimeMillis() - batch_start)/1000.0/60.0
batch_time = BigDecimal(batch_time).setScale(2, BigDecimal.RoundingMode.HALF_UP).toDouble
println(s"LGA H3 conversion for LGA: $iLGA has been processed in $batch_time minutes")
dfLGA.unpersist()
wktdfLGA.unpersist()
dfLGA_H3.unpersist()
dfLGA_New.unpersist()
val result = true
return result
}