7. GeoMesa数据读取篇之本地文件读取

//读取shapefile
    def read_shapefile(shapePath: String, shapeName: String)(implicit sparkContext: SparkContext) = {
        var intpuParams: Map[String, String] = Map()
        var File = new File(shapePath)
        intpuParams += ("url" -> File.toURI.toURL.toString)
        intpuParams += ("geotools" -> "true")
        val query = new Query(shapeName)
        val inputRdd = GeoMesaSpark(intpuParams).rdd(new Configuration(), sparkContext, intpuParams, query)
        println(inputRdd.schema) //打印方案

        inputRdd
    }

val shapePath: String = "D:\\jb\\gisdata"
    val shapeFile: String = "dltsb_6603"

    val shapeOutPath: String = "D:\\jb\\output"

    def main(args: Array[String]): Unit = {
        implicit val sparkContext: SparkContext = SparkUtilsScala.createSparkContext()

        //读取shapefile 单文件
        //val shapeRdd: SpatialRDD = HandleShapeFile.read_shapefile(shapePath, shapeFile)

        //读取shapefile 路径
        val shapeRdd = HandleShapeFile.read_shapePath("D:\\B工作文档\\三调共享 流入流出\\jb\\output\\local-1630396725278");
        val length: Int = shapeRdd.collect().length

        //保持输出shapefile
        HandleShapeFile.write_shapefile_single(shapeRdd, shapeOutPath)

        sparkContext.stop();
    }

//测试失败，必须指定具体shapefile 文件名称，否则读取失败
    //新的思路：可以通过便利文件路径，获取所有shapefile 文件，分别读取为rdd，然后合并rdd
    def read_shapePath(shapePath: String)(implicit sparkContext: SparkContext) = {
        var intpuParams: Map[String, String] = Map()

        var File = new File(shapePath)
        intpuParams += ("url" -> File.toURI.toURL.toString)
        intpuParams += ("geotools" -> "true")
        val query = new Query("a1ee03b5-b289-4ea7-a7c2-33bd4984365c")

        val inputRdd = GeoMesaSpark(intpuParams).rdd(new Configuration(), sparkContext, intpuParams, query)
        println(inputRdd.schema) //打印方案

        inputRdd
    }