193、Spark 2.0之Dataset开发详解-typed操作：joinWith

和join的区别是连接后的新Dataset的schema会不一样

代码

object TypedOperation {

  case class Employee(name: String, age: Long, depId: Long, gender: String, salary: Long)

  case class Department(id: Long, name: String)

  def main(args: Array[String]): Unit = {
    val sparkSession = SparkSession
      .builder()
      .appName("BasicOperation")
      .master("local")
      .getOrCreate()

    import sparkSession.implicits._
    import org.apache.spark.sql.functions._

    val employeePath = this.getClass.getClassLoader.getResource("employee.json").getPath
    val departmentPath = this.getClass.getClassLoader.getResource("department.json").getPath

    val employeeDF = sparkSession.read.json(employeePath)
    val departmentDF = sparkSession.read.json(departmentPath)

    val employeeDS = employeeDF.as[Employee]
    val departmentDS = departmentDF.as[Department]

    employeeDS.joinWith(departmentDS, $"depId" === $"id").show()
  }
}