1.样例类实现自定义排序,需要实现ordered特质,不需要实现serializable,不需要new对象
2.普通类实现自定义排序,需要实现ordered特质,实现serializable(本文普通类)
姓名name 年龄age 颜值fv
文本为Array(“mimi1 22 86”, “mimi2 22 86”, “mimi3 23 87”)
按照颜值降序、年龄降序排列
import org.apache.spark.rdd.RDD
import org.apache.spark.{
SparkConf, SparkContext}
object CustomSort_1 {
def main(args: Array[String]): Unit = {
val conf = new SparkConf()
conf.setAppName(this.getClass.getName).setMaster("local[2]")
val sc: SparkContext = new SparkContext(conf)
val userInfo: RDD[String] = sc.parallelize(Array"mimi1 22 86", "mimi2 22 86", "mimi3 23 87"))
//对文本进行拆分,并返回一个person1对象
val personRDD: RDD[person1] = userInfo.map(x => {
val arr = x.split(" ")
val name = arr(0)
val age = arr(1).toInt
val fv = arr(2).toInt
new person1(name, age, fv)
})
//指定排序规则x=>x既按照person1的compare进行排序
val sorted: RDD[person1] = personRDD.sortBy(x => x)
println(sorted.collect.toBuffer)
}
}
//普通类实现自定义排序,需要实现ordered特质,实现serializable
// 样例类实现自定义排序,需要实现ordered特质,不需要实现serializable,不需要new对象
//case class person1..... 使用时 person1(name, age, fv)
class person1(val name:String,val age:Int, val fv:Int) extends Serializable with Ordered[person1]{
override def compare(that: person1): Int = {
if(this.fv!=that.fv)
that.fv- this.fv
else that.age - this.age
}
override def toString: String = s"$name,$age,$fv"
}
运行结果
ArrayBuffer(mimi3,23,87, mimi1,22,86, mimi2,22,86)