第十三课：Scala模式匹配实战

模式匹配在很多地方都大量用到，一般会和case class结合起来使用，case class中的成员默认是不能变的

其实模式匹配看到它的语法，就是一个函数

 

package com.dt.spark.scala.basics

 

class DataFramework

case class ComputationFramework(name:String,popular:Boolean) extends DataFramework

case class StorageFramework(name:String,popular:Boolean) extends DataFramework

 

object HelloPatternMatch {

 

  def main(args:Array[String]) {

//    getSalary("Scala")

    getSalary("haha",6)

    getMatchType(10.0)

    getMatchCollection(Array("Scala","aaa","bbb"))

    /**

     * Scala会帮case class 自动生成伴生对象中的apply方法

     */

    getBigDataMatch(ComputationFramework("Spark",true))

    getBigDataMatch(StorageFramework("HDFS",true))

  }

 

  def getSalary(name:String,age:Int) {

    name match {

      case "Spark" => println("$150000/year")

      case "Hadoop" => println("$100000/year")

      case _ if name =="Scala" => println("$140000/year")

      case _ if name =="MapReduce" => println("$90000/year")

      case _name if age > 5 => println(_name+":"+age)

      case _ => println("$80000/year")

    }

  }

 

  def getMatchType(msg:Any){

    msg match {

      case i : Int => println("Int")

      case s : String => println("String")

      case d : Double => println("Double")

      case arr : Array[Any] => println("Array")

      case  _ => println("Unknown")

    }

  }

 

  def getMatchCollection(msg:Array[String]){

    msg match {

      case Array("Scala") => println("One Element")

      case Array("Scala","Java") => println("Two Element")

      case Array("Spark",_*) => println("Spark")

      case _ => println("Unknown")

    }

  }

 

  def getBigDataMatch(data:DataFramework) {

    data match {

      case ComputationFramework(name,popular) =>

        println(name+":"+popular)

      case StorageFramework(name,popular) =>

        println(name+":"+popular)

      case _ =>

        println("Unknown")

    }

  }

 

}

 

归纳总结：1.看笔记

package com.dt.spark.scala.basics

 

class DataFramework

case class ComputationFramework(name:String,popular:Boolean) extends DataFramework

case class StorageFramework(name:String,popular:Boolean) extends DataFramework

 

object HelloPatternMatch {

 

  def main(args:Array[String]) {

//    getSalary("Scala")

    getSalary("haha",6)

    getMatchType(10.0)

    getMatchCollection(Array("Scala","aaa","bbb"))

    /**

     * Scala会帮case class 自动生成伴生对象中的apply方法

     */

    getBigDataMatch(ComputationFramework("Spark",true))

    getBigDataMatch(StorageFramework("HDFS",true))

    getValue("Hadoop",Map("Spark" -> "hot"))

  }

 

  def getSalary(name:String,age:Int) {

    name match {

      case "Spark" => println("$150000/year")

      case "Hadoop" => println("$100000/year")

      case _ if name =="Scala" => println("$140000/year")

      case _ if name =="MapReduce" => println("$90000/year")

      case _name if age > 5 => println(_name+":"+age)

      case _ => println("$80000/year")

    }

  }

 

  def getMatchType(msg:Any){

    msg match {

      case i : Int => println("Int")

      case s : String => println("String")

      case d : Double => println("Double")

      case arr : Array[Any] => println("Array")

      case  _ => println("Unknown")

    }

  }

 

  def getMatchCollection(msg:Array[String]){

    msg match {

      case Array("Scala") => println("One Element")

      case Array("Scala","Java") => println("Two Element")

      case Array("Spark",_*) => println("Spark")

      case _ => println("Unknown")

    }

  }

 

  def getBigDataMatch(data:DataFramework) {

    data match {

      case ComputationFramework(name,popular) =>

        println(name+":"+popular)

      case StorageFramework(name,popular) =>

        println(name+":"+popular)

      case _ =>

        println("Unknown")

    }

  }

 

  def getValue(key:String,content:Map[String,String]) {

    content.get(key) match {

      case Some(value) => println(value)

      case None => println("No find")

    }

  }

 

}

 

归纳总结：1.看笔记