1 常量模式
object ConstantPattern{ def main(args: Array[String]): Unit = { //注意,下面定义的是一个函数 //函数的返回值利用的是模式匹配后的结果作为其返回值 //还需要注意的是函数定义在main方法中 //也即scala语言可以在一个函数中定义另外一个函数 def patternShow(x:Any)=x match { case 5 => "five" case true=>"true" case "test"=>"String" case null=>"null" case Nil=>"empty list" case _ =>"Other constant" } println(patternShow(5)) } }2 变量模式
object VariablePattern{ def main(args: Array[String]): Unit = { def patternShow(x:Any)=x match { case 5 => "five" //所有不是值为5的都会匹配变量y //例如"xxx",则函数的返回结果就是"xxx" case y => y } println(patternShow("xxx")) } }3 构造器模式
//构造器模式必须将类定义为case class case class Person(name:String,age:Int) object ConstructorPattern { def main(args: Array[String]): Unit = { val p=new Person("摇摆少年梦",27) def constructorPattern(p:Person)=p match { case Person(name,age) => "Person" case _ => "Other" } } }4 序列(Sequence)模式 序列模式指的是像Array、List这样的序列集合进行模式匹配
object SequencePattern { def main(args: Array[String]): Unit = { val p=List("spark","hive","SparkSQL") def sequencePattern(p:List[String])=p match { //只需要匹配第二个元素 case List(_,second,_*) => second case _ => "Other" } println(sequencePattern(p)) } }5 元组模式
//匹配某个元组内容 object TuplePattern { def main(args: Array[String]): Unit = { val t=("spark","hive","SparkSQL") def tuplePattern(t:Any)=t match { case (one,_,_) => one case _ => "Other" } println(tuplePattern(t)) } }6 类型模式
//匹配传入参数的类型 object TypePattern { def main(args: Array[String]): Unit = { def tuplePattern(t:Any)=t match { case t:String=> "String" case t:Int => "Integer" case t:Double=>"Double" } println(tuplePattern(5.0)) } }上述代码如果不用模式匹配的话,要实现相同的功能,可以通过下列代码实现:
def tuplePattern2(t:Any)={ if(t.isInstanceOf[String]) "String" else if(t.isInstanceOf[Int]) "Int" else if(t.isInstanceOf[Double]) "Double" else if(t.isInstanceOf[Map[_,_]]) "MAP" }7 变量绑定模式
object VariableBindingPattern { def main(args: Array[String]): Unit = { var t=List(List(1,2,3),List(2,3,4)) def variableBindingPattern(t:Any)= t match { //变量绑定,采用变量名(这里是e) //与@符号,如果后面的模式匹配成功,则将 //整体匹配结果作为返回 case List(_,e@List(_,_,_)) => e case _ => Nil } println(variableBindingPattern(t)) } } //编译执行后的输出结果为 List(2, 3, 4)正则表达式中的模式匹配:
object RegexMatch { def main(args: Array[String]): Unit = { val ipRegex="(\\d+)\\.(\\d+)\\.(\\d+)\\.(\\d+)".r for(ipRegex(one,two,three,four) <- ipRegex.findAllIn("192.168.1.1")) { println("IP子段1:"+one) println("IP子段2:"+two) println("IP子段3:"+three) println("IP子段4:"+four) } } }在前面的课程内容中,我们曾经提到过Option类型,Option类型有两个子类,分别是Some和None(单例对象),本小节将从模式匹配的角度对Option类进行重新思考。
下面给出的是Option类在scala语言中的类层次结构:
Option类其实是一个sealed class
//Option类的部分源码 sealed abstract class Option[+A] extends Product with Serializable { self => /** Returns true if the option is $none, false otherwise. */ def isEmpty: Boolean /** Returns true if the option is an instance of $some, false otherwise. */ def isDefined: Boolean = !isEmpty下面给出的分别是Some及None的源码:
/** Class `Some[A]` represents existing values of type * `A`. * * @author Martin Odersky * @version 1.0, 16/07/2003 */ final case class Some[+A](x: A) extends Option[A] { def isEmpty = false def get = x } /** This case object represents non-existent values. * * @author Martin Odersky * @version 1.0, 16/07/2003 */ case object None extends Option[Nothing] { def isEmpty = true def get = throw new NoSuchElementException("None.get") }下面的代码演示了其如何应用到模式匹配中:
object OptionDemo extends App{ val m=Map("hive"->2,"spark"->3,"Spark MLlib"->4) def mapPattern(t:String)=m.get(t) match { case Some(x) => println(x);x case None => println("None");-1 } println(mapPattern("Hive")) } //输出结果为: //None //-1前面我们看到:None是一个case object,它同Some一样都extends Option类,只不过Some是case class,对于case class我们已经很熟悉了,那case object它又是怎么样的呢?假设我们定义了以下类:
//下面的类主要用于模拟Option,Some,None三个类或对象之间的关系 sealed abstract class A case class B(name:String,age:Int) extends A case object CaseObject extends A{ }上述代码编译后,生成的字节码文件如下:
D:\ScalaWorkspace\ScalaChapter15\bin\cn\scala\xtwy 的目录 2015/08/01 21:26 <DIR> . 2015/08/01 21:26 <DIR> .. 2015/08/01 21:26 515 A.class 2015/08/01 21:26 1,809 B$.class 2015/08/01 21:26 4,320 B.class 2015/08/01 21:26 1,722 CaseObject$.class 2015/08/01 21:26 1,490 CaseObject.class单从编译后生成的类来看,它们之间似乎实现方式都一样,那到底是什么样的呢?
class A的反编译后的代码如下:
D:\ScalaWorkspace\ScalaChapter15\bin\cn\scala\xtwy>javap -private A.class Compiled from "CaseObject.scala" public abstract class cn.scala.xtwy.A { public cn.scala.xtwy.A(); }case class B对应的字节码文件反编译后如下:
D:\ScalaWorkspace\ScalaChapter15\bin\cn\scala\xtwy>javap -private B.class Compiled from "CaseObject.scala" public class cn.scala.xtwy.B extends cn.scala.xtwy.A implements scala.Product,sc ala.Serializable { private final java.lang.String name; private final int age; public static scala.Function1<scala.Tuple2<java.lang.String, java.lang.Object> , cn.scala.xtwy.B> tupled(); public static scala.Function1<java.lang.String, scala.Function1<java.lang.Obje ct, cn.scala.xtwy.B>> curried(); public java.lang.String name(); public int age(); public cn.scala.xtwy.B copy(java.lang.String, int); public java.lang.String copy$default$1(); public int copy$default$2(); public java.lang.String productPrefix(); public int productArity(); public java.lang.Object productElement(int); public scala.collection.Iterator<java.lang.Object> productIterator(); public boolean canEqual(java.lang.Object); public int hashCode(); public java.lang.String toString(); public boolean equals(java.lang.Object); public cn.scala.xtwy.B(java.lang.String, int); } //自动生成的伴生对像类 public final class cn.scala.xtwy.B$ extends scala.runtime.AbstractFunction2<java .lang.String, java.lang.Object, cn.scala.xtwy.B> implements scala.Serializable { public static final cn.scala.xtwy.B$ MODULE$; public static {}; public final java.lang.String toString(); public cn.scala.xtwy.B apply(java.lang.String, int); public scala.Option<scala.Tuple2<java.lang.String, java.lang.Object>> unapply( cn.scala.xtwy.B); private java.lang.Object readResolve(); public java.lang.Object apply(java.lang.Object, java.lang.Object); private cn.scala.xtwy.B$(); }case object CaseObject对应的反编译后的内容:
D:\ScalaWorkspace\ScalaChapter15\bin\cn\scala\xtwy>javap -private CaseObject.cla ss Compiled from "CaseObject.scala" public final class cn.scala.xtwy.CaseObject { public static java.lang.String toString(); public static int hashCode(); public static boolean canEqual(java.lang.Object); public static scala.collection.Iterator<java.lang.Object> productIterator(); public static java.lang.Object productElement(int); public static int productArity(); public static java.lang.String productPrefix(); } D:\ScalaWorkspace\ScalaChapter15\bin\cn\scala\xtwy>javap -private CaseObject$.cl ass Compiled from "CaseObject.scala" public final class cn.scala.xtwy.CaseObject$ extends cn.scala.xtwy.A implements scala.Product,scala.Serializable { public static final cn.scala.xtwy.CaseObject$ MODULE$; public static {}; public java.lang.String productPrefix(); public int productArity(); public java.lang.Object productElement(int); public scala.collection.Iterator<java.lang.Object> productIterator(); public boolean canEqual(java.lang.Object); public int hashCode(); public java.lang.String toString(); private java.lang.Object readResolve(); private cn.scala.xtwy.CaseObject$(); }对比上述代码不难看出,case object与case class所不同的是,case object对应反编译后的CaseObject$.cl ass中不存在apply、unapply方法,这是因为None不需要创建对象及进行内容提取,从这个角度讲,它被定义为case object是十分合理的。
添加公众微信号,可以了解更多最新Spark、Scala相关技术资讯
相关资源:python入门教程(PDF版)