大数据之scala基本语法学习
package edu.snnu.test object list2 { //把字符串转化成一个char类型的list "99 Red Balloons".toList //> res0: List[Char] = List(9, 9, , R, e, d, , B, a, l, l, o, o, n, s) "99 Red Balloons".toList.filter(x => Character.isDigit(x)) //> res1: List[Char] = List(9, 9) "99 Red Balloons".toList.takeWhile(x => x != 'B') //> res2: List[Char] = List(9, 9, , R, e, d, ) val c = List("x", "y", "z") //> c : List[String] = List(x, y, z) c.map(x => x.toUpperCase) //> res3: List[String] = List(X, Y, Z) //上面的语句可以简写为下面形式，因为scala中有下划线作为通配符 c.map(_.toUpperCase()) //> res4: List[String] = List(X, Y, Z) val a = List(1, 2, 3, 4) //> a : List[Int] = List(1, 2, 3, 4) a.filter(_%2 == 1) //> res5: List[Int] = List(1, 3) //对a这个list中的每个奇数元素加上10 a.filter(_%2 == 1).map(_+10) //> res6: List[Int] = List(11, 13) val q = List(a, List(4, 5, 6)) //> q : List[List[Int]] = List(List(1, 2, 3, 4), List(4, 5, 6)) q.map(x => x.filter(_%2 == 0)) //> res7: List[List[Int]] = List(List(2, 4), List(4, 6)) q.map(_.filter(_%2 == 0)) //> res8: List[List[Int]] = List(List(2, 4), List(4, 6)) //把有两个集合的集合中，内层中满足条件的元素变到一个list中 q.flatMap {_.filter(_%2 == 0)} //> res9: List[Int] = List(2, 4, 4, 6) }
柯里化案例：
(x: Int, y : Int) => x + y //> res0: (Int, Int) => Int = <function2> //def curriedAdd(a: Int)(b:Int)(c:Int)(d:Int) = a + b*c*d def curriedAdd(a:Int,b:Int)(c:Int)(d:Int) = a + b*c*d //> curriedAdd: (a: Int, b: Int)(c: Int)(d: Int)Int //curriedAdd(2)(2)(2)(2) val addOne = curriedAdd(4,3)_ //> addOne : Int => (Int => Int) = <function1> val c = addOne(2)(3) //> c : Int = 22 println(addOne) //> <function1>
Map使用方法
package edu.snnu.test object mapDemo { println("Welcome to the Scala worksheet") //> Welcome to the Scala worksheet val p = Map(1 -> "David", 9 -> "Elwood", "rain" -> "明明") //> p : scala.collection.immutable.Map[Any,String] = Map(1 -> David, 9 -> Elwoo //| d, rain -> 鏄庢槑) //通过key取map中对应的val p(1) //> res0: String = David p(9) //> res1: String = Elwood p("rain") //> res2: String = 鏄庢槑 //contains方法用来判断某个key在不在map里面 p.contains(1) //> res3: Boolean = true p.contains(2) //> res4: Boolean = false //调用map变量的keys方法将会返回一个存储这个map所有key的list p.keys //> res5: Iterable[Any] = Set(1, 9, rain) //val叶同样 p.values //> res6: Iterable[String] = MapLike(David, Elwood, 鏄庢槑) //添加一个（key，value）到map中 val pp = p+(8->"Archer") //> pp : scala.collection.immutable.Map[Any,String] = Map(1 -> David, 9 -> Elwo //| od, rain -> 鏄庢槑, 8 -> Archer) p //> res7: scala.collection.immutable.Map[Any,String] = Map(1 -> David, 9 -> Elwo //| od, rain -> 鏄庢槑) pp //> res8: scala.collection.immutable.Map[Any,String] = Map(1 -> David, 9 -> Elwo //| od, rain -> 鏄庢槑, 8 -> Archer) //删除一个(key, value)：map变量减去要删除的键值对的key即可 p-1 //> res9: scala.collection.immutable.Map[Any,String] = Map(9 -> Elwood, rain -> //| 鏄庢槑) p ++ List(2 ->"Alice", 5->"Bob") //> res10: scala.collection.immutable.Map[Any,String] = Map(5 -> Bob, 1 -> David //| , 9 -> Elwood, rain -> 鏄庢槑, 2 -> Alice) p -- List(1, 9, 2, "rain") //> res11: scala.collection.immutable.Map[Any,String] = Map() p //> res12: scala.collection.immutable.Map[Any,String] = Map(1 -> David, 9 -> Elw //| ood, rain -> 鏄庢槑) p ++ List(2 ->"Alice", 5->"Bob") -- List(9, 1, "rain") //> res13: scala.collection.immutable.Map[Any,String] = Map(5 -> Bob, 2 -> Alice //| ) }
快速排序小案例
package edu.snnu.test object qSort { println("Welcome to the Scala worksheet") //> Welcome to the Scala worksheet def qSort(a:List[Int]):List[Int] = { if(a.length < 2) a else qSort(a.filter(_<a.head)) ++ a.filter(_ == a.head) ++ qSort(a.filter(_>a.head)) } //> qSort: (a: List[Int])List[Int] val l = List(1, 2, 3, 4, 5, 9, 8, 7, 6) //> l : List[Int] = List(1, 2, 3, 4, 5, 9, 8, 7, 6) qSort(List(4, 3, 2, 6, 7, 8, 9)) //> res0: List[Int] = List(2, 3, 4, 6, 7, 8, 9) qSort(l) //> res1: List[Int] = List(1, 2, 3, 4, 5, 6, 7, 8, 9) }
range的使用
package edu.snnu.test object Range { println("Welcome to the Scala worksheet") //> Welcome to the Scala worksheet 1 to 10 //> res0: scala.collection.immutable.Range.Inclusive = Range(1, 2, 3, 4, 5, 6, 7, //| 8, 9, 10) 1 to 10 by 2 //> res1: scala.collection.immutable.Range = Range(1, 3, 5, 7, 9) (1 to 10).toList //> res2: List[Int] = List(1, 2, 3, 4, 5, 6, 7, 8, 9, 10) 1 until 10 //> res3: scala.collection.immutable.Range = Range(1, 2, 3, 4, 5, 6, 7, 8, 9) //也就是说to上届是一个闭区间 ，until上界是一个闭区间 val s = 1 #::2 #:: 3 #::Stream.empty //> s : <error> = Stream(1, ?) }
reduceLeft以及foldleft规约的使用
package edu.snnu.test object reduceLeft { //reduceLeft是一种规约方法 val a = List(1, 2, 3, 4) //> a : List[Int] = List(1, 2, 3, 4) //map的返回值和原来的值的类型是一样的，flatMap会把两层的map转化为一层的map a.reduceLeft((x, y) => x + y) //> res0: Int = 10 //简写方式，用两个下划线来代替这两个参数 a.reduce(_+_) //> res1: Int = 10 //foldleft也是一种规约方法 a.foldLeft(1)(_+_) //> res2: Int = 11 a.foldLeft(2)(_*_) //> res3: Int = 48 }
懒加载
package edu.snnu.test object StreamDemo { println("Welcome to the Scala worksheet") //> Welcome to the Scala worksheet //懒加载，在用的时候求值，按需求值 //val a = 1 #:: 2 #:: 3 #:: Stream.empty //val stream = (1 to 10000000).toStream() }
List的使用
package edu.snnu.test object test1 { println("Welcome to the Scala worksheet") //> Welcome to the Scala worksheet val a = List(1, 2, 3, 4) //> a : List[Int] = List(1, 2, 3, 4) //把0添加到刚才的list里面，两个冒号为连接操作符，连接操作符的左边是成员，右边是一个list val b = 0::a //> b : List[Int] = List(0, 1, 2, 3, 4) val c = "x"::"y"::"z"::Nil //> c : List[String] = List(x, y, z) //生成一个list(z) "z"::Nil //> res0: List[String] = List(z) //三个毛冒号的连接操作符用于连接两个list a:::c //> res1: List[Any] = List(1, 2, 3, 4, x, y, z) //list的head方法返回当前list的第一个元素 a.head //> res2: Int = 1 b.head //> res3: Int = 0 c.head //> res4: String = x //list的tail方法返回当前list里除了第一个元素外的所有元素组成的list,这样的列表我们称为尾列表 a //> res5: List[Int] = List(1, 2, 3, 4) a.tail //> res6: List[Int] = List(2, 3, 4) b //> res7: List[Int] = List(0, 1, 2, 3, 4) b.tail //> res8: List[Int] = List(1, 2, 3, 4) a.isEmpty //> res9: Boolean = false Nil //> res10: scala.collection.immutable.Nil.type = List() Nil.isEmpty //> res11: Boolean = true def walkthru(l:List[Int]) :String = { if(l.isEmpty) "" else { println(l.tail) l.head.toString+""+walkthru(l.tail) } } //> walkthru: (l: List[Int])String walkthru(List(1,2,3,4,5)) //> List(2, 3, 4, 5) //| List(3, 4, 5) //| List(4, 5) //| List(5) //| List() //| res12: String = 12345 //对list a进行过滤，如果里面的元素x满足x%2 == 1，那么保留下来，否则就删除 a.filter(x => x%2 == 1) //> res13: List[Int] = List(1, 3) }
tuple的使用
package edu.snnu.test object tuple { 1 -> 2 //> res0: (Int, Int) = (1,2) //定义一个tuple val t = (1, "Alice", "Math", 95,5) //> t : (Int, String, String, Int, Int) = (1,Alice,Math,95,5) //获得tuple t的第一个成员 t._1 //> res1: Int = 1 //获得tuple t的第二个成员 t._2 //> res2: String = Alice //第三个 t._3 //> res3: String = Math //函数的返回值一般都只有一个值，如果有多个值的话我们就可以把这多个值封装在一个tuple里， val a = List(1, 2, 3, 4) //> a : List[Int] = List(1, 2, 3, 4) //(Int, Int, Int)代表返回值是一个三个int数据的list def sumSq(in: List[Int]):(Int,Int,Int) = { //下面t代表(0, 0, 0)这个元组，v代表这个list中的每一个值 in.foldLeft((0,0,0))((t,v) => (t._1 + 1, t._2+v, t._3+v*v)) } //> sumSq: (in: List[Int])(Int, Int, Int) sumSq(a) //> res4: (Int, Int, Int) = (4,10,30) }
