集合
list
set
tuple
map
访问数据应该是下划线1，2，如hostPort._1。下标是从1开始的。
package cn.chinahadoop.scala
class Basic5 {
}
//默认为val
case class Book(name: String, author: String)
object Basic5 extends App {
// val value = 3
// //match是有返回值的
// val result = value match {
// case 1 => "one"
// case 2 => "two"
// case _ => "some other number"
// }
// println("result of match is :" + result)
// val value = 3
// val result = value match {
// case i if i == 1 => "one"
// case i if i == 2 => "two"
// case _ => "some other number"
//
// }
// println("result of match is : " + result)
// def t(obj: Any) = obj match {
// case x: Int => println("Int")
// case s: String => println("String")
// case _ => println("unknown type")
// }
// t(1)
// t("1")
// t(1L)
// val macTalk = Book("MacTalk", "CJQ")
// macTalk match {
// case Book(name, author) => println(" this is a book")
// case _ => println("unknown")
// }
// val l = List(1, 2, 3, 4, 5, 6, 7, 8, 9)
// val newList = l.map((x: Int) => 2 * x)
// val newList2 = l.map((x) => 2 * x)
// val newList3 = l.map(x => 2 * x)
// println(newList)
// println(newList2)
// println(newList3)
// val newList = l.map(2 * _)
// println(newList)
var l = List(1, 2, 3, 4, 5, 6);
var s = Set(1, 2, 3, 4, 5, 6);
val l1 = List(1, 2, 3, 4, 5)
val s1 = Set(1, 2, 3);
val hostPort = ("localhost", "8080")
//访问数组
println(hostPort._1)
}
结果：
localhost
package cn.chinahadoop.scala
class Basic5 {
}
//默认为val
case class Book(name: String, author: String)
object Basic5 extends App {
// val value = 3
// //match是有返回值的
// val result = value match {
// case 1 => "one"
// case 2 => "two"
// case _ => "some other number"
// }
// println("result of match is :" + result)
// val value = 3
// val result = value match {
// case i if i == 1 => "one"
// case i if i == 2 => "two"
// case _ => "some other number"
//
// }
// println("result of match is : " + result)
// def t(obj: Any) = obj match {
// case x: Int => println("Int")
// case s: String => println("String")
// case _ => println("unknown type")
// }
// t(1)
// t("1")
// t(1L)
// val macTalk = Book("MacTalk", "CJQ")
// macTalk match {
// case Book(name, author) => println(" this is a book")
// case _ => println("unknown")
// }
// val l = List(1, 2, 3, 4, 5, 6, 7, 8, 9)
// val newList = l.map((x: Int) => 2 * x)
// val newList2 = l.map((x) => 2 * x)
// val newList3 = l.map(x => 2 * x)
// println(newList)
// println(newList2)
// println(newList3)
// val newList = l.map(2 * _)
// println(newList)
var l = List(1, 2, 3, 4, 5, 6);
var s = Set(1, 2, 3, 4, 5, 6);
val l1 = List(1, 2, 3, 4, 5)
val s1 = Set(1, 2, 3);
val hostPort = ("localhost", "8080")
//访问数组
println(hostPort._1)
println("a" -> "s1")
}
结果：
localhost (a,s1)
用"a" -> "b" 创建了一个字符串(a,s1)的字符数组。
package cn.chinahadoop.scala
class Basic5 {
}
//默认为val
case class Book(name: String, author: String)
object Basic5 extends App {
// val value = 3
// //match是有返回值的
// val result = value match {
// case 1 => "one"
// case 2 => "two"
// case _ => "some other number"
// }
// println("result of match is :" + result)
// val value = 3
// val result = value match {
// case i if i == 1 => "one"
// case i if i == 2 => "two"
// case _ => "some other number"
//
// }
// println("result of match is : " + result)
// def t(obj: Any) = obj match {
// case x: Int => println("Int")
// case s: String => println("String")
// case _ => println("unknown type")
// }
// t(1)
// t("1")
// t(1L)
// val macTalk = Book("MacTalk", "CJQ")
// macTalk match {
// case Book(name, author) => println(" this is a book")
// case _ => println("unknown")
// }
// val l = List(1, 2, 3, 4, 5, 6, 7, 8, 9)
// val newList = l.map((x: Int) => 2 * x)
// val newList2 = l.map((x) => 2 * x)
// val newList3 = l.map(x => 2 * x)
// println(newList)
// println(newList2)
// println(newList3)
// val newList = l.map(2 * _)
// println(newList)
// var l = List(1, 2, 3, 4, 5, 6);
// var s = Set(1, 2, 3, 4, 5, 6);
// val l1 = List(1, 2, 3, 4, 5)
// val s1 = Set(1, 2, 3);
// val hostPort = ("localhost", "8080")
//访问数组
// println(hostPort._1)
// println("a" -> "s1")
val m1 = Map("a" -> "b");
println(m1)
}
结果：
Map(a -> b)
map的初始化。
package cn.chinahadoop.scala
class Basic5 {
}
//默认为val
case class Book(name: String, author: String)
object Basic5 extends App {
// val value = 3
// //match是有返回值的
// val result = value match {
// case 1 => "one"
// case 2 => "two"
// case _ => "some other number"
// }
// println("result of match is :" + result)
// val value = 3
// val result = value match {
// case i if i == 1 => "one"
// case i if i == 2 => "two"
// case _ => "some other number"
//
// }
// println("result of match is : " + result)
// def t(obj: Any) = obj match {
// case x: Int => println("Int")
// case s: String => println("String")
// case _ => println("unknown type")
// }
// t(1)
// t("1")
// t(1L)
// val macTalk = Book("MacTalk", "CJQ")
// macTalk match {
// case Book(name, author) => println(" this is a book")
// case _ => println("unknown")
// }
// val l = List(1, 2, 3, 4, 5, 6, 7, 8, 9)
// val newList = l.map((x: Int) => 2 * x)
// val newList2 = l.map((x) => 2 * x)
// val newList3 = l.map(x => 2 * x)
// println(newList)
// println(newList2)
// println(newList3)
// val newList = l.map(2 * _)
// println(newList)
// var l = List(1, 2, 3, 4, 5, 6);
// var s = Set(1, 2, 3, 4, 5, 6);
// val l1 = List(1, 2, 3, 4, 5)
// val s1 = Set(1, 2, 3);
// val hostPort = ("localhost", "8080")
//访问数组
// println(hostPort._1)
// println("a" -> "s1")
val m1 = Map("a" -> "b", "c" -> "d");
println(m1)
}
结果：
Map(a -> b, c -> d)
集合操作
foreach（类似于map，但是没有返回值）
map（迭代）
filter（过滤）
zip（集合）
partition(列表过滤)
flatten(扁平化)
flatMap(map+flatten)
val m1 = Map("a" -> "b", "c" -> "d", "e" -> "f", "c" -> "f");
println(m1("c"))
结果：
f
在java中key是不能有重复的，但在scala中可以，但如果key重复的话后面的值会覆盖前面的值。
val m1 = Map("a" -> "b", "c" -> "d", "e" -> "f", "c" -> "f");
// println(m1("c"))
println(m1.getOrElse("c", 3));
println(m1.getOrElse("cd", 4));
结果：
f 4
val l = List('c', 'd', 'e', 's', 'e', 's', 'e', 's', 'f', 'd', 'f', 's', 'w')
println(l.take(1))
结果：
List(c)
foreach用法
val m1 = Map("a" -> "b", "c" -> "d", "e" -> "f", "c" -> "f");
val l = List('c', 'd', 'e', 's', 'e', 's', 'e', 's', 'f', 'd', 'f', 's', 'w')
val r1=List(1,23,4,52,2,3)
println(l.take(1))
println(r1.map(3 * _))
println(r1)
结果：
List(c) List(3, 69, 12, 156, 6, 9) List(1, 23, 4, 52, 2, 3)
foreach没有返回值
val r1 = List(1, 23, 4, 52, 2, 3) println(r1.foreach(3 * _))
结果：
()
filter的用法 （过滤）
val r1 = List(1, 23, 4, 52, 2, 3) println(r1.filter(x => x % 2 == 0))
结果：
List(4, 52, 2)
zip，聚合，对数值进行匹配
val a = List(1, 2, 3) val b = List(4, 5, 6) println(a.zip(b))
结果：
List((1,4), (2,5), (3,6))
如果没有数值对它进行匹配，就会省略
val a = List(1, 2, 3) val b = List(4, 5, 6,7) println(a.zip(b))
结果：
List((1,4), (2,5), (3,6))
partiton列表分割
val l = List(1, 2, 3, 4, 5, 6, 7, 8) println(l.partition(_ % 2 == 0))
结果：
(List(2, 4, 6, 8),List(1, 3, 5, 7))
flatten（扁平化）
val l=List(List("a","b"),List("c","d")).flatten
println(l)
结果：
List(a, b, c, d)
flatMap(map+flatten)
val l = List(List(1, 2), List(3, 4)) println(l.flatMap(x => x.map(_ * 2)))
结果：
List(2, 4, 6, 8)
spark官网中http://spark.apache.org/有出现这个例子
file = spark.textFile("hdfs://...")
file.flatMap(lambda line: line.split())
.map(lambda word: (word, 1))
.reduceByKey(lambda a, b: a+b)
泛型
泛型类
class Pair[T,S](val first: T, val second: S)
泛型方法
def compute[T](list:List[T])=....
隐式转换
位于源目标类型的伴生对象中的隐式函数
位于当前作用域可以以单个标识符指代的隐匿函数
隐式参数
隐式类(scala 2.10)
隐式转换的关键字implicit
package cn.chinahadoop.scala
class Basic6 {
}
class A {
}
class RichA(a: A) {
def rich {
println("rich ......")
}
}
object Basic6 extends App {
implicit def a_RichA(a: A) = new RichA(a)
val a = new A
a.rich
}
结果：
rich ......
隐式参数
def testParam(implicit name: String) {
println(name)
}
implicit val name = "implicit!!!"
testParam
结果：
implicit!!!
def testParam(implicit name: String) {
println(name)
}
implicit val name = "implicit!!!"
testParam("chsl")
结果：
chsl
隐式类
implicit class Calculator(x: Int) {
def add(a: Int): Int = a + 1
}
print(1.add(1))
结果：
2
转载于:https://blog.51cto.com/chenshenglong/1415581
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