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scala集合基本介绍
- scala同时支持可变和不可变集合，不可变集合可安全的并发访问
- 2个主要的包：
- 不可变：scala.collection.immutable
- 可变：scala.collection.mutable
- scala默认采用不可变集合，对于几乎所有集合类，scala都提供了2个版本
不可变：集合本身内存地址不可变
集合的继承关系图
注意scala和java集合体系的不同。
+----------+
+------------+ Iterable +-------------+
| +-----+----+ |
| | |
+---v---+ | +----v--+
+-------------+------+ Set +---------+ | +----+ Map +--+----------+
| | +-------+ | | | +-------+ | |
+---v-----+ +---v-----+ +------+ +----v--+ | +-v-----+ +------v--+ +---v---+
| HashSet | |SortedSet| |BitSet| |ListSet| | |HashMap| |SortedMap| |ListMap|
+---------+ +---+-----+ +------+ +-------+ | +-------+ +----+----+ +-------+
| | |
+---v----+ | +-----v--+
|TreeSet | | | TreeMap|
+--------+ +--v+ +--------+
+---------------+Seq+------------------+
| +---+ |
+-----v-----+ +----v----+
|IndexedSeq | |LinearSeq|
+--------------+---------------+ +----------+-----+
| | | |
+--v---+ +-v---+ +-v---+ +--v--+
|Vector| |Array| | List| |Queue|
+------+ +-----+ +-----+ +-----+定长数组
// 方式1
val ints = new Array[Int](4)
println(ints.length) // 4
ints(3) = 9
for (i <- ints) {
println(i)
}
// 方式2
// Array[Int]
val arr01 = Array(1, 2)
arr01.foreach(println(_))
// Array[Any]
val arr02 = Array(1, 3, "hello")
arr02.foreach(println)变长数组
val arr01 = ArrayBuffer[Int](4, 5, 6, 1)
arr01.append(90, 88)
arr01.append(1)
arr01(1) = 10
arr01.foreach(println)
println("==============")
val arr02 = ArrayBuffer[Any](1, 2.3, "he")
arr02.foreach(println)
// 定长与变长互转
val arr03 = arr01.toArray
val arr04 = arr03.toBuffer
arr04.foreach(println)多维数组
val arr = Array.ofDim[Int](3, 4)
arr(1)(1) = 3
for (a1 <- arr) {
for (elem <- a1) {
print(elem + ",")
}
println()看下底层：
public void main(String[] args) {
int[][] arr = (int[][])scala.Array$.MODULE$.ofDim(3, 4, scala.reflect.ClassTag$.MODULE$.Int());
arr[1][1] = 3;
scala.Predef$.MODULE$.refArrayOps((Object[])arr).foreach((Function1)new ColDemo04$$anonfun$main$1());
}scala数组与java数组互换
scala转java
val arr = ArrayBuffer("1", "2", "3")
import scala.collection.JavaConversions.bufferAsJavaList
val builder = new ProcessBuilder(arr)
val list = builder.command()
println(list) // [1, 2, 3]注意这个bufferAsJavaList，实际上是个隐式转换：
implicit def bufferAsJavaList[A](b: mutable.Buffer[A]): ju.List[A] = b match {
case JListWrapper(wrapped) => wrapped
case _ => new MutableBufferWrapper(b)
}java转scala
import scala.collection.JavaConversions.asScalaBuffer
import scala.collection.mutable
val scalaArr: mutable.Buffer[String] = list
println(scalaArr) // ArrayBuffer(1, 2, 3)元组
最多22个
case class Tuple22[+T1, +T2, +T3, +T4, +T5, +T6, +T7, +T8, +T9, +T10, +T11, +T12, +T13, +T14, +T15, +T16, +T17, +T18, +T19, +T20, +T21, +T22](_1: T1, _2: T2, _3: T3, _4: T4, _5: T5, _6: T6, _7: T7, _8: T8, _9: T9, _10: T10, _11: T11, _12: T12, _13: T13, _14: T14, _15: T15, _16: T16, _17: T17, _18: T18, _19: T19, _20: T20, _21: T21, _22: T22)
extends Product22[T1, T2, T3, T4, T5, T6, T7, T8, T9, T10, T11, T12, T13, T14, T15, T16, T17, T18, T19, T20, T21, T22]
{
override def toString() = "(" + _1 + "," + _2 + "," + _3 + "," + _4 + "," + _5 + "," + _6 + "," + _7 + "," + _8 + "," + _9 + "," + _10 + "," + _11 +
"," + _12 + "," + _13 + "," + _14 + "," + _15 + "," + _16 + "," + _17 + "," + _18 + "," + _19 + "," + _20 + "," + _21 + "," + _22 + ")"
}例子：
val t4 = (1, 2, 3, "hehe")
println(t4, t4._1, t4._4) // ((1,2,3,hehe),1,hehe)编译后：
public void main(String[] args) {
Tuple4 t4 = new Tuple4(BoxesRunTime.boxToInteger(1), BoxesRunTime.boxToInteger(2), BoxesRunTime.boxToInteger(3), "hehe");
scala.Predef$.MODULE$.println(new Tuple3(t4, t4._1(), t4._4()));
}更多遍历方式：
println(t4.productElement(3))
for (elem <- t4.productIterator) {
println(elem)
}List
scala的List就是个object，是可变的。
def main(args: Array[String]): Unit = {
val list1 = List(1, 2, "AA")
println(list1) // List(1,2,AA)
// 空集合
val list2 = Nil
println(list2) // List()
}注意空列表也是List
case object Nil extends List[Nothing]{}取值：
println(list1(2)) // AA追加元素：
// 追加:返回新的集合/列表，与Java不一样
// 右边追加
val list3 = list1 :+ 4
println(list3) // List(1, 2, AA, 4)
// 左边追加
val list4 = 33 +: list1
println(list4) // List(33, 1, 2, AA)追加元素的符号 ::
val list5 = List(3, 4, "jimo")
val list6 = 4 :: 5 :: list5 :: 3 :: Nil
// 从右往左，从后往前塞
println(list6) // List(4, 5, List(3, 4, jimo), 3)
val list7 = 4 :: 5 :: list5 ::: 3 :: Nil
// 解构
println(list7) // List(4, 5, 3, 4, jimo, 3)数组练习
1.生成随机数数组
def mkArr(n: Int): Array[Int] = {
val a = new Array[Int](n)
val random = new Random()
for (i <- a) yield random.nextInt(n)
}2.交换相邻的2个元素
输入
5 9 3 10 1 1 2 0 0 7 8
输出
9 5 10 3 1 1 0 2 7 0 8 主要是util的使用
def revert(arr: Array[Int]): Unit = {
for (i <- 0 until(arr.length - 1, 2)) {
val t = arr(i)
arr(i) = arr(i + 1)
arr(i + 1) = t
}
}队列
插入数据
val q = new mutable.Queue[Int]
q += 1
q += 1
q ++= List(2, 3, 4)
println(q) // Queue(1, 1, 2, 3, 4)
val q2 = new mutable.Queue[Any]()
q2 += 10
q2 += List(1, 2, 3)
println(q2) // Queue(10, List(1, 2, 3))+=的特殊运算符，本质上还是 append
def +=(elem: A): this.type = { appendElem(elem); this }删除数据：出队入队
q.dequeue()
println(q) // Queue(1, 2, 3, 4)
q.enqueue(6, 7, 8)
println(q) // Queue(1, 2, 3, 4, 6, 7, 8)返回队列的头和尾
println(q.head, q) // (1,Queue(1, 2, 3, 4, 6, 7, 8))
println(q.last, q) // (8,Queue(1, 2, 3, 4, 6, 7, 8))
// 返回除第一个以外的后元素
println(q.tail) // Queue(2, 3, 4, 6, 7, 8)
println(q.tail.tail) // Queue(3, 4, 6, 7, 8)Map
scala中 不可变Map是有序的，可变map是无序的
val m1 = new mutable.HashMap[String, Int]()
m1.put("k1", 10)
m1.put("k2", 20)
m1.put("k3", 30)
println(m1) // Map(k2 -> 20, k1 -> 10, k3 -> 30)
println(m1.get("k2")) // Some(20)
// 不可变
val m2 = immutable.Map("a" -> 11, "b" -> 22, "c" -> 33)
println(m2) // Map(a -> 11, b -> 22, c -> 33)
println(m2("b"))
for (e <- m2) {
print(s"key=${e._1},value=${e._2},")
} // key=a,value=11,key=b,value=22,key=c,value=33, // 二元组的方式构建
val m3 = mutable.Map(("name", "jimo"), ("age", 18))
println(m3)取数抛异常：
println(m3.get("height"))
println(m3("height"))get方法不会
None
Exception in thread "main" java.util.NoSuchElementException: key not found: height
at scala.collection.MapLike$class.default(MapLike.scala:228)
at scala.collection.AbstractMap.default(Map.scala:59)
at scala.collection.mutable.HashMap.apply(HashMap.scala:65)
at com.jimo.scala.col.ColDemo10$.main(ColDemo10.scala:27)
at com.jimo.scala.col.ColDemo10.main(ColDemo10.scala)增加删除元素：
// 添加元素
val m4 = mutable.Map((0, 2))
m4 += (1 -> 2)
m4 += (2 -> 3)
println(m4) // Map(2 -> 3, 1 -> 2, 0 -> 2)
// 添加多个元素
m4 += (3 -> 4, 5 -> 6)
println(m4) // Map(2 -> 3, 5 -> 6, 1 -> 2, 3 -> 4, 0 -> 2)
// 删除元素
m4 -= (1, 2, 100)
println(m4) // Map(5 -> 6, 3 -> 4, 0 -> 2)遍历：
for ((k, v) <- m4) {
println(k, v)
}
for (elem <- m4.values) {
println(elem)
}
for (elem <- m4.keys) {
println(elem)
}
for (t <- m4) {
println(t._1, t._2)
}Set
创建
// 创建
val s1 = new mutable.HashSet[Int]()
s1.add(1)
s1.add(2)
s1.add(2)
s1.add(1)
println(s1)
val s2 = mutable.Set(1, 2, 3, 4, 3, 2, 3)
println(s2) // Set(1, 2, 3, 4)
// 默认不可变
val s3 = Set(1, 2, 3, 4, 3, 2, 3)
println(s3) // Set(1, 2, 3, 4)添加
// 添加元素
s2 += 4
s2 += 5
println(s2) // Set(1, 5, 2, 3, 4)
// 返回新的
val s4 = s2.+(6)
println(s4) // Set(1, 5, 2, 6, 3, 4)删除
// 删除
s2 -= 4
s2.remove(3)
println(s2) // Set(1, 5, 2)遍历
// 遍历
for (elem <- s2) {
println(elem)
}集合的交并差
// 交集
println(s1 & s2) // Set(1, 2)
// 差集
println(s1 &~ s2) // Set()
// 并集
println(s1 ++ s2) // Set(1, 5, 2)高阶函数
参数为函数
def main(args: Array[String]): Unit = {
println(test(twoFold, 2.0))
}
/**
* 以函数作为参数的函数
*/
def test(f: Double => Double, d: Double): Double = {
f(d)
}
def twoFold(d: Double): Double = {
2 * d
}map
将高阶函数应用于集合，函数式编程
val l1 = List(1, 2, 3)
println(l1.map(_ * 2)) // List(2, 4, 6)
val names = List("Hehe", "Jimo", "Lily")
print(names.map(_.toUpperCase())) // List(HEHE, JIMO, LILY)flatmap
集合中的每个元素的子元素映射到某个函数并返回新的集合。
val names = List("Hehe", "Jimo", "Lily")
// List(H, E, H, E, J, I, M, O, L, I, L, Y)
println(names.flatMap(_.toUpperCase()))filter
将符合要求的元素放到新集合
过滤以J开始的元素
val names = List("Hehe", "Jimo", "Lily")
println(names.filter(_.startsWith("J"))) // List(Jimo)reduce
简化版折叠
val nums = List(1, 2, 3, 4, 5, 6, 7)
println(nums.reduce(_ + _)) // 28
println(nums.sum) // 28
/**
* 1-2=-1
* -1-3=-4
* ...
* -19-7=-26
*/
println(nums.reduceLeft(_ - _)) // -26
/**
* 6-7=-1
* 5-(-1)=6
* 4-6=-2
* 3-(-2)=5
* 2-5=-3
* 1-(-3)=4
*/
println(nums.reduceRight(_ - _)) // 4fold
折叠: 相比于reduce，多了一个初始值
val nums = List(1, 2, 3, 4, 5, 6, 7)
println(nums.fold(1)(_ + _)) // 29
println(nums.foldLeft(1)(_ + _)) // 29
println(nums.foldRight(1)(_ + _)) // 29
println(nums.foldLeft(28)(_ - _)) // 0
println(nums.foldRight(4)(_ - _)) // 0缩写方式：
// foldLeft
println((1 /: nums) (_ + _)) // 29
println((28 /: nums) (_ - _)) // 0
// foldRight
println((nums :\ 1) (_ + _)) // 29
println((nums :\ 4) (_ - _)) // 0scan
扫描：对集合的每个元素做fold操作，但会把中间结果放到一个集合中保存
println(nums.scanLeft(1)(_ + _)) // List(1, 2, 4, 7, 11, 16, 22, 29)
println(nums.scanLeft(28)(_ - _)) // List(28, 27, 25, 22, 18, 13, 7, 0)
println(nums.scanRight(1)(_ + _)) // List(29, 28, 26, 23, 19, 14, 8, 1)
println(nums.scanRight(4)(_ - _)) // List(0, 1, 1, 2, 2, 3, 3, 4)练习
- 使用foldLeft把字符放进array里
val s = "AAAAAAAAAAAAAABBBBBBBBBBSDDDDDDDDDD"
val buf = ArrayBuffer[Char]()
println(s.foldLeft(buf)((b, c) => {
b.append(c);
b
}))
println(buf)
// ArrayBuffer(A, A, A, A, A, A, A, A, A, A, A, A, A, A, B, B, B, B, B, B, B, B, B, B, S, D, D, D, D, D, D, D, D, D, D)- 统计字符出现的次数
// 2. Map(A -> 14, B -> 10, S -> 1, D -> 10)
println(s.foldLeft(Map[Char, Int]())((map, c) => map + (c -> (map.getOrElse(c, 0) + 1))))zip
拉链（合并）：如果元素不匹配会丢失，按照最短长度
val list1 = List(1, 2, 3, 8)
val list2 = List(4, 5, 6)
println(list1.zip(list2)) // List((1,4), (2,5), (3,6))迭代器
val list3 = List(2, 3, 4, 5)
val it = list3.iterator
while (it.hasNext) {
println(it.next())
}stream
def numAdd(n: BigInt): Stream[BigInt] = n #:: numAdd(n + 1)
val stream1 = numAdd(1)
println(stream1) // Stream(1, ?)
// 我希望再取一个数据
println(stream1.tail) // Stream(2, ?)
println(stream1) // Stream(1, 2, ?)
println(stream1.head) // 1
println(stream1.take(2)) // Stream(1, ?)view
可用于懒加载
val viewSeq = (1 to 10).view.map(_ * 2).filter(_ % 2 == 0)
println(viewSeq) // SeqViewMF(...)
// 需要时才出结果
viewSeq.foreach(println)并行集合
- 充分利用多核CPU
- 主要用到的算法：分治；负载均衡算法(work stealin)
// 常规：串行
(1 to 5).foreach(println)
// 并行: 随机顺序
(1 to 5).par.foreach(println)再看个例子：我电脑有12个核,所以并行时全利用上了
val thread1 = (1 to 100).map(_ => Thread.currentThread().getName).distinct
println(thread1) // Vector(main)
val thread2 = (1 to 100).par.map { _ => Thread.currentThread().getName }.distinct
println(thread2) // ParVector(ForkJoinPool-1-worker-29, ForkJoinPool-1-worker-13, ForkJoinPool-1-worker-3, ForkJoinPool-1-worker-7, ForkJoinPool-1-worker-25, ForkJoinPool-1-worker-21, ForkJoinPool-1-worker-11, ForkJoinPool-1-worker-9, ForkJoinPool-1-worker-23, ForkJoinPool-1-worker-31, ForkJoinPool-1-worker-17, ForkJoinPool-1-worker-27)操作符扩展
使用关键字做变量名
val `var`: Int = 100
println(`var`)后置操作符
// 前置操作符
val n1 = 2
val n2 = 3
println(n1.+(n2)) // 等价于 n1 + n2
val p = new Person
p.+(10)
println(p.age) // 10
p + 10
println(p.age) // 20
class Person {
var age: Int = 0
def +(n: Int): Unit = {
age += n
}
}前置操作符
val op2 = new Op2
!op2 // !!!!
class Op2 {
// unary:一元运算符
def unary_!(): Unit = println("!!!!")
}练习
交换对偶泛型
val pair = new Pair[String, Int]("jimo", 18)
println(pair) // s=18,t=jimo
val pair2 = pair.swap()
println(pair2) // s=jimo,t=18
final class Pair[T, S](t: T, s: S) {
def swap(): Pair[S, T] = new Pair(s, t)
override def toString: String = (s"s=${s},t=${t}")
}
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只有泛型类型一致才交换：
val p = new Pair[String, String]("jimo", "hehe")
val p2 = p.swapSame
println(p2) // s=hehe,t=jimo
// S =:= T 表示 S和T的类型要一致
def swapSame(implicit env: S =:= T) = new Pair(t, s)
