283 lines
6.6 KiB
Markdown
283 lines
6.6 KiB
Markdown
# Map & Tuple
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<nav>
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<a href="#一映射Map">一、映射(Map)</a><br/>
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<a href="#11-构造Map">1.1 构造Map</a><br/>
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<a href="#12-获取值">1.2 获取值</a><br/>
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<a href="#13-新增修改删除值">1.3 新增/修改/删除值</a><br/>
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<a href="#14-遍历Map">1.4 遍历Map</a><br/>
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<a href="#15-yield关键字">1.5 yield关键字</a><br/>
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<a href="#16-其他Map结构">1.6 其他Map结构</a><br/>
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<a href="#17-可选方法">1.7 可选方法</a><br/>
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<a href="#18-与Java互操作">1.8 与Java互操作</a><br/>
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<a href="#二元组Tuple">二、元组(Tuple)</a><br/>
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<a href="#21--模式匹配">2.1 模式匹配</a><br/>
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<a href="#22-zip方法">2.2 zip方法</a><br/>
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</nav>
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## 一、映射(Map)
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### 1.1 构造Map
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```scala
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// 初始化一个空 map
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val scores01 = new HashMap[String, Int]
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// 从指定的值初始化 Map（方式一）
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val scores02 = Map("hadoop" -> 10, "spark" -> 20, "storm" -> 30)
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// 从指定的值初始化 Map（方式二）
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val scores03 = Map(("hadoop", 10), ("spark", 20), ("storm", 30))
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```
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采用上面方式得到的都是不可变 Map(immutable map)，想要得到可变 Map(mutable map)，则需要使用：
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```scala
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val scores04 = scala.collection.mutable.Map("hadoop" -> 10, "spark" -> 20, "storm" -> 30)
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```
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### 1.2 获取值
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```scala
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object ScalaApp extends App {
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val scores = Map("hadoop" -> 10, "spark" -> 20, "storm" -> 30)
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// 1.获取指定 key 对应的值
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println(scores("hadoop"))
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// 2. 如果对应的值不存在则使用默认值
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println(scores.getOrElse("hadoop01", 100))
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}
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```
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### 1.3 新增/修改/删除值
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可变 Map 允许进行新增、修改、删除等操作。
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```scala
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object ScalaApp extends App {
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val scores = scala.collection.mutable.Map("hadoop" -> 10, "spark" -> 20, "storm" -> 30)
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// 1.如果 key 存在则更新
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scores("hadoop") = 100
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// 2.如果 key 不存在则新增
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scores("flink") = 40
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// 3.可以通过 += 来进行多个更新或新增操作
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scores += ("spark" -> 200, "hive" -> 50)
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// 4.可以通过 -= 来移除某个键和值
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scores -= "storm"
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for (elem <- scores) {println(elem)}
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}
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// 输出内容如下
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(spark,200)
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(hadoop,100)
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(flink,40)
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(hive,50)
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```
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不可变 Map 不允许进行新增、修改、删除等操作，但是允许由不可变 Map 产生新的 Map。
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```scala
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object ScalaApp extends App {
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val scores = Map("hadoop" -> 10, "spark" -> 20, "storm" -> 30)
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val newScores = scores + ("spark" -> 200, "hive" -> 50)
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for (elem <- scores) {println(elem)}
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}
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// 输出内容如下
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(hadoop,10)
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(spark,200)
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(storm,30)
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(hive,50)
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```
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### 1.4 遍历Map
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```java
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object ScalaApp extends App {
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val scores = Map("hadoop" -> 10, "spark" -> 20, "storm" -> 30)
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// 1. 遍历键
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for (key <- scores.keys) { println(key) }
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// 2. 遍历值
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for (value <- scores.values) { println(value) }
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// 3. 遍历键值对
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for ((key, value) <- scores) { println(key + ":" + value) }
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}
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```
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### 1.5 yield关键字
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可以使用 `yield` 关键字从现有 Map 产生新的 Map。
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```scala
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object ScalaApp extends App {
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val scores = Map("hadoop" -> 10, "spark" -> 20, "storm" -> 30)
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// 1.将 scores 中所有的值扩大 10 倍
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val newScore = for ((key, value) <- scores) yield (key, value * 10)
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for (elem <- newScore) { println(elem) }
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// 2.将键和值互相调换
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val reversalScore: Map[Int, String] = for ((key, value) <- scores) yield (value, key)
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for (elem <- reversalScore) { println(elem) }
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}
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// 输出
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(hadoop,100)
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(spark,200)
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(storm,300)
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(10,hadoop)
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(20,spark)
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(30,storm)
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```
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### 1.6 其他Map结构
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在使用 Map 时候，如果不指定，默认使用的是 HashMap，如果想要使用 `TreeMap` 或者 `LinkedHashMap`，则需要显式的指定。
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```scala
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object ScalaApp extends App {
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// 1.使用 TreeMap,按照键的字典序进行排序
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val scores01 = scala.collection.mutable.TreeMap("B" -> 20, "A" -> 10, "C" -> 30)
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for (elem <- scores01) {println(elem)}
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// 2.使用 LinkedHashMap,按照键值对的插入顺序进行排序
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val scores02 = scala.collection.mutable.LinkedHashMap("B" -> 20, "A" -> 10, "C" -> 30)
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for (elem <- scores02) {println(elem)}
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}
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// 输出
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(A,10)
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(B,20)
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(C,30)
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(B,20)
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(A,10)
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(C,30)
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```
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### 1.7 可选方法
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```scala
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object ScalaApp extends App {
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val scores = scala.collection.mutable.TreeMap("B" -> 20, "A" -> 10, "C" -> 30)
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// 1. 获取长度
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println(scores.size)
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// 2. 判断是否为空
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println(scores.isEmpty)
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// 3. 判断是否包含特定的 key
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println(scores.contains("A"))
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}
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```
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### 1.8 与Java互操作
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```scala
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import java.util
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import scala.collection.{JavaConverters, mutable}
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object ScalaApp extends App {
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val scores = Map("hadoop" -> 10, "spark" -> 20, "storm" -> 30)
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// scala map 转 java map
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val javaMap: util.Map[String, Int] = JavaConverters.mapAsJavaMap(scores)
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// java map 转 scala map
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val scalaMap: mutable.Map[String, Int] = JavaConverters.mapAsScalaMap(javaMap)
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for (elem <- scalaMap) {println(elem)}
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}
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```
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## 二、元组(Tuple)
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元组与数组类似，但是数组中所有的元素必须是同一种类型，而元组则可以包含不同类型的元素。
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```scala
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scala> val tuple=(1,3.24f,"scala")
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tuple: (Int, Float, String) = (1,3.24,scala)
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```
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### 2.1 模式匹配
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可以通过模式匹配来获取元组中的值并赋予对应的变量：
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```scala
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scala> val (a,b,c)=tuple
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a: Int = 1
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b: Float = 3.24
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c: String = scala
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```
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如果某些位置不需要赋值，则可以使用下划线代替：
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```scala
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scala> val (a,_,_)=tuple
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a: Int = 1
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```
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### 2.2 zip方法
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```scala
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object ScalaApp extends App {
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val array01 = Array("hadoop", "spark", "storm")
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val array02 = Array(10, 20, 30)
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// 1.zip 方法得到的是多个 tuple 组成的数组
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val tuples: Array[(String, Int)] = array01.zip(array02)
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// 2.也可以在 zip 后调用 toMap 方法转换为 Map
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val map: Map[String, Int] = array01.zip(array02).toMap
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for (elem <- tuples) { println(elem) }
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for (elem <- map) {println(elem)}
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}
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// 输出
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(hadoop,10)
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(spark,20)
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(storm,30)
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(hadoop,10)
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(spark,20)
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(storm,30)
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```
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## 参考资料
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1. Martin Odersky . Scala 编程 (第 3 版)[M] . 电子工业出版社 . 2018-1-1
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2. 凯.S.霍斯特曼 . 快学 Scala(第 2 版)[M] . 电子工业出版社 . 2017-7
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