大数据最火爆语言Scala光速入门

scala 可以使用java的库
scala 的工厂方法：apply
条件表达式有返回值
数组可以用to ，箭头 <-
最后一行内容的值是整个代码块的返回值
def函数定义函数，调用不按顺序
函数：def 函数名，参数名：类型名，可以设定默认值，后可跟=号，如def f1 ( param1:String, param2: Int = 30) = param1 + param2
有默认值的参数调用时可以不加参数，另外调用时如果指定参数名的话可以不考虑参数顺序。
参数数量可变：def sum(numbers:Int*) *表示变长调用时不可sum(0 to 100) ,因为0 to 100是range类型，而参数中要求是变量，但是可以用 0 to 100 _* ，表示变成多个值

过程：无返回值的函数，定义函数返回值为Unit，在参数列表之后加上:Unit ,或者将函数定义后的=改变成花括号

lazy 类型：第一次被定义时计算

异常

try {val content = fromFile("/usr/local/spark/sfijweoijgr/")
}catch{case _: FileNotFoundException => println("Ooooops!!! File not found")
} finally {println("Byebye world!")
}

集合
数组val arr = new ArrayInt

ArrayBuffer的insert，remove方法

scala> val arr1 = Array("Scala","Spark")
arr1: Array[String] = Array(Scala, Spark)scala> val arr1 = Array.apply("Scala","Spark")
arr1: Array[String] = Array(Scala, Spark)scala> Array
res3: Array.type = scala.Array$@54d18072scala> arr1(2) = "Hadoop"
java.lang.ArrayIndexOutOfBoundsException: 2... 33 elidedscala> val arrbuf = ArrayBuffer[Int]()
<console>:7: error: not found: value ArrayBufferval arrbuf = ArrayBuffer[Int]()^scala> import scala.collection.mutable.A
AVLIterator      AbstractIterable   AbstractSet   ArrayBuilder   ArraySeq
AVLTree          AbstractMap        AnyRefMap     ArrayLike      ArrayStack
AbstractBuffer   AbstractSeq        ArrayBuffer   ArrayOps                    scala> import scala.collection.mutable.Array
ArrayBuffer   ArrayBuilder   ArrayLike   ArrayOps   ArraySeq   ArrayStackscala> import scala.collection.mutable.ArrayBu
ArrayBuffer   ArrayBuilderscala> import scala.collection.mutable.ArrayBuffer
import scala.collection.mutable.ArrayBufferscala> val arrbuf = ArrayBuffer[Int]()
arrbuf: scala.collection.mutable.ArrayBuffer[Int] = ArrayBuffer()scala> arrbuf += 10
res5: arrbuf.type = ArrayBuffer(10)scala> arrbuf
res6: scala.collection.mutable.ArrayBuffer[Int] = ArrayBuffer(10)scala> arrbuf(1)
java.lang.IndexOutOfBoundsException: 1at scala.collection.mutable.ResizableArray$class.apply(ResizableArray.scala:43)at scala.collection.mutable.ArrayBuffer.apply(ArrayBuffer.scala:48)... 33 elidedscala> arrbuf += ( 12,23,35,56)
res8: arrbuf.type = ArrayBuffer(10, 12, 23, 35, 56)scala> arrbuf
res9: scala.collection.mutable.ArrayBuffer[Int] = ArrayBuffer(10, 12, 23, 35, 56)scala> arrbuf ++= Array（1,2,3,4)
<console>:1: error: illegal character '\uff08'arrbuf ++= Array（1，,2,3,4)^
<console>:1: error: illegal character '\uff0c'arrbuf ++= Array（1，,2,3,4)^scala> arrbuf ++= Array(1,2,3,4)
res10: arrbuf.type = ArrayBuffer(10, 12, 23, 35, 56, 1, 2, 3, 4)scala> arrbuf
res11: scala.collection.mutable.ArrayBuffer[Int] = ArrayBuffer(10, 12, 23, 35, 56, 1, 2, 3, 4)scala> arrbuf.t
tail        takeWhile   toIndexedSeq   toMap      toString        transpose
tails       to          toIterable     toSeq      toTraversable   trimEnd
take        toArray     toIterator     toSet      toVector        trimStart
takeRight   toBuffer    toList         toStream   transform                   scala> arrbuf.t
tail        takeWhile   toIndexedSeq   toMap      toString        transpose
tails       to          toIterable     toSeq      toTraversable   trimEnd
take        toArray     toIterator     toSet      toVector        trimStart
takeRight   toBuffer    toList         toStream   transform                   scala> arrbuf.trim
trimEnd   trimStartscala> arrbuf.trim
trimEnd   trimStartscala> arrbuf.trimEnd(3)scala> arrbuf
res13: scala.collection.mutable.ArrayBuffer[Int] = ArrayBuffer(10, 12, 23, 35, 56, 1)scala> arrbuf
res14: scala.collection.mutable.ArrayBuffer[Int] = ArrayBuffer(10, 12, 23, 35, 56, 1)scala> arrbuf.in
indexOf        indexWhere   init    insert      intersect
indexOfSlice   indices      inits   insertAll               scala> arrbuf.insert(4,100)scala> arrbuf
res16: scala.collection.mutable.ArrayBuffer[Int] = ArrayBuffer(10, 12, 23, 35, 100, 56, 1)scala> arrbuf.insert(6,7,8,9)scala> arrbuf
res18: scala.collection.mutable.ArrayBuffer[Int] = ArrayBuffer(10, 12, 23, 35, 100, 56, 7, 8, 9, 1)scala> arrbuf.remove(0)
res19: Int = 10scala> arrbuf
res20: scala.collection.mutable.ArrayBuffer[Int] = ArrayBuffer(12, 23, 35, 100, 56, 7, 8, 9, 1)scala> arrbuf.remove(1,2)scala> arrbuf
res22: scala.collection.mutable.ArrayBuffer[Int] = ArrayBuffer(12, 100, 56, 7, 8, 9, 1)scala> val arr2 = arrbuf.toArray
arr2: Array[Int] = Array(12, 100, 56, 7, 8, 9, 1)scala> arr2.toBuffer
res23: scala.collection.mutable.Buffer[Int] = ArrayBuffer(12, 100, 56, 7, 8, 9, 1)scala> arr2.toStringdef toString(): Stringscala> arr2.toBuffer
res24: scala.collection.mutable.Buffer[Int] = ArrayBuffer(12, 100, 56, 7, 8, 9, 1)scala> for ( elem <- arr2) { elem}scala> for ( elem <- arr2) {println(elem)}
12
100
56
7
8
9
1scala> for( i <- 1 until (arr2.length,1)) println(arr2(i))
100
56
7
8
9
1scala> for( i <- 1 until (arr2.length,2)) println(arr2(i))
100
7
9scala> for( i <- 0 until (arr2.length,2)) println(arr2(i))
12
56
8
1scala> for( i <- 0 until (arr2.length,2)) println(arr2(i))
12
56
8
1scala> arr2
res31: Array[Int] = Array(12, 100, 56, 7, 8, 9, 1)scala> for(i <- (0 until arr2.length).reverse) println(arr2(i))
1
9
8
7
56
100
12scala> import scala.util.Sorting._
import scala.util.Sorting._scala> quickSort(arr2)scala> arr2
res34: Array[Int] = Array(1, 7, 8, 9, 12, 56, 100)scala> val arr3 = for(i <- arr2) yield i*i
arr3: Array[Int] = Array(1, 49, 64, 81, 144, 3136, 10000)scala> val arr4 = for(i <- arr2 if i%3 == 0) yield i*i
arr4: Array[Int] = Array(81, 144)scala>  arr2.filter(_%3 ==0).map(i => i*i)
res35: Array[Int] = Array(81, 144)scala>  arr2.filter{_%3 ==0}.map{i => i*i}
res36: Array[Int] = Array(81, 144)scala>  arr2.filter{_%3 ==0}map{i => i*i}
res3: Array[Int] = Array(144, 81)

yield 把后面的每一个元素收集起来并组拼成一个集合

作业：删掉数组中第一个负数后面的所有负数

scala> val person = Map("Spark" ->6, "Hadoop" -> 11)
person: scala.collection.immutable.Map[String,Int] = Map(Spark -> 6, Hadoop -> 11)scala> person("Hadoop")
res4: Int = 11scala> val person = scala.collection.mutable.Map("Spark" ->6, "Hadoop" -> 11)
person: scala.collection.mutable.Map[String,Int] = Map(Hadoop -> 11, Spark -> 6)scala> person += ("Flink" -> 5)
res5: person.type = Map(Hadoop -> 11, Spark -> 6, Flink -> 5)scala> person -= "Flink"
res6: person.type = Map(Hadoop -> 11, Spark -> 6)scala> val sparkValue = if (person.contains("Spark")) person("Spark") else 1000
sparkValue: Int = 6scala> val sparkValue = person.getOrElse
getOrElse   getOrElseUpdatescala> val sparkValue = person.getOrElse("Spark", 1000)
sparkValue: Int = 6scala> val sparkValue = person.getOrElse("Flink", 1000)
sparkValue: Int = 1000scala> for((key,value) <- person) println(key+":"+value)
Hadoop:11
Spark:6scala> for((key,value) <- person) println(key+":")
Hadoop:
Spark:scala> val person = scala.collection.mutable.S.Map("Spark" ->6, "Hadoop" -> 11)
Seq          SetProxy        Subscriber                  SynchronizedSet
SeqLike      SortedSet       SynchronizedBuffer          SynchronizedStack
Set          Stack           SynchronizedMap
SetBuilder   StackProxy      SynchronizedPriorityQueue
SetLike      StringBuilder   SynchronizedQueue                               scala> val person = scala.collection.immutable.S.Map("Spark" ->6, "Hadoop" -> 11)
Seq   SetProxy    SortedSet   Stream           StreamView       StringLike
Set   SortedMap   Stack       StreamIterator   StreamViewLike   StringOps    scala> val person = scala.collection.immutable.SortedMap("Spark" ->6, "Hadoop" -> 11)
person: scala.collection.immutable.SortedMap[String,Int] = Map(Hadoop -> 11, Spark -> 6)TUPLE：
scala> val tuple = ("Spark", 6, 99.0)
tuple: (String, Int, Double) = (Spark,6,99.0)scala> tuple._1
res9: String = Sparkscala> tuple._2
res10: Int = 6scala> tuple._3
res11: Double = 99.0

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大数据最火爆语言Scala光速入门

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