Big Data series cultivation-scala Course 07

Because yesterday after work a bit sleepy, did not come and write a blog, today will fill it up! Keep this habit going!

More about Scala's higher-order functions

1.Scala High-order function code implementation: higher-order functions are applied in our functions

2. Higher-order function code details: higher-order functions can make method invocation more convenient

println ("Welcome to the Scala worksheet")//> Welcome to the SCALA worksheet//(1 to 9) The map method in the array is placed in the array * using foreach to loop println _ to represent the function, passing the function as a parameter(1 to 9). Map ("*" * _). foreach (println _)//> *//| **                                                  //| ***                                                  //| ****                                                  //| *****                                                  //| ******                                                  //| *******                                                  //| ********                                                  //| *********  //traversal println, which is divisible by 2 after filtering, is also passed as a parameter, which is the higher order function.(1 to 9). Filter (_% 2 = = 0). foreach (println)//> 2//| 4//| 6//| 8//_*_ represents the multiplication of two data in an array also belongs to the higher order functionprintln ((1 to 9). Reduceleft (_ * _))//> 362880//divide a string into a space by its length"Spark is the most exciting thing happening in big data Today". Split (""). Sortwith (_.length<_.length). foreach (println)//> is//| in//| the//| Big//| most//| data//| Spark//| thing//| Today//| exciting//| Happening//The ceil function represents an upward valueVal Fun = Ceil _//> fun:double = Double = <function1>Val num = 3.14//> num:double = 3.14Fun (num)//> res0:double = 4.0Array (3.14, 1.42, 2.0). Map (Fun)//The fun function is passed as a function//> Res1:array[double] = Array (4.0, 2.0, 2.0)//function represents a multiple of threeval triple = (x:double) = 3 * x//> triple:double = Double = <function1>Array (3.14, 1.42, 2.0). Map (x:double) = 3 *x)//> Res2:array[double] = Array (9.42, 4.26, 6.0)Array (3.14, 1.42, 2.0). map{(x:double) = 3 *x}//> Res3:array[double] = Array (9.42, 4.26, 6.0)//defining higher order functionsDef high_order_functions (f: (double) + = double) = f (0.25)                                                  //> High_order_functions: (f:double = double) Doubleprintln (High_order_functions (ceil _))//> 1.0println (High_order_functions (sqrt _))//> 0.5//function Multiplicationdef mulby (factor:double) = (x:double) = factor *x//> Mulby: (factor:double) Double = DoubleVal quintuple = Mulby (5)//> quintuple:double = Double = <function1>println (Quintuple (20))//> 100.0//Multiple resolution of 3println (high_order_functions (x:double) = 3 *x))//> 0.75High_order_functions ((x) = 3 * x)//> res4:double = 0.75High_order_functions (x = 3 * x)//> res5:double = 0.75println (High_order_functions (3 * _))//> 0.75Val fun2= 3 * (_: Double)//> fun2:double = Double = <function1>Val fun3: (double) = = Double = 3 * _//> fun3:double = Double = <function1>

Sam Conversion tutorials in Scala

The meaning of 1.SAM: implicit conversion

2.SAM conversion in a detailed

var data = 0Val Frame=NewJFrame ("SAM testing"); Val JButton=NewJButton ("Counter") Jbutton.addactionlistener (NewActionListener {override def actionperformed (event:actionevent) {data+ = 1println (data)}) //implicit functions define functions like function definitions in Java--and this can be implicitly convertedImplicit def convertedaction (action: (actionevent) = Unit) =NewActionListener {override def actionperformed (event:actionevent) {action}}//This is when the code is written only to care about business logic, there is no need to write the non-relational code, directly write the desired resultsJbutton.addactionlistener ((event:actionevent) = {Data + = 1; println (data)}) //this is the same as GUI programming in Java.Frame.setcontentpane (JButton);      Frame.pack (); Frame.setvisible (true);

curring in Scala

Definition of 1.curring:curring particle size, is to simplify the parameter into one parameter to operate, return to the other calculation

2.curring importance in the project: very important in the push-to-neutralize calculation of the formula

    // curring particle size, is to simplify the parameter into one parameter to operate, return to the other calculation    def multiple (x:int, y:int) = x * y    = (y:int) + x * y    println (Multipleone (6) (7))    /c8>// can put the above calculation method for the following methods    def curring (X:int) (Y:int) = x * y        println (curring ( (Ten    )) = Array ("Hello", "Spark"    )= Array ("Hello", "Spark")     // compare two variables for equality    println (a.corresponds (b) (_.equalsignorecase (_)))

Getting started with pattern matching in Scala

1. Pattern matching analysis: Scala matching mode is flexible, can pass in parameters and functions, etc.

2. Use guard in pattern matching: The next blog will be explained in depth

3. Use of variables in pattern matching

  //pattern matching is represented in Java with a switch, which is not a lot of restrictions, Int,byte,char,shortVal Data =2Data Match { Case1 = println ("First")       Case2 = println ("Second")       Case_ = = println ("Not known number")    }    //In Scala, you can use conditional functions or functions, or you can pass argumentsVal result =Data Match { CaseIifi = = 1 = "The first" CaseNumberifNumber ==2 = "The Second" + Number Case_ = "not known number"} println (Result)"Spark!" foreach {c = =println (c match { Case' = ' and ' space ' Casech = "Char:" +ch})}

This is a default task, and today we will write another study on Scala! I hope you are concerned about Liaoliang Teacher's (18610086859), he will update the big Data video every day!

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Big Data series cultivation-scala Course 07