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Java switch-case (pair value)Scala is not only for values, but also for types, collections (map,list metadata matching), Object,classScala uses a lot of pattern matching (Match case)Scala's pattern match, which differs from the Java switch case:1. Not only can match the value, can match type2. Can match the collection of arraysAn array of the same array, the same length, and an array beginning with an elementAutomatic variable assignment for arrays of
variable, advanced and post - ImportScala.collection.mutable.Stack Val Stack=NewStack[int] Stack.push (1) Stack.push (2) Stack.push (3) println (stack.top) println (Stack) println (stack.pop) println (Stack)Set, Map, TreeSet, TREEMAP related operations1.Set, Map related operations: Set and map elements are mutable variable is also unordered2.TreeSet, TreeMap related operations: TreeMap and TreeSet can be used to sort theImportscala.collection.mutableImportScala.collection.mutable.TreeSetImpo
= "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!The latest big Data video 74 spea
: There are several implicit packages in Scala, such as the Java.lang._,scala._,predef_ three packages, which are like several common packages in Java and have many tool methods. about access permissions for packages, classes, objects, members, associated classes, and associated objects in Scala Access rights for packages, classes, objects, Members:
After building the Scala and Spark development environment, I couldn't wait to run the Scala program based on Spark, so I found a link to Spark's official website (http://spark.apache.org/docs/latest/ quick-start.html), describes how to run a Scala program. The detailed proc
crossvalidator is very high, however, compared with heuristic manual validation, cross-validation is still a very useful parameter selection method in existence. Scala: Import org.apache.spark.ml.Pipeline Import org.apache.spark.ml.classification.LogisticRegression Import Org.apache.spark.ml.evaluation.BinaryClassificationEvaluator import org.apache.spark.ml.feature. {HASHINGTF, tokenizer} import org.apache.spark.ml.linalg.Vector import org.apache.s
Package Com.leegh.parameterizationImport Scala.reflect.ClassTag/*** @author Guohui Li*/Class A[t]Object Manifest_classtag {def main (args:array[string]): Unit = {def Arraymake[t:manifest] (first:t, second:t) = {Val r = new Array[t] (2); R (0) = first; R (1) = second; R}Arraymake (1, 2). foreach (println)/** Common classtag*/def Mkarray[t:classtag] (elems:t*) = Array[t] (elems: _*)Mkarray (a). foreach (println)Mkarray ("Japan", "Brazil", "Germany"). foreach (println)Val m = manifest[a[string]]pri
As a beginner, first learn spark, share your own experience. In learning Spark programming, the first to prepare the compilation environment, to determine the programming language, I used the Scala language, IntelliJ idea of the compilation environment, at the same time have to prepare four packages, respectively: Spark
SparkstreamingcontextWe create Sparkstreamingcontext objects in a configuration-based manner:The third step is to create the spark streaming input data source:We configure the data source as local port 9999 (note that port requirements are not being used):Fourth step: As with the RDD programming, we program based on Dstream, because Dstream is the template that the RDD generates, and before spark streaming
Contents of this lesson:A thorough explanation of functional programming in 1:scalaScala functional programming in the 2:spark source code3: Cases and jobsFunctional Programming Begins:def fun1 (name:string) {println (name)}Assign a function name to a variable, then this variable is a function.Val Fun1_v = fun1_Visit Fun1_v ("Scala")Result: Scalaanonymous function: Parameter name = = point to function bodyV
was successful. This is followed by some basic grammar learning in Scala. val Variable declaration: declares a Val variable to hold the expression's computed result, which is immutable.Val result = 1 + 1 Subsequent constants are available for continuation, Eg:2 * result However, the Val constant declaration does not change its value, otherwise it returns an error. var variable declaration: DECLARE var variable, can change the refere
next three numbers, the first two means that SQL parameters, must be a long type, and must have, this is the spark source code requirements, if there is no long type of condition, you can use 1=1 this parameter (the third parameter is 1) The third parameter represents a partitioned query, for example, given the first two parameters of 1 and 20, the third parameter is 2, then SQL executes two times, the first parameter is (1, 10), the second is (11, 2
Listen to Liaoliang's Spark 3000 disciple series lesson four Scala pattern matching and type parameters, summarized as follows:Pattern matching:def data (array:array[string]) {Array match{Case Array (a,b,c) = println (A+b+c)Case Array ("Spark", _*) =//matches an array with spark as the first elementCase _ = ...}}After-
First, spark frame previewMainly have Core, GraphX, MLlib, spark streaming, spark SQL and so on several parts.GRAPHX is a graph calculation and graph mining, in which the mainstream diagram calculation framework now has: Pregal, HAMA, giraph (these parts are in the form of hyper-step synchronization), and Graphlab and Spark
Today is mainly about the list in Scala, list in Scala should be very important, next will explain the list of a series of operationsList map, FlatMap, foreach, filter operations explained1. About the list map, flatmap operation, Difference2. foreach, filter operation on List //a function expression is used in the map in list----but it is an operation on the list, which can represent a function or expres
* @param spark*/ Private Static voidDynamictransform (Sparksession Spark) {Javardd"StuInfo.txt"). Javardd (); Javardd{string[] parts= Line.split (","); String Sid= parts[0]; String sname= parts[1]; intSage = Integer.parseint (parts[2]); returnrowfactory.create (SID, Sname, Sage ); }); ArrayListNewArraylist(); Structfield Field=NULL; Field= Datatypes.createstructfield ("Sid"
Due to the natural compliance with the needs of many scenes in the Internet, graph computing is being favored more and more. Spark GraphX is a member of the Spark technology stack and takes on the responsibility of spark in the field of graph computing. There are already a lot of graphs and Spark GraphX concepts on the
Spark version: 2.0.1 Most recently, when you submitted a task in the Scala language with spark, the submit task always fails, and the exception is as follows: 17/05/05 18:39:23 ERROR yarn. Applicationmaster:user class threw Exception:java.lang.NoSuchMethodError: Scala.reflect.api.JavaUniverse.runtimeMirror (ljava/lang/classloader;) lscala/reflect/api/javamirro
[Introduction to Apache spark Big Data Analysis (i) (http://www.csdn.net/article/2015-11-25/2826324) Spark Note 5:sparkcontext,sparkconf Spark reads HBase Scala's powerful collection data operations example Some RDD operations and transformations in spark # Create Textfilerdd val textfile = Sc.textfile ("readme.md") Te
PrefaceWork today to see a lot about the front js,jquery, Bootstrap.js and Springmvc see vaguely, after all, rarely to learn the front-end technology, all see a bit sleepy, good to see more, go home also began to learn about the Scala related courses, experiment every day to stick to big data related things, what will become after a year ...... Look forward to ..., and today goes on yesterday's course.Scala Insider in real-class practical explanationI
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