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Spark Big Data Video tutorial install SQL streaming Scala Hive Hadoop

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"Spark Asia-Pacific Research series" Spark Combat Master Road-2nd Chapter hands-on Scala 3rd bar: Hands-on practical Scala Functional Programming (2)

3, hands-on generics in Scalageneric generic classes and generic methods, that is, when we instantiate a class or invoke a method, you can specify its type, because Scala generics and Java generics are consistent and are not mentioned here. 4, hands on. Implicit conversions, implicit parameters, implicit classes in Scalaimplicit conversion is one of the key points that many people learn about Scala, which i

"Spark Asia-Pacific Research series" Spark Combat Master Road-2nd Chapter hands-on Scala 3rd bar: Hands-on practical Scala Functional Programming (1)

none, and below we look at the use of option: Next, take a look at filter processing: Here's a look at the zip operation for the collection: Here's a look at the partition of the collection: We can use flatten's multi-collection for flattening operations: Flatmap is a combination of map and flatten operations, first map operation and then flatten operation: "Spark Asia-Pacific Research ser

"Spark Asia-Pacific Research series" Spark Combat Master Road-2nd Chapter hands-on Scala 2nd bar: Hands-on Scala object-oriented programming (2)

3, hands on the abstract class in ScalaThe definition of an abstract class requires the use of the abstract keyword: The above code defines and implements the abstract method, it is important to note that we put the direct running code in the trait subclass of the app, about the inside of the app helps us implement the Main method and manages the code written by the engineer;Here's a look at the use of uninitialized variables in an abstract class: 4, hands-on trait in ScalaTrait

Apache Spark Learning: Developing spark applications using Scala language _apache

The spark kernel is developed by the Scala language, so it is natural to develop spark applications using Scala. If you are unfamiliar with the Scala language, you can read Web tutorials A Scala

Build the Spark stand-alone development environment in Ubuntu16.04 (JDK + Scala + Spark)

1. PreparationThis article focuses on how to build the Spark 2.11 stand-alone development environment in Ubuntu 16.04, which is divided into 3 parts: JDK installation, Scala installation, and spark installation. JDK 1.8:jdk-8u171-linux-x64.tar.gz Scala 11.12:scala

Spark 2.0 Video | Learn Spark 2.0 (new features, real projects, pure Scala language development, CDH5.7)

Learn Spark 2.0 (new features, real projects, pure Scala language development, CDH5.7)Share the network disk download--https://pan.baidu.com/s/1c2f9zo0 password: pzx9Spark entered the 2.0 era, introducing many excellent features, improved performance, and more user-friendly APIs. In the "unified programming" is very impressive, the implementation of offline computing and Flow computing API unification, the

The first solution, the mechanism of actor-based concurrent programming in the Scala language, and shows the use of the message-driven framework Akka generated by the Scala language actor in Spark,

Scala Beginner's intermediate-Advanced Classic (66th: Scala concurrent programming experience and its application in Spark source code) content introduction and video link2015-07-24DT Big Data Dream FactoryFrom tomorrow onwards, be a diligent person.Watch videos, videos, share videosDT Big Data Dream Factory-scala--Adv

"Spark Mllib Express Treasure" basic 01Windows Spark development Environment Construction (Scala edition)

Directory installation JDK installation Scala IDE for Eclipse configuration spark configuration Hadoop create Maven engineering Scala code entry 7 Item 8 Item 9 Installing the JDK Requires installation of jdk1.8 or later.Back to Catalog installing Scala IDE for Eclipse

Scala's extensive application of generic classes, generic functions, generics in Spark, Scala learning notes-33

Package Com.leegh.parameterization/*** @author Guohui Li*/Import Scala.reflect.ClassTagClass Trible[f, S, T] (Val first:f, Val second:s, Val third:t)Object Hello_type_parameterization {def main (args:array[string]): Unit = {val triple = new Triple ("Spark", 3, 3.1415)Val bigdata = new triple[string, String, Char] ("Spark", "Hadoop", ' R ')def Getdata[t] (list:list[t]) = List (LIST.LENGTH/2)println (GetData

Application of implicit parameters in Scala and implicit parameters in spark Code parsing Scala learning notes-50

Package Com.leegh.implicits/*** @author Guohui Li*/Object Context_implicits {Implicit val default:string = "Java"}Object Param {def print (content:string) (implicit language:string) {println (language + ":" + content)}}Object Context_parameters {def main (args:array[string]): Unit = {Param.print ("Spark") ("Scala")Import Context_implicits._Param.print ("Hadoop")}}Report:This blog description:1. Organize you

Scala type constraint code combat and its application in Spark source parsing Scala learning notes-39

Package Com.leegh.parameterization/*** @author Guohui Li*/Object Type_contraints {def main (args:array[string]): Unit = {def Rocky[t] (i:t) (implicit ev:t println ("Life is too short,you need spark!")}Rocky ("Spark")}}Report:This blog description:1. Organize your ideas and improve yourself.2. Be educated in Liaoliang teacher, what to gain, so recommend.3. Blog focus on practice, superfluous words are not mu

Type variable bounds code in Scala and its application in Spark source parsing Scala learning notes-34

Package Com.leegh.parameterization/*** @author Guohui Li*/Class Pair[t def bigger = if (First.compareto (second) > 0) First Else second}Class Pair_lower_bound[t] (Val first:t, Val second:t) {def Replacefirst[r;: T] (newfirst:r) = new Pair_lower_bound[r] (Newfirst, second)}Object Type_variables_bounds {def main (args:array[string]): Unit = {Val pair = new pair ("Spark", "Hadoop")println (Pair.bigger)}}Report:This blog description:1. Organize your ideas

The context bounds code in Scala and its application in Spark source parsing Scala learning notes-36

Package Com.leegh.parameterization/*** @author Guohui Li*/Class Pair_ordering[t:ordering] (Val first:t, Val second:t) {def bigger (implicit ordered:ordering[t]) = {if (Ordered.compare (first, second) > 0) First Else second}}Object Context_bounds {def main (args:array[string]): Unit = {Val pair = new pair_ordering ("Spark", "Hadoop")println (Pair.bigger)Val pairint = new Pair_ordering (3, 5)println (Pairint.bigger)}}Report:This blog description:1. Orga

The implementation code of chained call style in Scala and its extensive application in Spark programming Scala learning notes-41

Package Com.leegh.parameterization/*** @author Guohui Li*/Because breathe returns This,scala the return type is inferred as animal, and because animal has no eat methodClass Animal {def breathe = this}Class Cat extends Animal {def eat = this}Class Animal {def Breathe:this.type = this}Class Cat extends Animal {def eat:this.type = this}Object Singleton_types {def main (args:array[string]): Unit = {Val cat = new CatCat.breathe.eat}}Report:This blog descr

Implicit conversion in Scala Insider operating rules disclosure, best practices and their application in spark source parsing Scala learning notes-55

public number is Dt_spark, every day will have big data actual combat video release, please continue to study.Liaoliang DT Big Data dream factory Scala all videos, PPT and code in Baidu Cloud disk link:http://pan.baidu.com/share/home?uk=4013289088#category/type=0 Qq-pf-to=pcqq.groupLiaoliang "Scala Beginner's introductory classic video course" http://edu.51cto.com/lesson/id-66538.htmlLiaoliang "

The first experience of Scala concurrent programming and its application in spark source code Scala learning notes-56

Package Com.leegh.actorImport Scala.actors.Actor/*** @author Guohui Li*/Object First_actor extends Actor {Def Act () {for (I println ("Step:" + i)println (Thread.CurrentThread (). GetName)Thread.Sleep (2000)}}}Object Second_actor extends Actor {Def Act () {for (I println ("Step further:" + i)println (Thread.CurrentThread (). GetName)Thread.Sleep (2000)}}}Object Hello_actor {def main (args:array[string]): Unit = {First_actor.start ()Second_actor.start ()}}Report:This blog description:1. Organize

Variance code in Scala and its application in spark Code parsing Scala learning notes-40

Package Com.leegh.parameterization/*** @author Guohui Li*/Class PersonClass Student extends PersonClass C[+t] (Val args:t)Trait Friend[-t] {def makefriend (Somebody:t)}Object Variance {def makefriendwithyou (S:student, f:friend[student]) {f.makefriend (s)}def main (args:array[string]): Unit = {Val Value:c[person] = new C[student] (new Student)}}Report:This blog description:1. Organize your ideas and improve yourself.2. Be educated in Liaoliang teacher, what to gain, so recommend.3. Blog focus on

Big Data spark mushroom cloud prequel 16th: Scala implicits programming thorough combat and spark source appreciation (study notes)

implicit object, then import the function of this type, and then the man can also be used under the function of implicit object in the implicit conversion. Implicit parameters, which can be used to transmit the parameters for an implied number of variables.First write a function:def talk (name:string) (implicit content:string) = println (name + ":" + content), the 2nd is an implicit reference, and then the talk-side If there are no implicit parameters, the editor will report it! At this poi

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