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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

"Spark Asia-Pacific Research series" Spark Combat Master Road-2nd Chapter hands-on Scala 2nd bar (3)

5. Apply method and Singleton object in Scala to create a new class: As an additional point, the methods placed in object objects are static methods, as follows: Next look at the use of the Apply method: The above code always when we use "val a = Applytest ()" will cause the call of the Apply method and return the value of the method call, that is, the instantiated object of the applytest. C The lass can also be used by the Apply method, as shown

Introduction to Spark's Python and Scala shell (translated from Learning.spark.lightning-fast.big.data.analysis)

useful for learning APIs, we recommend that you run these examples in one of these two languages, even if you are a Java developer. In each language, these APIs are similar.The simplest way to demonstrate the power of the spark shell is to use them for simple data analysis. Let's start with an example from the Quick Start Guide in the official documentation.The first step is to open a shell. In order to op

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

The collection mainly has list, set, Tuple, map, etc., we follow the hands-on practical way to learn. We create a list instance in the Eclipse IDE: Now let's look at the code implementation: In the source code, it is stated that the internal is the method of apply to complete the instantiation; In the same way we can instantiate set: You can also see the implementation of the set instantiation object at this point: Next we'll look at the set in the command-line terminal, first of all set:

Scala spark-streaming Integrated Kafka (Spark 2.3 Kafka 0.10)

The MAVEN components are as follows: org.apache.spark spark-streaming-kafka-0-10_2.11 2.3.0The official website code is as follows:Pasting/** Licensed to the Apache software Foundation (ASF) under one or more* Contributor license agreements. See the NOTICE file distributed with* This work for additional information regarding copyright ownership.* The ASF licenses this file to under the Apache License, Version 2.0* (the "License"); You are no

Build Scala+spark development environment with Eclipse and idea, respectively

14.0.2. To enable the idea to support Scala development, you need to install the Scala plugin,After the plug-in installation is complete, IntelliJ idea will require a reboot.2.2. Create a MAVEN projectClick Create New Project to select the JDK installation directory in the Project SDK (it is recommended that the JDK version in the development environment be consistent with the JDK version on the

Spark RDD API (Scala)

(transformation) and the Action (action). The main difference between the two types of functions is that transformation accepts the RDD and returns the RDD, while the action accepts the RDD to return the non-rdd.The transformation operation is deferred, meaning that a conversion operation that generates another RDD from an RDD is not performed immediately, and the operation is actually triggered when there is an action action.The action operator triggers sp

Installing Spark and Scala

Tag: Spark installs Scala1. Download SparkHttp://mirrors.cnnic.cn/apache/spark/spark-1.3.0/spark-1.3.0-bin-hadoop2.3.tgz2. Download ScalaHttp://www.scala-lang.org/download/2.10.5.html3. Install ScalaMkdir/usr/lib/scalaTAR–ZXVF scala-2.10.5.tgzMV

Install Scala and Spark in CentOS

Install Scala and Spark in CentOS 1. Install Scala Scala runs on the Java Virtual Machine (JVM). Therefore, before installing Scala, you must first install Java in linux. You can go to my article http://blog.csdn.net/xqclll/article/details/54256713to continue without install

MAC configuration Spark Environment Scala+python version (Spark1.6.0) __python

"Easy_install py4j" command on the line. Then go into the Spark installation directory under the Python folder, open the Lib folder, the inside of the PY4J compression package copied to the next Level Python folder, decompression. 5. Write a good demo in Pycharm, click to run. The demo example is as follows: "" "simpleapp.py" "" from Pyspark import sparkcontext logFile = "/

Lesson 83: Scala and Java two ways to combat spark streaming development

First, the Java Way development1, pre-development preparation: Assume that you set up the spark cluster.2, the development environment uses Eclipse MAVEN project, need to add spark streaming dependency.3. Spark streaming is calculated based on spark core and requires attention:Set local master, you must configure at le

83rd lesson: Scala and Java two ways to combat spark streaming development

for an odd number of cores, for example: Assigning 3, 5, 7 cores, etc.)Next, let's start writing Java code!First step: Create a Sparkconf object650) this.width=650; "Src=" http://images2015.cnblogs.com/blog/860767/201604/860767-20160425230333767-26176125. GIF "style=" margin:0px;padding:0px;border:0px; "/>Step Two: Create Sparkstreamingcontext650) this.width=650; "Src=" http://images2015.cnblogs.com/blog/860767/201604/860767-20160425230457970-4365990

Eclipse creates MAVEN management for Spark's Scala

Description, since Spark was written in Scala. Therefore, it is best to use Scala whether you are looking at the source code or writing spark-related codes. Then, as a programmer, the first thing to do is to sharpen the sword in hand. That's creating a code environment for writing

Spark the common application examples of Scala language __spark

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

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