spark sample programs in scala

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(upgraded) Spark from beginner to proficient (Scala programming, Case combat, advanced features, spark core source profiling, Hadoop high end)

using dynamic resource allocation 2nd 43 Talk-spark Operations Management advanced-Job Resource Scheduling-experiment: Using dynamic resource allocation in yarn mode No. 244 talk-spark Operations Management advanced-Job resource scheduling-Multiple Job resource scheduling principles NO. 245-spark Operations Management Advanced-Job resource scheduling-fair Schedu

Spark official documentation-write and run scala programs locally

must be set. The installation path is used to determine which several nodes Spark runs. The jar name will enable Spark to automatically transmit jar files to slave nodes.This program file relies on Spark APIs, so we must have an sbt configuration file to describe the dependencies between the program and Spark. The fol

Spark Large Data Chinese word segmentation statistics (c) Scala language to achieve word segmentation statistics __spark

change is to add a word to the statistical results according to the frequency of the sorting function: Added by Dumbbell Yang at 2016-07-24Wordcounts.sortby (x => x._2, False, WordCounts.partitions.size) You can compare Java methods to implement sorting, Exchange keys and value, sort, and then switch back in the tedious, Scala language is indeed very convenient. After the above changes, spark Chinese word

Spark Big Data Chinese Word segmentation Statistics (iii) Scala language implementation segmentation statistics

, WordCounts.partitions.size)You can compare Java methods to achieve sorting, Exchange key and value, sort, and then swap back the tedious, Scala language is really handy for a lot. After the above changes, spark Chinese word segmentation statistics can be called from the Main method, such as the original call in the associated object: /** * Use Scala to dev

Eclipse Builds Maven+scala+spark Engineering _spark

from its pom.xml, it is based on scala-2.11.5. There is only one code file, which is Xmlhelloworld.scala. As long as you can smoothly pull to the pom.xml in the dependency pack, you can directly right-click Xmlhelloworld.scala, Run as-> Scala application. At this point, Ecipse+scala+maven was built. Next, configure the spark

Intellij idea uses Maven to build the Spark development environment (Scala)

Val sc=new Sparkcontext (CONF) //The statement above is equivalent to Val sc=new sparkcontext ("local", "Testrdd") val data=sc.textfile ("e:// Hello.txt ")//Read local file data.flatmap (_.split (" "))//underscore is a placeholder, FlatMap is a way to manipulate rows, splitting the data that is being read in . Map ((_,1))// Convert each item to Key-value, and the data is Key,value is 1 . Reducebykey (_+_)//combine items with the same key into one . Col

Scala pattern matching, type system and spark source reading

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

Getting started with spark to Mastery-(section II) Scala programming detailed basic syntax

What is Scala?  S-Cala is a language designed to achieve scaleable language. Officially, it is called the mixed language of object-oriented language and functional language.Scala can be seamlessly spliced with Java programs, because Scala files are compiled as. class files and run on the JVM.Spark was developed by Scala.Scala installation?  Here's the process of

Scala in Spark basic operation not finished

[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

Spark junk e-mail classification (Scala+java)

("")))Val hamfeatures = ham.map (email + tf.transform (email.split ("")))Create labeledpoint datasets for positive (spam) and negative (ham) examples.Val positiveexamples = spamfeatures.map (features = Labeledpoint (1, features))Val negativeexamples = hamfeatures.map (features = Labeledpoint (0, features))Val Trainingdata = positiveexamples + + negativeexamplesTrainingdata.cache ()//cache data since Logistic Regression is an iterative algorithm.Create a Logistic Regression learner which uses th

Spark Scala Demo

file system, read the file from HDFs by default classification and function of spark operators value type transformation operator input partition and output partition one-to- one Map FlatMap mappartitions Glom input partition and output partition many-to-one type Union Cartesian input partition and output partition Many-to-many types GroupBy output partition as input partition subset type Filter distinct Subtract

Spark Java Sample Code WordCount

WordCount written by Java"). Setmaster ("local")); /*** 2nd step: Create a Sparkcontext Object * Sparkcontext is the only entry for all the functions of the Spark program, whether in Scala, Java, Python *, R, etc. must have a sparkcontext (different Language specific class name is different, if Java is javasparkcontext) * Sparkcontext Core role: Initialize the Spark

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