spark scala course

How to build a spark development environment using MAVEN step-by-step in IntelliJ idea, and write a simple wordcount instance of Spark based on Scala. 1. Preparatory workFirst you need to install JDK and Scala and development tools on your computer IntelliJ idea, this article uses the Win7 system, the environment is co

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:

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

This article first describes how to configure the Maven+scala development environment in Eclipse, and then describes how to implement the spark local run. Finally, the spark program written by Scala is successfully run. At first, my Eclipse+maven environment was well configured. System: Win7 Eclipse version: Luna rele

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 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

Quick StartThis article describes how to use scala, java, and python to compile a spark click Mode Program. First, you only need to successfully build Spark on a machine. Practice: Enter the Spark root directory and enter the command: $ sbt/sbt package(Because of the Great Firewall of tianchao, the mainland China canno

data source:The second step, flatmap operation:The third step, map operation:Fourth step, reduce operation:The fifth step, print () and other operations:Sixth step: awaittermination operationSummarize:With spark streaming you can handle a variety of data source types, such as database, HDFS, server log logs, network streams, which are more powerful than you might imagine, but are often not used by people, and the real reason for this is the

imagine, but are often not used by people, and the real reason for this is the spark, spark Streaming itself does not understand.Note:Data from: Dt_ Big Data DreamWorks (the fund's legendary action secret course)For more private content, please follow the public number: Dt_sparkIf you are interested in big data spark,

Learn Spark 2.0 (new features, real projects, pure Scala language development, CDH5.7)Share--https://pan.baidu.com/s/1jhvviai Password: SirkStarting from the basics, this course focuses on Spark 2.0, which is focused, concise and easy to understand, and is designed to be fast and flexible.The

Preface:　　　　Recently in the research Spark also has Kafka, wants to pass the data which the Kafka end obtains, uses the spark streaming to carry on some computation, but constructs the entire environment is really not easy, therefore hereby writes down this process, shares to everybody, hoped that everybody may take a little detour, can help everybody!Environment Preparation:operating system: ubuntu14.04 LT

Spark provides an interactive shell that enables us to point to point (Original: ad hoc) data analysis. If you've already used R,python, or a shell in Scala, or an operating system shell (such as bash), or a Windows command prompt, you'll be familiar with Spark's shell.But in fact, the spark shell is different from most other shells, and most of the other shells

://master. Hadoop:8390/gradient_data/spam.data.txt ") Val Lines=Text.map { line=Line.split (" "). Map (_.todouble)} Val points= Lines.map (Parsepoint (_))//(Parsepoint (_)) looks the samevar w = Densevector.rand (Lines.first (). size-2) Val iterations= 100 for(I to iterations) {val Gradient= Points.map (P = = (1/(1 + exp (-P.Y * (w dot p.x)))-1) * P.Y *p.x). Reduce (_+_) W-=gradient} println ("Finish data loading, W num:" + w.length + "; W: "+W)}}Then on the M42n05 machine, the first use

Install jdk1.7.0_60 and scala2.10.4 on the development machine and configure the relevant environment variables. Many online data, installation process ignored. In addition, Eclipse uses Luna4.4.1,idea to use the 14.0.2 version.1. Eclipse Development Environment Building1.1. Install the Scala pluginInstalling the Eclipse-scala-plugin plug-in, http://scala-ide.org

Lesson 2nd: Scala's object-oriented mastery and spark source readingContents of this issue:1 Scala's class, object in real combat2 abstract classes and interfaces in Scala3 comprehensive case and spark source code analysisOne: Define ClassClass hiscala{private var name = "Spark"Def sayname () {println (name)}def getName = Name}In

(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