Running Scala

Translation: Esri Lucas The first paper on the Spark framework published by Matei, from the University of California, AMP Lab, is limited to my English proficiency, so there must be a lot of mistakes in translation, please find the wrong direct contact with me, thanks. (in parentheses, the italic part is my own interpretation) Summary: MapReduce and its various variants, conducted on a commercial cluster on a large scale ...

Spark is a cluster computing platform that originated at the University of California, Berkeley Amplab. It is based on memory calculation, from many iterations of batch processing, eclectic data warehouse, flow processing and graph calculation and other computational paradigm, is a rare all-round player. Spark has formally applied to join the Apache incubator, from the "Spark" of the laboratory "" EDM into a large data technology platform for the emergence of the new sharp. This article mainly narrates the design thought of Spark. Spark, as its name shows, is an uncommon "flash" of large data. The specific characteristics are summarized as "light, fast ...

Spark can read and write data directly to HDFS and also supports Spark on YARN. Spark runs in the same cluster as MapReduce, shares storage resources and calculations, borrows Hive from the data warehouse Shark implementation, and is almost completely compatible with Hive. Spark's core concepts 1, Resilient Distributed Dataset (RDD) flexible distribution data set RDD is ...

Code version: Spark 2.2.0 This article mainly describes a creator running process. Generally divided into three parts: (1) sparkconf creation, (2) Sparkcontext creation, (3) Task execution. If we use Scala to write a wordcount program to count the words in a file, package Com.spark.myapp import Org.apache.spark. {Sparkcontext, Spar ...

1. Introduction to the installation environment hardware environment: Two four cores CPU, 4G memory, 500G hard disk virtual machine. Software Environment: 64-bit http://www.aliyun.com/zixun/aggregation/13835.html ">ubuntu12.04 LTS; host name SPARK1, SPARK2,IP address respectively 1**.1 *.**.***/***。 The JDK version is 1.7. Ha has been successfully deployed on the cluster.

Normally do we need a new programming language? You might think we do not need it. But if you understand the recent trends, your ideas may change. Why did Google use both GO and DART programming languages? Why did IBM, Cray and Red Hat create X10, Chapel and Ceylon respectively? In the future, these 10 programming languages ​​(DART, Ceylon, GO, F # OPA, Fantom, Zimb ...

Serendip is a social music service, used as a http://www.aliyun.com/zixun/aggregation/10585.html "> Music sharing" between friends. Based on the "people to clustering" this reason, users have a great chance to find their favorite music friends. Serendip is built on AWS, using a stack that includes Scala (and some Java), Akka (for concurrency), play framework (for Web and API front-end ...).

Absrtact: 7 years ago, one of the ideas, the success of today's popular social network and microblogging service--twitter. Twitter now has more than 200 million monthly active subscribers, and about 500 million tweets are sent every day. 　　Behind all this is the support of a large number of open source projects. Twitter, known as the "Internet SMS Service", allows users to post no more than 140 tweets, the idea from Twitter's co-founder, Jack Dorsey, which was dubbed "the dumbest Ever" by analysts 7 years ago ...

Serendip is a social music service, used as a http://www.aliyun.com/zixun/aggregation/10585.html "> Music sharing" between friends. Based on the "people to clustering" this reason, users have a great chance to find their favorite music friends. Serendip is built on AWS, using a stack that includes Scala (and some Java), Akka (for concurrency), play framework (for Web and API front-end ...).

Hadoop is a large data distributed system infrastructure developed by the Apache Foundation, the earliest version of which was the 2003 original Yahoo! Doug cutting is based on Google's published academic paper. Users can easily develop and run applications that process massive amounts of data in Hadoop without knowing the underlying details of the distribution. The features of low cost, high reliability, high scalability, high efficiency and high fault tolerance make Hadoop the most popular large data analysis system, yet its HDFs and mapred ...