Scala Source Code

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Twitter: A simple tweet behind the powerful open source power

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 ...

How to carry out the code followed?

Summary Today, we're not talking about complex technical implementations in Spark, just a little bit of code-behind. It's well known that Spark uses scala to develop because scala has lots of syntactic sugar on it, so many times it's time to get back the code and follow it, and Spark is based on information exchanged by Akka, so how do you know each other? Is the recipient? new Throwable (). printStackTrace In the code to read, users often ask for help in the log, reading the log ...

Spark system code to read

Summary Today we only talk about the code to read the method, do not carry out those complicated technical implementation in Spark. Surely we all know that Spark was developed using scala, but because of the large number of syntactic sugars in scala, code often follows and discovers clues. Second, Spark interacts with Akka based on how to know who Recipient it? new Throwable (). printStackTrace In the code following, we often rely on the log, and ...

Spark: A framework for cluster computing on a workgroup

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 ...

Inventory the Hadoop Biosphere: 13 Open source tools for elephants to fly

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 ...

13 Open source tools based on large data analysis system Hadoop

Hadoop is a large data distributed system infrastructure developed by the Apache Foundation, the earliest version of which was the 2003 original Yahoo! Dougcutting 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 mapreduc ...

13 open source tools for big data analytics system Hadoop

This time, we share the 13 most commonly used open source tools in the Hadoop ecosystem, including resource scheduling, stream computing, and various business-oriented scenarios. First, we look at resource management.

Recommended! The machine learning resources compiled by foreign programmers

C + + computer vision ccv-based on C language/provides cache/core machine Vision Library, novel Machine Vision Library opencv-It provides C + +, C, Python, Java and MATLAB interfaces, and supports Windows, Linux, Android and Mac OS operating system. General machine learning Mlpack dlib Ecogg Shark Closure Universal machine learning Closure Toolbox-cloj ...

Twitter Open source Summingbird: Consolidated batch processing and flow processing under near-native coding

Depending on the use scenario, large data processing is gradually evolving to two extremes-batch processing and streaming. The streaming processing pays more attention to the real-time analysis of the data, and represents the storm and S4 of the tools.   and batch processing is more focused on the long-term data mining, the typical tool is derived from the three major Google paper Hadoop. With the "bursting" of data, companies are racking their brains over large data processing, with the aim of being faster and more accurate. However, the recent new Open-source tool Summingbird has broken the rhythm of ...

Chen: Spark this year, from open source to hot

The Big data field of the 2014, Apache Spark (hereinafter referred to as Spark) is undoubtedly the most attention. Spark, from the hand of the family of Berkeley Amplab, at present by the commercial company Databricks escort. Spark has become one of ASF's most active projects since March 2014, and has received extensive support in the industry-the spark 1.2 release in December 2014 contains more than 1000 contributor contributions from 172-bit TLP ...

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