Fast Data Processing With Spark

The development of spark for a platform with considerable technical threshold and complexity, spark from the birth to the formal version of the maturity, the experience of such a short period of time, let people feel surprised. Spark was born in Amplab, Berkeley, in 2009, at the beginning of a research project at the University of Berkeley. 　　It was officially open source in 2010, and in 2013 became the Aparch Fund project, and in 2014 became the Aparch Fund's top project, the process less than five years time. Since spark from the University of Berkeley, make it ...

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 ...

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 ...

In attracting Cloudera, DataStax, MapR, Pivotal, Hortonworks and many other manufacturers to join, Spark technology in Yahoo, EBay, Twitter, Amazon, Ali, Tencent, Baidu, Millet, BEIJING-East and many other well-known domestic and foreign enterprises to practice. In just a year, spark has become open source to the hot, and gradually revealed the common big data platform with Hadoop's Chamber of the potential to fight. However, as a high-speed development of open source projects, the deployment process of ...

At the moment, http://www.aliyun.com/zixun/aggregation/13383.html ">spark has gained popularity, and a distributed computing approach based on map reduce makes spark similar to Hadoop, 　　It is more versatile than Hadoop, with more efficient iterations and more fault-tolerant capabilities, and future spark will be a very successful parallel computing framework. "Editor's note" author Mikio Braun is Berlin industrial big ...

Spark is a memory-based, open-source cluster computing system designed for faster data analysis. Spark was developed using Scala by Matei, AMP Labs, University of California, Berkeley. The core part of the code is only 63 Scala files, which is very lightweight. Spark provides an open source clustered computing environment similar to Hadoop, but Spark performs better on some workloads based on memory and iteratively optimized designs. & nbs ...

As a common parallel processing framework, http://www.aliyun.com/zixun/aggregation/13383.html ">spark has some advantages like Hadoop, and Spark uses better memory management, In iterative computing has a higher efficiency than Hadoop, Spark also provides a wider range of data set operation types, greatly facilitate the development of users, checkpoint application so that spark has a strong fault tolerance, many ...

The authors observed that http://www.aliyun.com/zixun/aggregation/14417.html ">apache Spark recently issued some unusual events databricks will provide $ 　　14M USD supports Spark,cloudera decision to support Spark,spark is considered a big issue in the field of large data. The beautiful first impressions of the author think that they have been used with Scala's API (spark).

April 19, 2014 Spark Summit China 2014 will be held in Beijing. The Apache Spark community members and business users at home and abroad will be gathered in Beijing for the first time. Spark contributors and front-line developers from AMPLab, Databricks, Intel, Taobao, NetEase, and others will share their Spark project experience and best practices in production environments. MapR is well-known Hadoop provider, the company recently for its Ha ...

The authors observed that Apache Spark recently sent some unusual events, Databricks will provide $14m USD support Spark,cloudera decided to support Spark,spark is considered a big issue in the field of large data. A good first impression the author believes that he has been dealing with Scala's API (spark using Scala) for some time, and, to tell you the truth, was very impressive at first because spark was so small and good. The basic abstraction is the projectile ...