Big Data Analysis With Spark

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 ...

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 ...

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 ...

Spark is a cluster computing platform originating from the Amplab of the University of California, Berkeley, which is based on memory computing and has more performance than Hadoop, and is a rare all-around player, starting with multiple iterations, eclectic data warehousing, streaming, and graph computing paradigms. 　　Spark uses a unified technology stack to solve the cloud computing large data stream processing, graph technology, machine learning, NoSQL query and other aspects of all the core issues, with a perfect ecosystem, which directly laid its unified cloud computing large data field hegemony. ...

According to relevant data, China's mobile internet users in the first half of 2013 has exceeded the 500 million mark, is expected in the first quarter of 14, the domestic mobile internet users will be over the PC, mobile phone users more than 1 billion, 3G users continue to grow, as well as 4G strong momentum, have spawned mobile large data explosion. 　　A lot of new data is emerging all the times, and the mobile Internet is affecting all aspects of human life. This will be an unprecedented era. All companies and institutions are or are becoming mobile internet organizations. All companies and institutions will eventually be big data organizations for cloud computing. Move ...

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. The following is a reporter interviewed the original: - What are the reasons to attract you to study Spark ...

In the past few years, the use of Apache Spark has increased at an alarming rate, usually as a successor to the MapReduce, which can support thousands of-node-scale cluster deployments. In the memory data processing, the Apache spark is more efficient than the mapreduce has been widely recognized, but when the amount of data is far beyond memory capacity, we also hear some organizations in the spark use of trouble. Therefore, with the spark community, we put a lot of energy to do spark stability, scalability, performance, etc...

Since May 30, the Apache Software Foundation announced the release of the open source Platform Spark 1.0, Spark has repeatedly headlines, has been the focus of data experts. 　　But is Spark's business application era really coming? From the recent Spark Summit in the United States, we are still full of confidence in spark technology. Spark is often considered a real-time processing environment, applied to Hadoop, NoSQL databases, AWS, and relational databases, and can be used as an API for application interfaces, and programmers process data through a common program ...

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 ...