Learn Sql 2012

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Learn big data from top ten technology and top ten Giants

Big data has grown rapidly in all walks of life, and many organizations have been forced to look for new and creative ways to manage and control such a large amount of data, not only to manage and control data, but to analyze and tap the value to facilitate business development. Looking at big data, there have been a lot of disruptive technologies in the past few years, such as Hadoop, Mongdb, Spark, Impala, etc., and understanding these cutting-edge technologies will also help you better grasp the trend of large data development. It is true that in order to understand something, one must first understand the person concerned with the thing. So, ...

Microsoft releases some significant updates to Windows Azure

This morning we released some significant updates to Windows Http://www.aliyun.com/zixun/aggregation/13357.html ">azure." These new features include: SQL Server support: Windows Azure virtual machines support general availability (including high availability and disaster recovery) Notification Center: The general availability version of Windows Azure Notification Center (Windows 8, Windo ...).

The present situation and future development of 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 ...

Microsoft enterprise-wide data analysis strategy: integrating Hadoop

A few months ago, Microsoft announced its own version of the Hadoop release hdinsight for Big Data management, analytics and mining.   The reporter contacted the senior product marketing manager, Val Fontama, of SQL Server, hoping to learn more about Microsoft's corporate-class data. On the growth trend in the size of datasets in the enterprise: The ocean of data has been growing. There is a forecast that the volume of business information is doubled each year. For example, Gartner found all ...

Overview Big Data

Big data has grown rapidly in all walks of life, and many organizations have been forced to look for new and creative ways to manage and control such a large amount of data, not only to manage and control data, but to analyze and tap the value to facilitate business development. Looking at big data, there have been a lot of disruptive technologies in the past few years, such as Hadoop, Mongdb, Spark, Impala, etc., and understanding these cutting-edge technologies will also help you better grasp the trend of large data development. It is true that in order to understand something, one must first understand the person concerned with the thing. So, ...

"Pioneer" Simin software large data technology platform to create the process and impala real-combat sharing

In the interview of Simin data Liu Chengzhong, he said that the current large data domain enterprise-level market rely on technology monopoly to obtain high profits of the game is outdated, the cost of technology will continue to decline, this is the general trend, the market giant will appear in the technology is very good, but better service companies. From the user's point of view, the user's first concern is how to make the data value, then the solution depends on what kind of technology, whether it can quickly apply, whether it can adapt to the next possible expansion, relative technology, 1th is more difficult. In fact, today's corporate customers, particularly in the field of large data technology, ...

Sun Yuanhao: Spark engine-based high-speed memory analysis and mining tools

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 ...

BDTC ppt Collection (iii): BAT, IBM, Intel shared large data technology

From the 2008 60-man "Hadoop in China" technology salon, to the current thousands of-person scale of the industry technology feast, the seven-year BDTC (large data technology conference) has fully witnessed the transformation of China's large data technology and applications, faithfully depicting the large data field of technology hotspots, Precipitated countless valuable industry experience. At the same time, from December 2014 12 to 14th, the largest China data technology event will continue to lead the current field of technology hotspots, sharing the industry experience. In order to better understand the trend of industry development, understanding of enterprises ...

2014 worth of attention 10 Hadoop large data processing companies

Open source Large data frame Apache Hadoop has become a fact standard for large data processing, but it is also almost synonymous with large numbers, although this is somewhat biased.   According to Gartner, the current market for Hadoop ecosystems is around $77 million trillion, which will grow rapidly to $813 million in 2016. But it's not easy to swim in the fast-growing blue sea of Hadoop, it's hard to develop large data infrastructure technology products, and it's hard to sell, specifically ...

2014 10 Big Hadoop data startups worth watching

Open source Large data frame Apache Hadoop has become a fact standard for large data processing, but it is also almost synonymous with large numbers, although this is somewhat biased. According to Gartner, the current market for Hadoop ecosystems is around $77 million trillion, which will grow rapidly to $813 million in 2016. But it's not easy to swim in the fast-growing blue sea of Hadoop, not only is it hard to develop large data infrastructure technology products, but it's hard to sell, particularly to big data infrastructures ...

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