The greatest fascination with large data is the new business value that comes from technical analysis and excavation. SQL on Hadoop is a critical direction. CSDN Cloud specifically invited Liang to write this article, to the 7 of the latest technology to do in-depth elaboration. The article is longer, but I believe there must be a harvest. December 5, 2013-6th, "application-driven architecture and technology" as the theme of the seventh session of China Large Data technology conference (DA data Marvell Conference 2013,BDTC 2013) before the meeting, ...
The SQL Azure database is a relational database service provided by Microsoft based on cloud technology. Cloud-based Data solutions can offer many benefits, including fast provisioning, more economical scalability, high availability, and reduced management overhead. This article describes the dynamic management views available in SQL Azure and how to speak them for troubleshooting. Performance considerations SQL Azure uses the SQL Server 2008 data engine as the core. SQL Server 20 ...
In real life, backing up the database regularly is a very important thing. When we use MySQL, there is a lot of choice in database backup, and this article will show readers how to use MySQL's mysqldump to back up the database. First, the importance of data backup work, if the accidental deletion of important files or directories, then the result will be miserable. Especially when the data that is accidentally deleted involves important customers or key projects, and the data can't be recreated easily, it doesn't have to be what I say you can imagine. Unfortunately ...
The REST service can help developers to provide services to end users with a simple and unified interface. However, in the application scenario of data analysis, some mature data analysis tools (such as Tableau, Excel, etc.) require the user to provide an ODBC data source, in which case the REST service does not meet the user's need for data usage. This article provides a detailed overview of how to develop a custom ODBC driver based on the existing rest service from an implementation perspective. The article focuses on the introduction of ODBC ...
In large data technology, Apache Hadoop and MapReduce are the most user-focused. But it's not easy to manage a Hadoop Distributed file system, or to write MapReduce tasks in Java. Then Apache hive may help you solve the problem. The Hive Data Warehouse tool is also a project of the Apache Foundation, one of the key components of the Hadoop ecosystem, which provides contextual query statements, i.e. hive queries ...
Two days ago, someone asked questions on Weibo, in what way to tell the big data and cloud computing can not be heard by professionals more clearly, in fact, there are many cases of large data, business intelligence analysis has repeatedly mentioned the value and significance of data mining, but today to see more data than before, big data is not terrible, The scary thing is that his real-time analytics will expose flaws and truth to people, so when cloud computing encounters big data and a brain pours into companies, can companies manage? The so-called large data mainly covers 3V-oriented, respectively, the Treatment of aging (Veloci ...
In the past few years, the innovative development of the open source world has elevated the productivity of Java™ developers to one level. Free tools, frameworks and solutions make up for once-scarce vacancies. The Apache CouchDB, which some people think is a WEB 2.0 database, is very promising. It's not difficult to master CouchDB, it's as simple as using a Web browser. This issue of Java open ...
In an effort to reduce the high risk of sea death in the fishing industry, Royal National Lifeboat centric signed an agreement with Active Web FX (AWS) to create an automated offshore security application. AWS has developed a location-based service infrastructure, code-named "Geopoint", which transmits location data to the central tracking and alerting system. AWS uses Geopoint to build MOB Gu ...
It has been almost 2 years since the big data was exposed and the customers outside the Internet were talking about big data. It's time to sort out some of the feelings and share some of the puzzles that I've seen in the domestic big data application. Clouds and large data should be the hottest two topics in the IT fry in recent years. In my opinion, the difference between the two is that the cloud is to make a new bottle, to fill the old wine, the big data is to find the right bottle, brew new wine. The cloud is, in the final analysis, a fundamental architectural revolution. The original use of the physical server, in the cloud into a variety of virtual servers in the form of delivery, thus computing, storage, network resources ...
As companies begin to leverage cloud computing and large data technologies, they should now consider how to use these tools in conjunction. In this case, the enterprise will achieve the best analytical processing capabilities, while leveraging the private cloud's fast elasticity (rapid elasticity) and single lease features. How to collaborate utility and implement deployment is the problem that this article hopes to solve. Some basic knowledge first is OpenStack. As the most popular open source cloud version, it includes controllers, computing (Nova), Storage (Swift), message team ...
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