Data Query Language Definition

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The Apache hive is a Hadoop based tool that specializes in analyzing large, unstructured datasets using class-SQL syntax to help existing business intelligence and Business Analytics researchers access Hadoop content. 　　As an open source project developed by the Facebook engineers and recognized and contributed by the Apache Foundation, Hive has now gained a leading position in the field of large data analysis in the business environment. Like other components of the Hadoop ecosystem, hive ...

"Editor's note" This article is reproduced in the public number "Fu Zhihua", the author has been Tencent social networking business Group data center director and Tencent Data Association president.     Before Tencent, he worked in the market consulting, Analysys International, China Internet Association, and served as vice president of Dcci Internet Data Center. The internet industry in the accumulation of large data and applications to Baidu, Tencent and Alibaba is the most noteworthy. Baidu, Tencent and Alibaba in the application of large data although there is a common place, but due to their respective data sources and ...

With the development of the Internet, mobile Internet and IoT, no one can deny that we have actually ushered in a massive data era, data research company IDC expects 2011 total data will reach 1.8 trillion GB, the analysis of these massive data has become a very important and urgent demand. As an Internet data analysis company, we are "revolt" in the field of analysis of massive data. Over the years, with stringent business requirements and data pressures, we've tried almost every possible big data analysis method, and finally landed on the Hadoop platform ...

There are many methods for processing and analyzing large data in the new methods of data processing and analysis, but most of them have some common characteristics. 　　That is, they use the advantages of hardware, using extended, parallel processing technology, the use of non-relational data storage to deal with unstructured and semi-structured data, and the use of advanced analysis and data visualization technology for large data to convey insights to end users. 　　Wikibon has identified three large data methods that will change the business analysis and data management markets. Hadoop Hadoop is a massive distribution of processing, storing, and analyzing ...

One of the key decisions faced by enterprises that perform large data projects is which database to use, SQL or NoSQL? SQL has impressive performance, a huge installation base, and NoSQL is gaining considerable revenue and has many supporters. 　　Let's take a look at the views of two experts on this issue. Experts· VOLTDB's chief technology officer, Ryan Betts, says that SQL has won widespread deployments of large companies, and that big data is another area that it can support. Couchba ...

One of the key decisions that companies that perform large data [note] projects face is which database to use, SQL or NoSQL? SQL has impressive performance, a huge installation base, and NoSQL is gaining considerable revenue and has many supporters. 　　Let's take a look at the views of two experts on this issue. Experts· VOLTDB's chief technology officer, Ryan Betts, says that SQL has won widespread deployments of large companies, and that big data is another area that it can support. Couch ...

If you talk to people about big data, you'll soon be turning to the yellow elephant--hadoop (it's marked by a yellow elephant). 　　The open source software platform is launched by the Apache Foundation, and its value lies in its ability to handle very large data in a simple and efficient way. But what is Hadoop? To put it simply, Hadoop is a software framework that enables distributed processing of large amounts of data. First, it saves a large number of datasets in a distributed server cluster, after which it will be set in each server ...

When Hadoop enters the enterprise, it must face the problem of how to address and respond to the traditional and mature it information architecture. 　　In the industry, how to deal with the original structured data is a difficult problem for enterprises to enter large data field. When Hadoop enters the enterprise, it must face the problem of how to address and respond to the traditional and mature it information architecture. In the past, MapReduce was mainly used to solve unstructured data such as log file analysis, Internet click Stream, Internet index, machine learning, financial analysis, scientific simulation, image storage and matrix calculation. But ...

This year, big data has become a topic in many companies. While there is no standard definition to explain what "big Data" is, Hadoop has become the de facto standard for dealing with large data. Almost all large software providers, including IBM, Oracle, SAP, and even Microsoft, use Hadoop. However, when you have decided to use Hadoop to handle large data, the first problem is how to start and what product to choose. You have a variety of options to install a version of Hadoop and achieve large data processing ...