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Large Data Technology stickers: Building a guided data mining model

The purpose of data mining is to find more quality users from the data. Next, we continue to explore the model of the guidance data mining method. What is a guided data mining method model and how data mining builds the model. In building a guided data mining model, the first step is to understand and define the target variables that the model attempts to estimate. A typical case, two-dollar response model, such as selecting a customer model for direct mailing and e-mail marketing campaigns. The build of the model selects historical customer data that responds to similar activities in the past. The purpose of guiding data mining is to find more similar ...

Detailed Hadoop core architecture

Through the introduction of the core Distributed File System HDFS, MapReduce processing process of the Hadoop distributed computing platform, as well as the Data Warehouse tool hive and the distributed database HBase, it covers all the technical cores of the Hadoop distributed platform. Through this stage research summary, from the internal mechanism angle detailed analysis, HDFS, MapReduce, Hbase, Hive is how to run, as well as based on the Hadoop Data Warehouse construction and the distributed database interior concrete realization. If there are deficiencies, follow-up ...

Nine programming languages needed for large data processing

With the upsurge of large data, there are flood-like information in almost every field, and it is far from satisfying to do data processing in the face of thousands of users ' browsing records and recording behavior data. But if only some of the operational software to analyze, but not how to use logical data analysis, it is also a simple data processing. Rather than being able to go deep into the core of the planning strategy. Of course, basic skills is the most important link, want to become data scientists, for these procedures you should have some understanding: ...

Nine programming languages needed for large data processing

With the upsurge of large data, there are flood-like information in almost every field, and it is far from satisfying to do data processing in the face of thousands of users ' browsing records and recording behavior data. But if only some of the operational software to analyze, but not how to use logical data analysis, it is also a simple data processing. Rather than being able to go deep into the core of the planning strategy. Of course, basic skills is the most important link, want to become data scientists, for these procedures you should have some understanding: ...

Java Development 2.0: Implementing REST through CouchDB and Groovy restclient

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 ...

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Trends in large data-processing technology-introduction of five open source technologies

Large data areas of processing, my own contact time is not long, formal projects are still in development, by the large data processing attraction, so there is the idea of writing articles. Large data is presented in the form of database technologies such as Hadoop and "NO SQL", Mongo and Cassandra. Real-time analysis of data is now likely to be easier. Now the transformation of the cluster will be more and more reliable, can be completed within 20 minutes. Because we support it with a table? But these are just some of the newer, untapped advantages and ...

10 program languages to help you read the "Secrets" of Big Data

With the upsurge of large data, there are flood-like information in almost every field, and it is far from satisfying to do data processing in the face of thousands of users ' browsing records and recording behavior data.   But if only some of the operational software to analyze, but not how to use logical data analysis, it is also a simple data processing.   Rather than being able to go deep into the core of the planning strategy. Of course, basic skills is the most important link, want to become data scientists, for these procedures you should have some understanding ...

R language for Hadoop injection of statistical blood

R is a GNU open Source Tool, with S-language pedigree, skilled in statistical computing and statistical charting. An open source project launched by Revolution Analytics Rhadoop the R language with Hadoop, which is a good place to play R language expertise. The vast number of R language enthusiasts with powerful tools Rhadoop, can be in the field of large data, which is undoubtedly a good news for R language programmers. The author gave a detailed explanation of R language and Hadoop from a programmer's point of view. The following is the original: Preface wrote several ...

Five-step implementation of cloud computing PAAs security

When it comes to security and cloud computing models, the platform as a service (PaaS) has its own special challenges. Unlike other cloud computing models, PAAs security requires application security expertise that most companies can not invest heavily in. This is a complex issue because many companies use the "cantonment" infrastructure-level security control strategy as a response to application-level security risks (for example, once the application code releases production, use WAF to mitigate the discovery of cross-site scripting or other front-end problems). Due to the lack of PAAs ...

Cloud security issues and precautionary measures inventory

The first problem that cloud security faces is the technology and management problems in the virtualized environment. Traditional protection mechanism based on physical security boundary is difficult to effectively protect user application and information security based on shared virtualization environment. In addition, the cloud computing system is so large, and mainly through the virtual machine to calculate, in the event of failure, how to quickly locate the problem is also a major challenge. Secondly, it is the problem that the service model of cloud computing separates the ownership, management and right of use of the resources. Cloud computing, a new service model, separates the ownership, management, and use of resources.

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