Monthly Archives: January 2014

Parallel Computing and Column Storage in one program language

The columnar storage is good, especially when there are lots of tabular fields (this is quite common). In querying, the data to traverse is far less than that on the row storage. Less data to traverse brings less I/O workloads … Continue reading

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6 Desktop BI Tools

Recently, I finished a project which involves using the Excel, R Project, and es-series in combination. An idea occurred to me in the work. Why not put them along with the Matlab, SPSS, and Stata side-by-side to make an introductions … Continue reading

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Data source preparation, an obstacle in report developing

To date, the reporting tools have been developed pretty well. We have embraced a lot of emerging tools like Qlikview, Tableau, Spotfire, and still have the choices of classic tools like Sap Visual Intelligence, JasperReport, and Cognos. However, in developing … Continue reading

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Hadoop would not be complex with agile program language

Hadoop is an outstanding parallel computing system whose default parallel computing mode is MapReduce. However, such parallel computing is not specially designed for parallel data computing. Plus, it is not an agile parallel computing program language, the coding efficiency for … Continue reading

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Five Methods Solving Big Data Computing, Migration and Integration in Java

The computing layer is a layer between the data storage layer and the application layer. This layer is responsible for computing the data from data storage layer, and return the result to the application layer, with an aim to reduce … Continue reading

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An example to illustrate hadoop code reuse

The MapReduce of Hadoop is a widely-used parallel computing framework. However, its code reuse mechanism is inconvenient, and it is quite cumbersome to pass parameters. Far different from our usual experience of calling the library function easily, I found both … Continue reading

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Big data will be a big failure?

Recently, I read Why Big Data Projects Fail by Stephen Brobst athttp://data-informed.com/why-big-data-projects-fail. I can’t agree more with his opinions which exposed the problem I’ve been worried about. In this article, I am going to further discuss this topic to remind … Continue reading

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