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The research and design of SQL processing in a data-mining system based on MapReduce

Authors: Lei Zhang; Kaiping Li; Bin Wu;

The research and design of SQL processing in a data-mining system based on MapReduce

Abstract

SQL as a database language has been widely used in the modern society. Its function mainly focuses on the data processing, which can be used in data-mining. Due to the rapid growth of data, large-scale data processing is becoming a focal point of information techniques. Though we can still use SQL, but where to store the data and how to get the data efficiently, cost effectively, can be a tricky problem. Cloud computing emerges to solve the problem. It is mainly to deal with large-scale data processing. In this paper, we design a data-mining system which can directly deal with SQL processing based on Hadoop, a parallel store and computing platform. Then we will have a discussion about running time's efficiencies.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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