BlogRank algorithm parallelization processing construction method based on Haloop

A construction method and algorithm technology, applied in the field of cloud computing, can solve problems such as algorithm efficiency improvement, and achieve the effect of improving efficiency, improving efficiency, and reducing I/O consumption

Inactive Publication Date: 2013-09-04
HOHAI UNIV
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AI Technical Summary

Problems solved by technology

They all aim to improve the operating efficiency of the algorithm by reducing the number of iterations of the algorithm, speeding up the convergence speed of the algorithm,

Method used

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  • BlogRank algorithm parallelization processing construction method based on Haloop
  • BlogRank algorithm parallelization processing construction method based on Haloop
  • BlogRank algorithm parallelization processing construction method based on Haloop

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Embodiment Construction

[0023] Below in conjunction with specific embodiment, further illustrate the present invention, should be understood that these embodiments are only used to illustrate the present invention and are not intended to limit the scope of the present invention, after having read the present invention, those skilled in the art will understand various equivalent forms of the present invention All modifications fall within the scope defined by the appended claims of the present application.

[0024] like figure 1 As shown, this embodiment preprocesses the blog data according to the parallelization idea of ​​the BlogRank algorithm based on the MapReduce model; abstracts each iteration process of the algorithm into a MapReduce model, and distinguishes the input data set according to the variability of the data in the iteration process. Determine the appropriate iteration termination conditions and the maximum number of iterations; use the programming interface provided by the Haloop fram...

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Abstract

The invention discloses a blogRank algorithm parallelization processing construction method based on Haloop. Blog data are preprocessed; every iterative process of the algorithm is abstracted into a MapReduce model, and the model is composed of two concrete MapReduce processes; cyclic invariables and cyclic variables in the iterative process are separated; appropriate iteration end conditions and the maximum iteration times are set; calculation is performed with a programmatic interface provided by a Haloop frame. After the test, under the condition of a large data volume, compared with a traditional one-machine computing method applying the matrix and a distributed computing method applying a Hadoop frame, the construction method applying the Haloop frame obviously promotes operating efficiency, and the larger the data volume is, the more the efficiency is promoted. The method can effectively reduces the effect on executing efficiency of the BlogRank algorithm caused by iteration, and can well adapt to requirements for processing a large volume of data with the algorithm.

Description

technical field [0001] The invention relates to a construction method for parallel processing of BlogRank algorithm based on a Haloop framework, which belongs to the research on parallel algorithm in the field of cloud computing. Background technique [0002] With the rapid development of the Internet, more and more users use blogs. Blog posts in the blog system are updated more and more frequently, and the number is also increasing. How to enable users to search for the blog post they want in a large number of blog posts in a short time? It is very important to establish a good and efficient blog evaluation system. The BlogRank algorithm is proposed based on blog metrology and PageRank algorithm. It is an algorithm used to quantify the "influence" of blogs and is an important part of the blog evaluation system. The final result of this algorithm is the ranking of all blogs. Ranking value (that is, BR value, between 1 and 10, the larger the BR value, the more valuable the...

Claims

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Application Information

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IPC IPC(8): G06F9/38
Inventor 娄渊胜张文渊叶枫许峰陈胜
Owner HOHAI UNIV
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