Cross-platform large data processing load distributing system and method
A data processing, cross-platform technology, applied in database management systems, electronic digital data processing, special data processing applications, etc., can solve problems such as data loss, reduce the accuracy of large-scale data, and the central server cannot process data in time, so as to alleviate Burden, the effect of improving processing capacity and accuracy of analysis
Inactive Publication Date: 2014-03-05
DONGGUAN FOOCAA NETWORK TECH
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Problems solved by technology
However, this data processing method has the following defects: (1) In this era of increasing information, when the central server needs to process more data, a high-performance central server is necessary; (2) When analyzing and sampling data At present, the consistency of data structure and format must be guaranteed, but the central server receives large-scale data from various platforms. In most cases, the data of each platform has inconsistencies in structure and format, which increases the burden on the central server. burden, and it is very easy to cause the central server to be unable to process all the data that needs to be processed in time, and even cause data loss in severe cases, which greatly reduces the processing capacity of large data and the accuracy of analysis
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[0030] Embodiments of the present invention will now be described with reference to the drawings, in which like reference numerals represent like elements
[0031] Please refer to figure 1 , The cross-platform large-scale data processing and offloading system of the present invention includes multiple pre-processing terminals (1, 2,...n) and a central server, and the multiple pre-processing terminals correspond to multiple platforms (1, 2,. ...n), and there is a one-to-one correspondence between multiple pre-processing terminals and multiple platforms. Each processing terminal receives large-scale data from each platform, and converts the large-scale data for transmission, and the central server receives the converted large-scale data transmitted by multiple pre-processing terminals, and analyzes and samples the converted large-scale data .
[0032] Specifically, please refer to figure 2 , each pre-processing terminal includes:
[0033] Receiving module 10, is used for re...
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The invention discloses a cross-platform large data processing load distributing system. The system comprises at least two front processing terminals and a central server. The front processing terminals receive large data from platforms and convert the data. The central server receives the large data and carries out analyzing and sampling on the converted large data. Compared with the prior art, the front processing terminals are used for receiving the large data from different platforms and converting the large data so that the formats of the large data transmitted to the central server from different platforms are uniform and are required data formats of the central server. Thus, a high-performance central server is not needed, burdens of the central server are reduced and therefore, the central server can process all the data needing processing in time. Losses of the data will not occur and the capacity for processing the large data and the analysis accuracy of the central server are improved. The invention further discloses a cross-platform large data processing load distributing method.
Description
technical field [0001] The invention relates to the technical field of cross-platform large-scale data processing, and more particularly relates to a system and method for cross-platform large-scale data processing load sharing. Background technique [0002] Currently, a single central server is often used for data analysis and sampling when dealing with cross-platform large-scale data. However, this data processing method has the following defects: (1) In this era of increasing information, when the central server needs to process more data, a high-performance central server is necessary; (2) When analyzing and sampling data At present, the consistency of data structure and format must be guaranteed, but the central server receives large-scale data from various platforms. In most cases, the data of each platform has inconsistencies in structure and format, which increases the burden on the central server. And it is very easy to cause the central server to be unable to proc...
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IPC IPC(8): G06F17/30
CPCG06F16/25
Inventor 黄彤元
Owner DONGGUAN FOOCAA NETWORK TECH