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Database coordination optimization method based on big data dynamic planning

A technology of dynamic planning, coordination and optimization, applied in database design/maintenance, structured data retrieval, special data processing applications, etc., can solve the problems of low transmission efficiency, long data transmission time, large transmission errors, etc., to improve transmission efficiency , the effect of saving memory space and saving traffic

Inactive Publication Date: 2020-11-03
江苏哩咕信息科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At present, since all network data needs to be stored centrally in the server where the database is located, these data need to be transmitted through the network from the respective network management server to the local server where the data warehouse is located. However, a large amount of data needs to be transmitted, and network bandwidth resources But it is limited, usually only tens of megabytes per second, the data transmission time is too long, the probability of transmission error is high, and the transmission efficiency is low

Method used

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  • Database coordination optimization method based on big data dynamic planning
  • Database coordination optimization method based on big data dynamic planning
  • Database coordination optimization method based on big data dynamic planning

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Experimental program
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Embodiment 1

[0031] refer to figure 1 with figure 2 , which is the first embodiment of the present invention, provides a database coordination optimization method based on big data dynamic programming, including:

[0032] S1: Divide the complete set of data to be transmitted into data primitives by adopting the data flow block strategy. It should be noted that the division of data primitives includes:

[0033] Based on the quaternary information system description principle, the following calculations are performed,

[0034]

[0035] Among them, G bi for feature b i The value set of , W is the complete set of all individuals in the data system, which is a non-empty finite set, b is the characteristic of the individual, G a is the value range of feature b.

[0036] Further, it also includes:

[0037] Use the data operation matrix to map to the complete set of data, define W={d1,d2...dn}, b={MS1,MS2...MSq}, G a = OPr is the value range of feature b, namely G a =∪1≤i≤n, 1≤j≤qOPrij;...

Embodiment 2

[0064] In order to better verify and explain the technical effects adopted in the present invention, this embodiment chooses to conduct a comparative test with the traditional distributed database collaborative optimization method and the method of the present invention, and compares the test results by means of scientific demonstration to verify the results of the method of the present invention. have real effects.

[0065] The traditional collaborative optimization method for distributed databases has limited scope of application, low practicability, and cannot play a good role in reconciling data efficiency. In order to verify that the method of the present invention has higher transmission efficiency than the traditional method, this embodiment In this paper, the traditional method and the method of the present invention will be used to measure and compare the data file transmission efficiency of the four network types in real time.

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Abstract

The invention discloses a database coordination optimization method based on big data dynamic programming, which comprises the following steps: dividing a complete set of data to be transmitted into data elements by adopting a data flow partitioning strategy; converting data primitives into a two-dimensional table structure by utilizing a binary serialization compression strategy, and carrying outrun-length hybrid coding and compression; and constructing an optimization model based on a multi-objective optimization strategy, dynamically optimizing the compressed data primitives, and transmitting the optimized data primitives. The data primitives are divided through the data flow blocking strategy, the binary serialization compression strategy is used for reducing the data transmission amount and the size of transmitted data, meanwhile, redundant and repeated data is removed in combination with the optimization model, the memory space and unnecessary transmission are saved, the transmission efficiency is greatly improved, the flow is saved, and the space is saved; and the method has positive significance for promoting big data optimization research.

Description

technical field [0001] The invention relates to the technical fields of cloud computing, big data and database optimization, and in particular to a database coordination and optimization method based on big data dynamic programming. Background technique [0002] Dynamic programming programming is a way and a method to solve optimization problems, rather than a special algorithm. Unlike search or numerical calculation, it has a standard mathematical expression and a clear and clear problem-solving method. Planning programming is often aimed at an optimization problem. Due to the different nature of various problems, the conditions for determining the optimal solution are also different. Therefore, the design method of dynamic programming has its own unique problem-solving methods for different problems. , there is no universal dynamic programming algorithm that can solve various optimization problems. [0003] Simply put, the database itself can be regarded as an electronic ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/21
CPCG06F16/217
Inventor 杨璐绮李海坤王悦华
Owner 江苏哩咕信息科技有限公司