Database multi-connection query optimization method based on evolutionary algorithm

An evolutionary algorithm and query optimization technology, which is applied in the fields of electrical digital data processing, special data processing applications, and computing. It can solve problems such as local optimal solutions, reduce the probability of falling into local optimality, shorten the search time, and speed up the query. The effect of processing speed

Inactive Publication Date: 2017-12-12
CAS OF CHENGDU INFORMATION TECH CO LTD
View PDF3 Cites 7 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Therefore, in view of the above problems, it is necessary to propose a new optimization method based on evolutionary computing to solve the defect that the SDD-1 algorithm is prone to fall into local optimal solutions when generating query plans, significantly reduce the generation time of query plans, and improve the performance of join queries. query efficiency

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Database multi-connection query optimization method based on evolutionary algorithm
  • Database multi-connection query optimization method based on evolutionary algorithm
  • Database multi-connection query optimization method based on evolutionary algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0019] A database multi-join query optimization method based on evolutionary algorithm, such as figure 1 shown, including the following steps:

[0020] Step 1. Preprocess the original data, perform unary operations such as projection on each distributed database node, and simplify the original data. The above streamlined data is merged and sorted according to each attribute, so that each attribute forms an ordered intermediate data sequence, and the query graph G is further constructed.

[0021] 1.1 Assuming that R and S are two relationships, they have attributes A and B, and the connection operation of A and B has:

[0022]

[0023] where ∞ represents the join operation, π B (S) represents the projection of relation S on attribute B.

[0024] 1.2 Perform a merge operation on the database relational table, that is, read the content of a block from each sorted sub-table in order and put it into the memory, and perform a merge operation on the records in these blocks unif...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a database multi-connection query optimization method based on an evolutionary algorithm. According to the method, first, a data preprocessing technology and a bidirectional semi-connection technology are introduced into an SDD-1 algorithm, projection and other unary operation are adopted to simplify data, meanwhile, data of all nodes is ordered by merging, and row data and column data can be reduced at the same time through the bidirectional semi-connection technology; second, all beneficial bidirectional semi-connections are calculated and added into a set BS, a parallel genetic algorithm is adopted to solve a connection query strategy of the SDD-1 algorithm, a group initialization method, a fitness function and a relevant genetic operator suitable for the problem are constructed, and a protocol optimal query path for solving the problem is obtained; and last, the query path is used to initialize a pheromone matrix of an ant colony algorithm, a multi-ant-colony optimization method is utilized to solve an optimal query path again, and the problem that the parallel genetic algorithm has a weak local search ability is solved.

Description

technical field [0001] The invention belongs to the application field of computer information technology, and specifically relates to the optimization of the connection execution strategy of the distributed database, which can be used to optimize the connection execution strategy of the distributed database and reduce the execution time of large-scale multi-connection query. Background technique [0002] With the maturity of traditional database technology, the rapid development of computer network technology and the expansion of application scope, the research and development of distributed database system has attracted people's attention. As an important operation in distributed databases, multi-relational join query is a difficulty that needs to be overcome in query optimization. Distributed query processing has the ability to access the data of remote sites through the communication network, as well as the ability to transmit requests and data between different sites. T...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
CPCG06F16/24544G06F16/2455
Inventor 孙治秦小林张力戈王文彬王会勇
Owner CAS OF CHENGDU INFORMATION TECH CO LTD
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products