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Dynamic-planning data fragment optimizing method based on range query boundary set

A technology of data sharding and dynamic programming, which is applied in the direction of electrical digital data processing, special data processing applications, instruments, etc., can solve the problems of poor feasibility and achieve the effect of improving search efficiency

Inactive Publication Date: 2018-08-21
GUANGXI NORMAL UNIV
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Problems solved by technology

Such problems can be solved by enumeration, but the complexity of enumeration methods is mostly exponential, and the feasibility is poor

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  • Dynamic-planning data fragment optimizing method based on range query boundary set

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Embodiment

[0015] A dynamic programming data fragmentation optimization method based on range query boundary sets, comprising the following steps:

[0016] 1) Establish the data access probability model under the range query load: define the set of all boundaries of the range query on the data set is called the range query boundary set, in the record-based data organization mode, the query cumulative probability of a data record = data record Number of visits by query load / total number of queries, in the data organization method based on data slices, define the kth data slice DS k has a length of l k , data slice DS k The query cumulative probability on P k , data slice DS k Query the cumulative probability P k The value is DS k the maximum value of the query cumulative probability of the contained data records;

[0017] 2) Find the optimal K-slice: Based on the dynamic programming method, the optimization goal of finding the optimal K-slice can be decomposed into finding an optima...

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Abstract

The invention discloses a dynamic-planning data fragment optimizing method based on a range query boundary set. The dynamic-planning data fragment optimizing method is characterized by comprising thefollowing steps that 1, a data access probability model under a range query load is established; 2, an optimal K-fragment is found; 3, the step 2 is repeated, calculation of the optical query cost canbe constantly iterated and decomposed until all K-1 optimal fragment positions b1, b2, ..., bK-1 are found, the optical targets are converted into the sum of query costs C (bi, bj), I and j<[1, N] ofa set of data fragments. By adopting the dynamic-planning method, the optimal fragment positions are searched in the range query boundary set, and the optimal data fragments can reduce the cost of data management and maintenance, as well as the cost of locating and transmitting in data query, and improve query efficiency.

Description

technical field [0001] The invention relates to a data fragmentation optimization technology under a range query load with inclined characteristics on big data, in particular to a dynamic programming data fragmentation optimization method based on a range query boundary set. Background technique [0002] Data sharding is a kind of horizontal or vertical partitioning of tables. It is a countermeasure for data management systems in the face of large-scale data, that is, it adopts the idea of ​​​​"divide and conquer" to manage data. The original data is organized and managed at the granularity of records, which is expensive. The query of each record brings location and addressing overhead and transmission overhead. Therefore, query optimization based on the record-based data organization method has limited improvement in query performance. . [0003] In some combinatorial optimization problems, the goal of optimization is to maximize or minimize some specific objective value. ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
CPCG06F16/2282
Inventor 葛微李先贤王金艳
Owner GUANGXI NORMAL UNIV
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